Compare commits

..

571 Commits

Author SHA1 Message Date
Alexander Smorkalov
616fd50947 Release 5.0.0-alpha. 2024-12-05 11:54:05 +03:00
Gursimar Singh
816851c999 Merge pull request #26202 from gursimarsingh:improved_tracker_samples
Improved Tracker Samples #26202

Relates to #25006

This sample has been rewritten to track a selected target in a video or camera stream. It combines VIT tracker, Nano tracker and Dasiamrpn tracker into one tracker sample

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-12-05 11:50:03 +03:00
Abduragim Shtanchaev
0c774c94f9 Merge pull request #26573 from Abdurrahheem:ash/fix-gpt2-sample
Fix gpt2 sample #26573

This PR adds dynamic input support for `gpt2_inference.py` sample.
Fixes #26518
Fixes #26517

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-12-05 11:34:49 +03:00
Alexander Smorkalov
ddfb9d1dc8 Merge pull request #26572 from FantasqueX:fix-typo-3
fix typo modfication
2024-12-05 09:10:41 +03:00
Vadim Pisarevsky
446787ab48 Merge pull request #26571 from vpisarev:fix_26497
Fixed issue when std::vector<T> is wrapped into Mat with explicit step. #26571

Hopefully, fixes #26497

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-12-05 09:03:51 +03:00
FantasqueX
91a0bdb6ea fix typo modfication 2024-12-04 23:51:39 +08:00
Alexander Smorkalov
c69b5524ff Merge pull request #26570 from asmorkalov:as/more_types_java
More type constants for Java bindings too.
2024-12-04 17:18:46 +03:00
Alexander Smorkalov
95659ebe97 Merge pull request #26568 from asmorkalov:as/more_types_objc_swift
More data types support in Obj-C  and Swift bindings
2024-12-04 16:56:38 +03:00
Alexander Smorkalov
644cf0de08 More data types support in Obj-C and Swift bindings. 2024-12-04 16:00:57 +03:00
Alexander Smorkalov
cb1e6250e6 More type constants for Java bindings too. 2024-12-04 15:51:58 +03:00
Alexander Smorkalov
69d0aacc2a Merge pull request #26567 from FantasqueX:fix-typo-2
fix typo in AlgorithmHint description
2024-12-04 14:27:20 +03:00
Letu Ren
2b28a6e205 fix typo in AlgorithmHint description 2024-12-04 16:51:32 +08:00
Alexander Smorkalov
3b1ec72cf5 Merge pull request #26559 from asmorkalov:as/mattype_fix_ios
Fixed cv::Mat type constants in ObjC and Swift.
2024-12-03 12:58:59 +03:00
Alexander Smorkalov
22d4735de1 Merge pull request #26558 from mshabunin:fix-doc-1.12-5x
doc: fixed issue with doxygen 1.12 (5.x)
2024-12-02 17:16:43 +03:00
Alexander Smorkalov
0c4fd4f7ee Fixed cv::Mat type constants in ObjC and Swift. 2024-12-02 17:13:25 +03:00
Alexander Smorkalov
650f2c3da3 Merge pull request #26551 from Kumataro:fix26550
doc: update introduction for new MatDepth(5.x)
2024-12-02 14:01:15 +03:00
Maksim Shabunin
a492068a3a doc: fixed issue with doxygen 1.12 2024-12-02 13:52:10 +03:00
Gursimar Singh
efbe580ff3 Merge pull request #26486 from gursimarsingh:object_detection_engine_update
Code Fixes and changed post processing based on models.yml in Object Detection Sample #26486

## Major Changes

1. Changes to add findModel support for config file in models like yolov4, yolov4-tiny, yolov3, ssd_caffe, tiny-yolo-voc, ssd_tf and faster_rcnn_tf.
2. Added new model and config download links for ssd_caffe, as previous links were not working.
3. Switched to DNN ENGINE_CLASSIC for non-cpu convig as new engine does not support it.
4. Fixes in python sample related to yolov5 usage.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-12-02 09:05:25 +03:00
Kumataro
5b03d82814 doc: update introduction for new MatDepth 2024-12-01 08:13:08 +09:00
Yuantao Feng
b476ed6d06 Merge pull request #26505 from fengyuentau:imgproc/new_nearest_inter
imgproc: optimized nearest neighbour interpolation for warpAffine, warpPerspective and remap #26505

PR Description has a limit of 65536 characters. So performance stats are attached below.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-30 10:41:21 +03:00
Alexander Smorkalov
b7dacbd5e3 Merge pull request #26535 from mshabunin:fix-qr-bitstream-5x
objdetect: fix invalid vector access in QR encoder (5.x)
2024-11-29 17:56:33 +03:00
Maksim Shabunin
18e8d69097 objdetect: fix invalid vector access in QR encoder 2024-11-29 14:52:41 +03:00
Alexander Smorkalov
0213483c18 Merge branch 4.x 2024-11-28 13:20:39 +03:00
Alexander Smorkalov
b31bc1a295 Merge pull request #26545 from asmorkalov:as/python_missing_type_stubs
Added some mssing type constants to python type stubs generator.
2024-11-28 12:15:24 +03:00
Alexander Smorkalov
d0ccd85a02 Added some mssing type constants to python type stubs generator. 2024-11-28 09:42:22 +03:00
Alexander Smorkalov
85a844e9c2 Merge pull request #26540 from asmorkalov:5.0-alpha-pre
pre: OpenCV 5.0.0-alpha (version++).
2024-11-28 08:16:48 +03:00
Alexander Smorkalov
e1ba8f2659 Merge pull request #26527 from asmorkalov:as/gapi_migration
Restore predefined G-API types in Python type stubs generator
2024-11-27 16:01:02 +03:00
Alexander Smorkalov
2ba82c2c88 Restore predefined G-API types in Python type stubs generator 2024-11-27 14:34:33 +03:00
Alexander Smorkalov
ff142b8ef9 pre: OpenCV 5.0.0-alpha (version++). 2024-11-27 12:59:28 +03:00
alexlyulkov
3672a14b42 Merge pull request #26394 from alexlyulkov:al/new-engine-tf-parser
Modified tensorflow parser for the new dnn engine #26394

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-27 09:15:20 +03:00
Alexander Smorkalov
b9914065e8 Merge pull request #26534 from mshabunin:fix-reduce-test-5x
test: fix technical issue with min_element in reduce tests (5.x)
2024-11-27 09:09:11 +03:00
Maksim Shabunin
939aac47a2 test: fix technical issue with min_element in reduce tests 2024-11-26 22:21:16 +03:00
Alexander Smorkalov
d6b674a3de Merge pull request #26531 from mshabunin:fix-usac-vector-access-5x
calib3d: fix vector access in USAC (5.x)
2024-11-26 22:15:50 +03:00
Alexander Smorkalov
37e13f9dcf Merge pull request #26528 from mshabunin:fix-clang-warning-cblas
build: disable clang  warning in clapack 3rdparty
2024-11-26 19:12:00 +03:00
Maksim Shabunin
57b31e2d4b calib3d: fix vector access in USAC 2024-11-26 16:19:47 +03:00
Maksim Shabunin
997a2bf0bb build: disable clang warning in clapack 3rdparty 2024-11-26 14:59:36 +03:00
Kumataro
f7483cd978 Merge pull request #26508 from Kumataro:fix26507
Support CV_32U, CV_64U and CV_64S for TIFF #26508

Close https://github.com/opencv/opencv/issues/26507

Note: Predictor 2 for 64-bit is only supported after libtiff 4.4.0. But Linux x64 Debug uses libtiff 4.1.0 (releases at 2019/11/3). I append fallback fix to NONE. I hope It works well.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-25 11:04:54 +03:00
Alexander Smorkalov
6e229bda2b Merge pull request #26503 from asmorkalov:as/fix_lstm_tmp
Fixed test LSTM warning.
2024-11-22 10:43:06 +03:00
Alexander Smorkalov
83a1621527 Fixed test LSTM warning. 2024-11-22 09:10:25 +03:00
Alexander Smorkalov
ae0a06c206 Merge pull request #26474 from vpisarev:detect_default_python3_on_mac
detect Python libs inside Xcode.app properly
2024-11-22 08:56:57 +03:00
Alexander Alekhin
7808d50412 Merge branch 4.x 2024-11-22 02:32:17 +00:00
Alexander Alekhin
5a3e18973b Merge pull request #26473 from opencv-pushbot:gitee/alalek/update_ffmpeg_5.x
ffmpeg/5.x: update FFmpeg wrapper 2024.11
2024-11-21 19:30:20 +03:00
Alexander Alekhin
f85a51ed18 ffmpeg/5.x: update FFmpeg wrapper 2024.11
- FFmpeg n7.1
- OpenH264 2.5.0
- libvpx 1.15.0
- aom 3.11.0
2024-11-21 14:45:33 +00:00
Alexander Alekhin
d39810d5c5 videoio(test): re-enable FFmpeg tests on WIN32
- related PR25874
2024-11-21 14:41:18 +00:00
Alexander Alekhin
5fe6b9c8f8 5.x: don't use videoio plugins for 4.x 2024-11-21 14:41:18 +00:00
Alexander Alekhin
ce7c0f0e65 videoio: support properties in ffmpeg plugins 2024-11-21 14:41:18 +00:00
Abduragim Shtanchaev
d0820dac38 Merge pull request #26391 from Abdurrahheem:ash/lstm-new-graph-engine-latest
LSTM layer for new graph engine. #26391

Merge with extra: https://github.com/opencv/opencv_extra/pull/1218

This PR updates/creates LSTM layer compatible with new graph engine. It is based on previous LSTM implementation with some modification on how initializers blobs are processed.

Note: Following tests are currently are disabled 


Two following two tests are disbled since ONNNRuntime does not support `layout=1` attiribute inference. See a detailed issue #26456 on this.
- `LSTM_layout_seq` 
- `LSTM_layout_batch`

Following test fails with the new engine as it is not able to deal with shapes of the form [?, C, H, W]
- `LSTM_Activations`

Works:
- [x] One directional case any batch type 
 - [x] Fix directional case when batch size large than 1
 - [x] Add peepholes attribute

TODO with the next PRs:
 - [ ] Activation support

Note: 
  

> Currently `LSTM_layout_seq`, `LSTM_layout_batch` are disabled as the tests are incorrect. They do not comply with the ONNX standard. Particularly test outputs are of incorrect dimensionality. They produce 3-dimentinal output instead of 4-dimentional. 

------

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-20 14:12:58 +03:00
Vadim Pisarevsky
2ed6d0f590 Merge pull request #26469 from vpisarev:move_gapi_to_contrib_part1
Removed g-api from the main repo #26469

Following #25000.
CI patch: https://github.com/opencv/ci-gha-workflow/pull/196

This is migration of G-API from opencv to opencv_contrib, part 1.
Here we simply remove G-API from the main repo. The next patch should bring G-API to opencv_contrib.

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-11-19 10:29:24 +03:00
Yuantao Feng
ea0f9336e2 Merge pull request #26454 from fengyuentau/imgproc:update_warp_c4_kernels
imgproc: fix perf regressions on the c4 kernels of warpAffine / warpPerspective / remap #26454

## Performance

Previous performance regressions on c4 kernels are mainly on A311D https://github.com/opencv/opencv/pull/26348.
Regressions on c3 kernels on intel platform will be fixed in another pull request.

M2

```
Geometric mean (ms)

                                      Name of Test                                        base  patch   patch
                                                                                                          vs
                                                                                                         base
                                                                                                      (x-factor)
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)               0.338 0.163    2.08
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)               0.310 0.107    2.90
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)              0.344 0.162    2.13
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)              0.313 0.111    2.83
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)              0.676 0.333    2.03
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)              0.640 0.240    2.66
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)             1.212 0.885    1.37
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)             1.153 0.756    1.53
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)             0.950 0.475    2.00
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)             1.158 0.500    2.32
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)            3.441 3.106    1.11
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)            3.351 2.837    1.18
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)     0.336 0.163    2.07
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)     0.314 0.124    2.54
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)    0.385 0.226    1.70
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)    0.364 0.183    1.99
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)    0.541 0.290    1.87
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)    0.523 0.243    2.16
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)   1.540 1.239    1.24
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)   1.504 1.134    1.33
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)   0.751 0.465    1.62
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)   0.958 0.507    1.89
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)  3.785 3.487    1.09
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)  3.602 3.280    1.10
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.331 0.153    2.16
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.304 0.128    2.37
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.329 0.156    2.11
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.306 0.121    2.53
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  2.046 0.930    2.20
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  2.122 1.391    1.53
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 2.035 0.954    2.13
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 2.127 1.410    1.51
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.329 0.157    2.09
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.306 0.124    2.47
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.327 0.158    2.08
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.308 0.127    2.43
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  2.039 0.948    2.15
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  2.175 1.373    1.58
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 2.065 0.956    2.16
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 2.158 1.372    1.57
```

Intel i7-12700K:

```
Geometric mean (ms)

                                      Name of Test                                        base  patch   patch   
                                                                                                          vs    
                                                                                                         base   
                                                                                                      (x-factor)
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)               0.140 0.051    2.77   
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)               0.140 0.054    2.57   
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)              0.140 0.050    2.78   
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)              0.143 0.054    2.64   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)              0.297 0.118    2.51   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)              0.296 0.130    2.28   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)             0.481 0.304    1.58   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)             0.470 0.309    1.52   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)             0.381 0.184    2.07   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)             0.811 0.781    1.04   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)            1.297 1.063    1.22   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)            1.275 1.171    1.09   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)     0.135 0.057    2.36   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)     0.134 0.062    2.16   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)    0.155 0.076    2.04   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)    0.150 0.079    1.90   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)    0.229 0.114    2.02   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)    0.227 0.120    1.89   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)   0.560 0.444    1.26   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)   0.529 0.442    1.20   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)   0.326 0.192    1.70   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)   0.805 0.762    1.06   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)  1.395 1.255    1.11   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)  1.381 1.306    1.06   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.138 0.049    2.81   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.134 0.053    2.53   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.137 0.049    2.79   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.134 0.053    2.51   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  1.362 1.352    1.01   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  3.124 3.038    1.03   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 1.354 1.351    1.00   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 3.142 3.049    1.03   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.140 0.052    2.70   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.136 0.056    2.43   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.139 0.051    2.70   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.135 0.056    2.41   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  1.335 1.345    0.99   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  3.117 3.024    1.03   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 1.327 1.319    1.01   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 3.126 3.026    1.03   
```

A311D

```
Geometric mean (ms)

                                      Name of Test                                         base  patch    patch
                                                                                                            vs
                                                                                                           base
                                                                                                        (x-factor)
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)               1.762  1.361     1.29
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)               2.390  2.005     1.19
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)              1.747  1.238     1.41
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)              2.399  2.016     1.19
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)              3.917  3.104     1.26
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)              5.995  5.172     1.16
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)             6.711  5.460     1.23
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)             8.017  6.890     1.16
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)             6.269  5.596     1.12
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)             10.301 9.507     1.08
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)            18.871 17.375    1.09
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)            20.365 18.227    1.12
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)     2.083  1.514     1.38
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)     2.966  2.309     1.28
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)    2.358  1.715     1.37
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)    3.220  2.464     1.31
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)    3.763  3.014     1.25
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)    5.777  4.940     1.17
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)   8.791  7.819     1.12
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)   10.165 8.426     1.21
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)   6.047  5.293     1.14
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)   9.851  9.023     1.09
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)  31.739 29.323    1.08
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)  32.439 29.236    1.11
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    1.759  1.441     1.22
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    2.681  2.270     1.18
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   1.774  1.425     1.24
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   2.672  2.252     1.19
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  14.079 9.334     1.51
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  17.770 16.155    1.10
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 15.872 11.192    1.42
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 19.167 15.342    1.25
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    2.284  1.545     1.48
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    3.040  2.231     1.36
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   2.280  1.380     1.65
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   2.882  2.185     1.32
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  15.877 11.381    1.40
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  19.521 16.106    1.21
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 15.950 11.532    1.38
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 19.699 16.276    1.21
```

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-19 09:43:59 +03:00
Alexander Smorkalov
8b84fcb376 Merge pull request #26484 from gursimarsingh:text_detection_fixed
Fixed sha1 issues with East model in Text Detection Sample
2024-11-19 09:07:30 +03:00
Alexander Smorkalov
db1aa3c8a9 Merge pull request #26485 from gursimarsingh:fixed_edge_detection_and_segmentation_sample
Added cap.isOpened() check to edge detection and segmentation sample
2024-11-19 09:05:25 +03:00
Gursimar Singh
1d420dc9c0 Added camera open check 2024-11-18 20:07:27 +05:30
Gursimar Singh
b89c041227 fixed sha1 issues with East model 2024-11-18 20:02:13 +05:30
Alexander Smorkalov
0d7d045a3b Merge pull request #26466 from vrabaud:5.x_calibration_fix
Fix minor bugs in calibration.
2024-11-18 10:49:30 +03:00
Vadim Pisarevsky
206a30bce9 detect Python libs inside Xcode.app properly 2024-11-16 13:50:07 +03:00
Vincent Rabaud
d46280507e Fix minor bugs in calibration.
- the asserts are contradictory with the asserts below
- fix when rvecs/tvecs are requested
2024-11-15 09:35:08 +01:00
Alexander Smorkalov
cd5dbf9389 Merge pull request #26455 from sturkmen72:minor_fix
Fix warnings on documentation built
2024-11-14 18:55:19 +03:00
Alexander Smorkalov
77b45145d1 Merge pull request #26458 from asmorkalov:as/drop_c_core
Drop C API in core
2024-11-14 17:27:36 +03:00
Alexander Smorkalov
0310b081f9 Dropped C API in core module. 2024-11-14 08:33:22 +03:00
Suleyman TURKMEN
dc1f7ea5cb Update load_point_cloud.cpp 2024-11-13 15:05:43 +03:00
Alexander Smorkalov
3cc130db5d Merge branch 4.x 2024-11-13 09:02:39 +03:00
Alexander Smorkalov
07d519fe88 Merge pull request #26448 from asmorkalov:as/uwp_ci_5.x
Windows UWP build in CI for 5.x
2024-11-12 14:22:47 +03:00
WU Jia
614e250fd3 Merge pull request #26405 from kaingwade:rename_features2d
Rename features2d #26405

This PR renames the module _features2d_ to _features_ as one of the Big OpenCV Cleanup #25007. 
Related PR: opencv/opencv_contrib: [#3820](https://github.com/opencv/opencv_contrib/pull/3820) opencv/ci-gha-workflow: [#192](https://github.com/opencv/ci-gha-workflow/pull/192)
2024-11-12 11:04:48 +03:00
Alexander Smorkalov
22f7002ed2 Windows UWP build in CI for 5.x 2024-11-12 09:33:08 +03:00
Dmitry Kurtaev
c7a21dc5bf Merge pull request #26444 from dkurt:fix_empty_mat_assert
Fix empty mat debug assertion #26444

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-11 22:54:57 +03:00
Alexander Smorkalov
e83a7fef9f Merge pull request #26283 from mshabunin:cpp-test-3d
C-API cleanup: removed or updated some of 3d and calib tests
2024-11-11 21:44:26 +03:00
Yuantao Feng
c445a000c9 Merge pull request #26348 from fengyuentau:imgproc/remap_opt
imgproc: add new remap kernels that align with the new warpAffine and warpPerspective kernels #26348

## Performance

M2:

```
Geometric mean (ms)

                                      Name of Test                                        base  patch   patch   
                                                                                                          vs    
                                                                                                         base   
                                                                                                      (x-factor)
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                0.213 0.185    1.15   
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)               0.213 0.187    1.14   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)               0.417 0.355    1.18   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)              0.973 0.908    1.07   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)              0.563 0.507    1.11   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)             3.208 3.165    1.01   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)      0.244 0.195    1.26   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)     0.270 0.245    1.10   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)     0.361 0.328    1.10   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)    1.365 1.273    1.07   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)    0.532 0.508    1.05   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)   3.651 3.545    1.03   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                     0.272 0.097    2.80   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                    0.304 0.148    2.06   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                    0.271 0.125    2.16   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                     0.406 0.178    2.28   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                    0.476 0.275    1.73   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                    0.354 0.256    1.38   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                     0.382 0.168    2.28   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.555 0.338    1.64   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.385 0.307    1.25   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                    0.271 0.099    2.75   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                   0.301 0.145    2.07   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                   0.270 0.120    2.24   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                    0.408 0.180    2.27   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                   0.474 0.277    1.71   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                   0.352 0.261    1.35   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                    0.382 0.166    2.29   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.552 0.339    1.63   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.380 0.308    1.24   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                   1.013 0.474    2.14   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                  1.155 0.705    1.64   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                  1.200 0.674    1.78   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                   1.614 0.986    1.64   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                  2.042 1.605    1.27   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                  2.275 1.647    1.38   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                   1.558 0.847    1.84   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  2.394 2.036    1.18   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  2.693 2.112    1.27   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                  0.999 0.463    2.16   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                 1.194 0.699    1.71   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                 1.211 0.677    1.79   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                  1.619 1.045    1.55   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                 2.039 1.604    1.27   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                 2.257 1.657    1.36   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                  1.578 0.845    1.87   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 2.405 2.032    1.18   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 2.669 2.107    1.27   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                     0.277 0.104    2.66   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                    0.310 0.149    2.08   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                    0.275 0.122    2.26   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                     0.412 0.177    2.33   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                    0.479 0.277    1.73   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                    0.360 0.253    1.43   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                     0.388 0.173    2.24   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.575 0.337    1.71   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.387 0.307    1.26   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                    0.274 0.100    2.73   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                   0.312 0.144    2.16   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                   0.278 0.128    2.18   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                    0.407 0.178    2.29   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                   0.483 0.275    1.75   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                   0.358 0.250    1.43   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                    0.389 0.168    2.31   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.563 0.338    1.66   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.390 0.312    1.25   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                   1.024 0.483    2.12   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                  1.224 0.770    1.59   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                  1.185 0.674    1.76   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                   1.633 0.922    1.77   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                  2.042 1.607    1.27   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                  2.244 1.647    1.36   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                   1.592 0.872    1.83   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  2.473 2.014    1.23   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  2.604 2.127    1.22   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                  1.020 0.490    2.08   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                 1.193 0.733    1.63   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                 1.203 0.694    1.73   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                  1.642 0.923    1.78   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                 2.055 1.619    1.27   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                 2.210 1.658    1.33   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                  1.642 0.883    1.86   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 2.463 2.077    1.19   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 2.610 2.152    1.21   
```


Intel i7-12700K:

```
Geometric mean (ms)

                                      Name of Test                                        base  patch   patch   
                                                                                                          vs    
                                                                                                         base   
                                                                                                      (x-factor)
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                0.146 0.055    2.66   
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)               0.146 0.055    2.65   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)               0.301 0.138    2.18   
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)              0.490 0.329    1.49   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)              0.390 0.194    2.01   
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)             1.286 1.190    1.08   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)      0.140 0.058    2.40   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)     0.157 0.078    2.02   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)     0.234 0.117    2.01   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)    0.550 0.472    1.16   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)    0.334 0.199    1.68   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)   1.361 1.347    1.01   

map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                     0.146 0.046    3.18   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                    0.174 0.045    3.88   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                    0.150 0.036    4.21   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                     0.195 0.120    1.63   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                    0.365 0.111    3.29   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                    0.217 0.106    2.05   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                     0.177 0.054    3.30   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.451 0.143    3.15   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.276 0.139    1.98   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                    0.142 0.046    3.06   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                   0.182 0.045    4.00   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                   0.154 0.036    4.31   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                    0.196 0.120    1.63   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                   0.364 0.111    3.29   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                   0.221 0.107    2.07   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                    0.177 0.054    3.31   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.488 0.143    3.42   
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.280 0.139    2.01   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                   0.480 0.290    1.66   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                  0.698 0.288    2.43   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                  0.613 0.322    1.90   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                   0.665 0.808    0.82   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                  1.522 0.942    1.62   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                  2.504 2.204    1.14   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                   0.619 0.376    1.64   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  2.018 1.397    1.44   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  3.582 3.157    1.13   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                  0.481 0.293    1.64   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                 0.698 0.288    2.42   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                 0.606 0.321    1.88   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                  0.669 0.806    0.83   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                 1.514 0.935    1.62   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                 2.472 2.203    1.12   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                  0.618 0.378    1.63   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 1.998 1.404    1.42   
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 3.583 3.160    1.13   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                     0.153 0.050    3.08   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                    0.189 0.048    3.90   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                    0.162 0.041    3.91   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                     0.211 0.124    1.70   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                    0.384 0.113    3.39   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                    0.221 0.107    2.07   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                     0.186 0.059    3.17   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    0.465 0.147    3.16   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    0.312 0.140    2.22   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                    0.148 0.052    2.88   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                   0.189 0.049    3.82   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                   0.167 0.041    4.06   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                    0.202 0.124    1.63   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                   0.383 0.113    3.39   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                   0.228 0.106    2.14   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                    0.188 0.058    3.26   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   0.467 0.147    3.17   
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   0.286 0.140    2.05   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                   0.519 0.311    1.67   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                  0.743 0.307    2.42   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                  0.646 0.329    1.96   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                   0.714 0.826    0.86   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                  1.567 0.939    1.67   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                  2.501 2.183    1.15   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                   0.670 0.389    1.72   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  2.060 1.384    1.49   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  3.556 3.151    1.13   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                  0.517 0.312    1.66   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                 0.745 0.306    2.44   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                 0.651 0.332    1.96   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                  0.731 0.831    0.88   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                 1.574 0.934    1.68   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                 2.442 2.181    1.12   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                  0.666 0.390    1.71   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 2.045 1.391    1.47   
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 3.557 3.154    1.13   
```

A311D:

```
Geometric mean (ms)

                                      Name of Test                                         base  patch    patch
                                                                                                            vs
                                                                                                           base
                                                                                                        (x-factor)
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                1.335  0.936     1.43
WarpAffine::TestWarpAffine::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)               1.331  0.940     1.42
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)               2.950  2.199     1.34
WarpAffine::TestWarpAffine::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)              6.011  5.177     1.16
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)              4.415  3.533     1.25
WarpAffine::TestWarpAffine::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)             26.619 17.665    1.51
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)      1.465  1.119     1.31
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)     1.776  1.416     1.25
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)     4.106  2.307     1.78
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)    12.015 7.427     1.62
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)    7.196  4.044     1.78
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)   32.182 29.642    1.09

map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                     2.358  0.751     3.14
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                    3.342  0.847     3.94
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                    2.863  0.941     3.04
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                     4.062  1.474     2.75
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                    4.937  1.681     2.94
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                    3.796  2.152     1.76
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                     3.838  1.341     2.86
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    5.682  2.288     2.48
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    3.943  3.154     1.25
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                    2.346  0.754     3.11
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                   3.370  0.849     3.97
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                   2.841  0.934     3.04
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                    4.244  1.466     2.90
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                   4.882  1.680     2.91
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                   3.672  2.163     1.70
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                    3.822  1.349     2.83
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   5.614  2.291     2.45
map1_32fc1::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   3.987  3.174     1.26
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                   10.358 4.713     2.20
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                  14.165 4.903     2.89
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                  11.751 5.648     2.08
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                   13.912 6.793     2.05
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                  22.706 8.440     2.69
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                  16.738 13.517    1.24
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                   18.715 9.065     2.06
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  28.190 15.483    1.82
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  17.441 20.976    0.83
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                  10.506 4.770     2.20
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                 14.298 4.952     2.89
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                 11.534 5.669     2.03
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                  19.890 9.588     2.07
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                 23.599 11.543    2.04
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                 16.827 14.255    1.18
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                  18.878 9.185     2.06
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 28.377 15.766    1.80
map1_32fc1::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 17.337 21.134    0.82
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                     2.170  0.763     2.84
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                    3.035  0.959     3.17
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                    2.759  0.937     2.94
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                     4.074  1.484     2.74
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                    4.757  1.689     2.82
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                    3.766  2.165     1.74
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                     3.730  1.353     2.76
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                    5.623  2.301     2.44
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                    3.935  3.115     1.26
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                    2.236  0.761     2.94
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                   3.010  0.946     3.18
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                   2.750  0.933     2.95
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                    4.045  1.484     2.73
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                   4.785  1.694     2.83
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                   3.642  2.146     1.70
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                    3.710  1.357     2.73
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                   5.594  2.310     2.42
map1_32fc2::TestRemap::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                   3.845  3.120     1.23
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)                   10.092 4.846     2.08
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)                  14.501 5.724     2.53
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)                  11.698 5.709     2.05
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)                   19.480 9.290     2.10
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)                  23.830 11.636    2.05
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)                  16.725 13.922    1.20
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)                   18.756 8.839     2.12
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)                  29.698 15.668    1.90
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)                  17.641 20.145    0.88
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)                  10.128 4.883     2.07
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)                 14.438 5.685     2.54
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)                 11.440 5.674     2.02
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)                  19.681 10.117    1.95
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)                 23.757 11.623    2.04
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)                 16.891 13.690    1.23
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)                  18.887 8.756     2.16
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)                 29.654 15.890    1.87
map1_32fc2::TestRemap::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)                 17.412 20.535    0.85
```

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-11 21:44:01 +03:00
Alexander Smorkalov
a4ab68f9f4 Merge pull request #26443 from mshabunin:cleanup-core-test
C-API cleanup: core module tests
2024-11-11 20:51:31 +03:00
Maksim Shabunin
2d9c0c8592 C-API cleanup: core module tests 2024-11-11 14:53:09 +03:00
Gursimar Singh
979428d590 Merge pull request #26334 from gursimarsingh:dnn_engine_change
Modify DNN Samples to use ENGINE_CLASSIC for Non-Default Back-end or Target #26334

PR resolves #26325 regarding fall-back to ENGINE_CLASSIC if non-default back-end or target is passed by user.
### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-08 08:58:35 +03:00
Gursimar Singh
1ae304bb83 Merge pull request #26347 from gursimarsingh:updated_dnn_samples
Updated segmentation sample as per current update usage and engine #26347

This PR updates segmentation sample as per new usage, and change their DNN engines. It adds usage of findModel, dynamic fontsize, etc. in segmentation sample.

The PR makes the sample consistent with other dnn samples

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-08 08:55:46 +03:00
Dmitry Kurtaev
a7bb17b092 Merge pull request #26399 from dkurt:dk/file_storage_new_data
int64 data type in FileStorage #26399

### Pull Request Readiness Checklist

resolves #23333

Proposed approach is not perfect in terms of complexity and potential bugs. Instead of changing `INT` raw size from `4` to `8`, we check int64 value can be fitted to int32 or not.

Collections such as cv::Mat rely on data type symbol.

This PR is addressed to 5.x branch first to cover `CV_64S` Mat. Later, it can be backported to 4.x

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-08 08:27:59 +03:00
Kumataro
3fac9a9d69 Merge pull request #26412 from Kumataro:fix26411
doc: update to doxygen-awesome-css v2.3.4 #26412

Close https://github.com/opencv/opencv/issues/26411

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [X] The PR is proposed to the proper branch
- [X] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-11-06 09:50:45 +03:00
Alexander Smorkalov
03983549fc Merge branch 4.x 2024-11-06 08:20:12 +03:00
Dmitry Kurtaev
286f7524bb Merge pull request #26420 from dkurt:fs_mat_0d_1d
Support 0d/1d Mat in FileStorage #26420

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-06 08:11:59 +03:00
Alexander Smorkalov
ef0d83643d Merge pull request #26418 from mshabunin:cleanup-waitkey-5
highgui: drop legacy waitkey behavior
2024-11-05 21:27:30 +03:00
Maksim Shabunin
25b67bc99e highgui: drop legacy waitkey behavior 2024-11-05 15:01:53 +03:00
Alexander Smorkalov
55105719dd Merge pull request #26396 from hanliutong:rvv-fp16-m2
Use LMUL=2 in the RISC-V Vector (RVV) FP16 part. (5.x)
2024-11-02 13:30:31 +03:00
Vadim Pisarevsky
853fa9dd40 Merge pull request #26400 from vpisarev:fix_fp16_cmp
Fixed FP16 mat comparison in tests #26400

make sure that if both compared FP16/BF16 values are bitwise-equal, assume their difference to be 0 (zero), just like in the case of FP32 and FP64, don't try to compare them as floating-point numbers, because they can be NaN's.

**fixes** #24894

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-02 12:07:48 +03:00
Alexander Smorkalov
7a5f12c630 Merge pull request #26397 from FantasqueX:remove-useless-cmake-policy
Remove useless cmake policy after upgrading cmake_minimum_required
2024-11-02 10:02:39 +03:00
Vadim Pisarevsky
df06d2eac2 Merge pull request #26254 from vpisarev:extra_tests_for_reshape
Added extra tests for reshape #26254

Attempt to reproduce problems described in #25174. No success; everything works as expected. Probably, the function has been used improperly. Slightly modified the code of Mat::reshape() to provide better diagnostic.

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-11-01 11:37:56 +03:00
Letu Ren
65a606966b Remove useless cmake policy after upgrading cmake_minimum_required 2024-11-01 16:16:37 +08:00
Liutong HAN
a59a66a2c7 Use LMUL=2 in the RISC-V Vector (RVV) FP16 part. 2024-11-01 07:05:25 +00:00
Alexander Smorkalov
a95658f106 Merge pull request #26383 from mshabunin:fix-samples-cpp-17
build: raise min cmake version to 3.13 in other places
2024-10-31 09:34:28 +03:00
Alexander Smorkalov
6a8300c1a0 Merge pull request #26385 from vpisarev:fix_bfloat_test
fixed typo in bfloat<=>float conversion test
2024-10-30 16:01:46 +03:00
Maksim Shabunin
e44e3ab0a7 build: raise min cmake version to 3.13 in other places 2024-10-30 14:39:04 +03:00
Vadim Pisarevsky
299aa14c4b fixed typo in bfloat<=>float conversion test 2024-10-29 20:06:11 +03:00
WU Jia
66a29b422c Merge pull request #25708 from kaingwade:flann2annoy
Add interface to Annoy which will replace the FLANN #25708

This PR is to add interface to [Annoy](https://github.com/spotify/annoy) which will replace the FLANN, part of one of the cleanup work of OpenCV 5.0: #24998. 

After it, there will be consecutive patches:

- [ ] Add Annoy based DescriptorMatcher
- [ ] Replace FLANN based code with Annoy and remove FLANN completely

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-10-28 17:04:02 +03:00
alexlyulkov
a2fa1d49a4 Merge pull request #26208 from alexlyulkov:al/new-engine-caffe-parser
Modified Caffe parser to support the new dnn engine #26208

Now the Caffe parser supports both the old and the new engine. It can be selected using newEngine argument in PopulateNet.

All cpu Caffe tests work fine except:

- Test_Caffe_nets.Colorization
- Test_Caffe_layers.FasterRCNN_Proposal

Both these tests doesn't work because of the bug in the new net.forward function. The function takes the name of the desired target last layer, but uses this name as the name of the desired output tensor.
Also Colorization test contains a strange model with a Silence layer in the end, so it doesn't have outputs. The old parser just ignored it. I think, the proper solution is to run this model until the (number_of_layers - 2) layer using proper net.forward arguments in the test.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-28 11:32:07 +03:00
Gursimar Singh
7b0a082dd4 Merge pull request #26326 from gursimarsingh:object_detection_fixed
[BUG FIX] Object detection sample preprocessing #26326

PR resloves #26315 related to incorrect preprocessing for 'Image2BlobParams' in object detection sample.
### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-28 11:25:45 +03:00
Gursimar Singh
f217656916 Merge pull request #25349 from gursimarsingh:videocapture_samples_cpp
combined videocapture and videowriter samples  for cleanup
2024-10-28 09:57:54 +03:00
Gursimar Singh
331d327760 Merge pull request #26336 from gursimarsingh:person_reid_bug_fix
[BUG FIX] Fix issues in Person ReID C++ sample #26336

This PR fixes multiple issues in the Person ReID C++ sample that were causing incorrect outputs. It addresses improper matrix initialization, adds a missing return statement, and ensures that vectors are properly cleared before reuse. These changes correct the output of the sample.
### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-28 09:49:33 +03:00
Kumataro
3b01a4d4e9 Merge pull request #26373 from Kumataro:fix26372
doc: fix doxygen errors at Algorithm and QRCodeEncoder #26373

Close https://github.com/opencv/opencv/issues/26372

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-10-28 09:20:04 +03:00
Alexander Smorkalov
8a5ec4bf7b Merge pull request #26287 from mshabunin:cpp-17
build: transition to C++17, minor changes in documentation
2024-10-26 19:59:48 +03:00
Wanli
29e712ed93 Merge pull request #26369 from WanliZhong:5x_fix_hfloat_vfunc
Fix hfloat conflicts of v_func in merging 4.x to 5.x #26369

This PR solves the conflicts in merging 4.x to 5.x https://github.com/opencv/opencv/pull/26358
1. Explicitly convert the inputs number for `v_setall_` to hfloat number
2. Loosens the threshold for `v_sincos` test. (related issue: https://github.com/opencv/opencv/issues/26362)
3. Remove the new but temp api `template <> inline v_float16x8 v_setall_(float v) { return v_setall_f16((hfloat)v); }`

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-10-26 19:54:13 +03:00
Alexander Smorkalov
05e7988e9c Merge pull request #26367 from alexlyulkovЖal/forward-to-layer-assert
Added exception when calling forward to specified layer with the new dnn engine
2024-10-25 15:22:09 +03:00
Maksim Shabunin
d223e796f5 build: transition to C++17, minor changes in documentation 2024-10-25 15:05:14 +03:00
Alexander Lyulkov
3a4c88c33e Added exception when calling forward to specified layer with the new dnn engine 2024-10-25 13:00:15 +03:00
Alexander Smorkalov
8e55659afe Merge branch 4.x 2024-10-24 15:10:43 +03:00
Alexander Smorkalov
9f0c3f5b2b Merge pull request #26327 from asmorkalov:as/drop_convertFp16
Finally dropped convertFp16 function in favor of cv::Mat::convertTo() #26327 

Partially address https://github.com/opencv/opencv/issues/24909
Related PR to contrib: https://github.com/opencv/opencv_contrib/pull/3812

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-10-22 15:17:24 +03:00
alexlyulkov
a40ceff215 Merge pull request #26330 from alexlyulkov:al/new-engine-tflite-parser2
Modified TFLite parser for the new dnn engine #26330

The new dnn graph is creating just by defining input and output names of each layer.
Some TFLite layers has fused activation, which doesn't have layer name and input and output names. Also some layers require additional preprocessing layers (e.g. NHWC -> NCHW). All these layers should be added to the graph with some unique layer and input and output names. 

I solve this problem by adding additionalPreLayer and additionalPostLayer layers.

If a layer has a fused activation, I add additionalPostLayer and change input and output names this way:
**original**: conv_relu(conv123, conv123_input, conv123_output)
**new**: conv(conv123, conv123_input, conv123_output_additional_post_layer) + relu(conv123_relu,  conv1_output_additional_post_layer, conv123_output)

If a layer has additional preprocessing layer, I change input and output names this way:
**original**: permute_reshape(reshape345, reshape345_input, reshape345_output)
**new**: permute(reshape345_permute, reshape345_input, reshape345_input_additional_pre_layer) + reshape(reshape345, reshape345_input_additional_pre_layer, reshape345_output)


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-22 09:05:58 +03:00
Alexander Smorkalov
6648482b69 Merge pull request #26324 from asmorkalov:as/model_diagnostics_engine
Added DNN engine selector to model diagnostics tool.
2024-10-21 15:51:53 +03:00
Vadim Pisarevsky
6e3c5db1c6 Merge pull request #26333 from vpisarev:fix_26322
Fix #26322: construction of another Mat header for empty matrix #26333

The PR fixes #26322

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-18 14:50:27 +03:00
Vadim Pisarevsky
2f35847960 Merge pull request #26321 from vpisarev:better_bfloat
2x more accurate float => bfloat conversion #26321

There is a magic trick to make float => bfloat conversion more accurate (_original reference needed, is it done this way in PyTorch?_). In simplified form it looks like:

```
uint16_t f2bf(float x) {
    union {
        unsigned u;
        float f;
    } u;
    u.f = x;
    // return (uint16_t)(u.u >> 16); <== the old method before this patch
    return (uint16_t)((u.u + 0x8000) >> 16);
} 
```

it works correctly for almost all valid floating-point values, positive, zero or negative, and even for some extreme cases, like `+/-inf`, `nan` etc. The addition of `0x8000` to integer representation of 32-bit float before retrieving the highest 16 bits reduces the rounding error by ~2x.

The slight problem with this improved method is that the numbers very close to or equal to `+/-FLT_MAX` are mistakenly converted to `+/-inf`, respectively.

This patch implements improved algorithm for `float => bfloat` conversion in scalar and vector form; it fixes the above-mentioned problem using some extra bit magic, i.e. 0x8000 is not added to very big (by absolute value) numbers:

```
// the actual implementation is more efficient,
// without conditions or floating-point operations, see the source code
return (uint16_t)(u.u + (fabsf(x) <= big_threshold ? 0x8000 : 0)) >> 16);
```

The corresponding test has been added as well and this is output from the test:

```
[----------] 1 test from Core_BFloat
[ RUN      ] Core_BFloat.convert
maxerr0 = 0.00774842, mean0 = 0.00190643, stddev0 = 0.00186063
maxerr1 = 0.00389057, mean1 = 0.000952614, stddev1 = 0.000931268
[       OK ] Core_BFloat.convert (7 ms)
```

Here `maxerr0, mean0, stddev0` are for the original method and `maxerr1, mean1, stddev1` are for the new method. As you can see, there is a significant improvement in accuracy.

**Note:**

_Actually, on ~32,000,000 random FP32 numbers with uniformly distributed sign, exponent and mantissa the new method is always at least as accurate as the old one._

The test also checks all the corner cases, where we see no degradation either vs the original method.

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-18 14:46:40 +03:00
Alexander Smorkalov
9773694527 Added DNN engine selector to model diagnostics tool. 2024-10-17 15:09:13 +03:00
Gursimar Singh
1696819abb Merge pull request #25667 from gursimarsingh:improved_person_reid_python
Improved person reid cpp and python sample #25667

#25006 

This sample has been rewritten to track a selected target in a video or camera stream. Person detection has been integrated using yolov8 and the user can provide a target image via command line or interactively select the target at start of the execution


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-17 10:46:53 +03:00
Vadim Pisarevsky
3cd57ea09e Merge pull request #26056 from vpisarev:new_dnn_engine
New dnn engine #26056

This is the 1st PR with the new engine; CI is green and PR is ready to be merged, I think.
Merge together with https://github.com/opencv/opencv_contrib/pull/3794

---

**Known limitations:**
* [solved] OpenVINO is temporarily disabled, but is probably easy to restore (it's not a deal breaker to merge this PR, I guess)
* The new engine does not support any backends nor any targets except for the default CPU implementation. But it's possible to choose the old engine when loading a model, then all the functionality is available.
* [Caffe patch is here: #26208] The new engine only supports ONNX. When a model is constructed manually or is loaded from a file of different format (.tf, .tflite, .caffe, .darknet), the old engine is used.
* Even in the case of ONNX some layers are not supported by the new engine, such as all quantized layers (including DequantizeLinear, QuantizeLinear, QLinearConv etc.), LSTM, GRU, .... It's planned, of course, to have full support for ONNX by OpenCV 5.0 gold release. When a loaded model contains unsupported layers, we switch to the old engine automatically  (at ONNX parsing time, not at `forward()` time).
* Some layers , e.g. Expat, are only partially supported by the new engine. In the case of unsupported flavours it switches to the old engine automatically (at ONNX parsing time, not at `forward()` time).
* 'Concat' graph optimization is disabled. The optimization eliminates Concat layer and instead makes the layers that generate tensors to be concatenated to write the outputs to the final destination. Of course, it's only possible when `axis=0` or `axis=N=1`. The optimization is not compatible with dynamic shapes since we need to know in advance where to store the tensors. Because some of the layer implementations have been modified to become more compatible with the new engine, the feature appears to be broken even when the old engine is used.
* Some `dnn::Net` API is not available with the new engine. Also, shape inference may return false if some of the output or intermediate tensors' shapes cannot be inferred without running the model. Probably this can be fixed by a dummy run of the model with zero inputs.
* Some overloads of `dnn::Net::getFLOPs()` and `dnn::Net::getMemoryConsumption()` are not exposed any longer in wrapper generators; but the most useful overloads are exposed (and checked by Java tests).
* [in progress] A few Einsum tests related to empty shapes have been disabled due to crashes in the tests and in Einsum implementations. The code and the tests need to be repaired.
* OpenCL implementation of Deconvolution is disabled. It's very bad and very slow anyway; need to be completely revised.
* Deconvolution3D test is now skipped, because it was only supported by CUDA and OpenVINO backends, both of which are not supported by the new engine.
* Some tests, such as FastNeuralStyle, checked that the in the case of CUDA backend there is no fallback to CPU. Currently all layers in the new engine are processed on CPU, so there are many fallbacks. The checks, therefore, have been temporarily disabled.

---

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-10-16 15:28:19 +03:00
Maksim Shabunin
e2f583a9ee C-API cleanup: removed or updated some of 3d and calib tests 2024-10-15 18:27:23 +03:00
Yuantao Feng
12738deaef Merge pull request #26271 from fengyuentau:imgproc/warpperspective_opt
imgproc: add optimized warpPerspective linear kernels for inputs of type CV_8U/16U/32F+C1/C3/C4

Merge with https://github.com/opencv/opencv_extra/pull/1214

## Performance

### Apple Mac Mini (M2, 16GB memory)

```
Geometric mean (ms)

                                      Name of Test                                        base  patch   patch   
                                                                                                          vs    
                                                                                                         base   
                                                                                                      (x-factor)
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)      0.397 0.119    3.34   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)     0.412 0.155    2.65   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)     0.382 0.134    2.85   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)      0.562 0.201    2.80   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)     0.580 0.279    2.07   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)     0.477 0.269    1.78   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)      0.536 0.221    2.43   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)     0.662 0.328    2.02   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)     0.511 0.325    1.57   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)     0.433 0.171    2.54   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)    0.452 0.204    2.21   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)    0.410 0.180    2.27   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)     0.624 0.243    2.57   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)    0.636 0.331    1.92   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)    0.511 0.315    1.62   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)     0.604 0.281    2.15   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)    0.712 0.393    1.81   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)    0.552 0.368    1.50   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC1)     0.768 0.214    3.58   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC1)    0.743 0.260    2.86   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC1)    0.722 0.235    3.07   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC3)     1.091 0.333    3.28   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC3)    1.035 0.453    2.29   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC3)    0.955 0.442    2.16   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)     1.097 0.364    3.01   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)    1.141 0.547    2.09   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)    1.015 0.591    1.72   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC1)    1.012 1.006    1.01   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC1)   0.996 1.060    0.94   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC1)   0.930 0.993    0.94   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC3)    1.560 1.260    1.24   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC3)   1.374 1.410    0.97   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC3)   1.212 1.292    0.94   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)    1.702 1.354    1.26   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)   1.554 1.522    1.02   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)   1.342 1.435    0.94   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)    1.561 0.364    4.29   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)   1.444 0.406    3.56   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)   1.423 0.394    3.61   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)    2.177 0.533    4.08   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)   2.006 0.689    2.91   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)   1.907 0.688    2.77   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)    2.213 0.581    3.81   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)   2.238 0.810    2.76   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)   2.072 1.055    1.96   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)   2.201 2.908    0.76   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)  2.108 2.951    0.71   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)  1.997 2.840    0.70   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)   3.444 3.293    1.05   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)  2.889 3.417    0.85   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)  2.671 3.354    0.80   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)   3.765 3.767    1.00   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)  3.247 3.962    0.82   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)  2.993 3.669    0.82   
```

### Desktop (i7-12700K, 64GB memory)

```
Geometric mean (ms)

                                      Name of Test                                        base  patch   patch   
                                                                                                          vs    
                                                                                                         base   
                                                                                                      (x-factor)
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)      0.274 0.076    3.62   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)     0.299 0.058    5.14   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)     0.299 0.043    6.90   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)      0.330 0.115    2.87   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)     0.480 0.109    4.39   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)     0.608 0.180    3.37   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)      0.317 0.143    2.21   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)     0.704 0.139    5.07   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)     0.508 0.141    3.60   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)     0.293 0.064    4.57   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)    0.311 0.061    5.07   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)    0.299 0.057    5.29   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)     0.373 0.135    2.75   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)    0.501 0.129    3.87   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)    0.403 0.123    3.26   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)     0.372 0.163    2.28   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)    0.582 0.161    3.63   
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)    0.459 0.152    3.03   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC1)     0.558 0.099    5.63   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC1)    0.607 0.098    6.20   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC1)    0.599 0.090    6.65   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC3)     0.636 0.198    3.22   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC3)    0.806 0.187    4.31   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC3)    1.329 0.227    5.85   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)     0.643 0.238    2.70   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)    1.401 0.233    6.02   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)    1.083 0.229    4.72   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC1)    0.682 0.358    1.91   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC1)   0.695 0.350    1.99   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC1)   0.666 0.334    2.00   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC3)    0.895 0.502    1.78   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC3)   1.035 0.492    2.11   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC3)   0.924 0.466    1.98   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)    0.969 0.551    1.76   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)   1.201 0.550    2.18   
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)   0.948 0.544    1.74   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)    1.018 0.174    5.84   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)   0.973 0.173    5.63   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)   1.002 0.164    6.13   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)    1.100 0.297    3.71   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)   1.197 0.278    4.30   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)   3.108 0.296   10.49   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)    1.086 0.340    3.20   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)   2.987 0.336    8.88   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)   2.249 0.835    2.69   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)   1.330 1.007    1.32   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)  1.352 0.974    1.39   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)  1.241 0.933    1.33   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)   1.896 1.287    1.47   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)  2.071 1.288    1.61   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)  1.870 1.211    1.54   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)   2.059 1.362    1.51   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)  2.366 1.395    1.70   
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)  1.859 1.416    1.31   
```

### Khadas VIM3 (A311D, 4xA73+2xA53, no fp16 vector intrinsics support, 4GB memory)

```
Geometric mean (ms)

                                      Name of Test                                         base  patch    patch
                                                                                                            vs
                                                                                                           base
                                                                                                        (x-factor)
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC1)      2.543  0.702     3.62
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC1)     3.175  0.727     4.37
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC1)     2.877  0.777     3.70
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC3)      4.059  1.192     3.41
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC3)     4.689  1.642     2.86
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC3)     4.071  2.064     1.97
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 8UC4)      3.897  1.501     2.60
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 16UC4)     5.485  2.106     2.60
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_CONSTANT, 32FC4)     4.611  2.938     1.57
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC1)     2.717  0.912     2.98
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC1)    3.426  0.885     3.87
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC1)    3.009  0.979     3.07
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC3)     4.409  1.488     2.96
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC3)    5.236  1.901     2.75
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC3)    4.445  2.232     1.99
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 8UC4)     4.400  1.816     2.42
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 16UC4)    6.211  2.390     2.60
WarpPerspective::TestWarpPerspective::(640x480, INTER_LINEAR, BORDER_REPLICATE, 32FC4)    4.779  3.154     1.52
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC1)     5.487  1.599     3.43
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC1)    6.589  1.652     3.99
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC1)    4.916  1.779     2.76
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC3)     7.676  2.465     3.11
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC3)    8.783  3.020     2.91
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC3)    8.468  4.314     1.96
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 8UC4)     7.670  2.944     2.60
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 16UC4)    9.364  3.871     2.42
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_CONSTANT, 32FC4)    9.297  5.770     1.61
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC1)    6.809  5.359     1.27
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC1)   9.010  4.745     1.90
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC1)   8.501  4.712     1.80
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC3)    10.652 7.345     1.45
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC3)   12.319 7.647     1.61
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC3)   10.466 7.849     1.33
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 8UC4)    11.659 8.226     1.42
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 16UC4)   13.157 8.825     1.49
WarpPerspective::TestWarpPerspective::(1280x720, INTER_LINEAR, BORDER_REPLICATE, 32FC4)   11.557 9.869     1.17
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC1)    14.773 3.081     4.79
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC1)   14.971 3.135     4.78
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC1)   14.795 3.321     4.45
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC3)    20.823 4.319     4.82
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC3)   22.128 5.029     4.40
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC3)   22.583 8.036     2.81
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 8UC4)    20.141 5.018     4.01
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 16UC4)   23.505 6.132     3.83
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_CONSTANT, 32FC4)   20.226 10.050    2.01
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC1)   18.904 15.189    1.24
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC1)  22.749 12.979    1.75
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC1)  19.685 12.981    1.52
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC3)   29.636 19.974    1.48
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC3)  36.266 19.563    1.85
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC3)  30.124 19.434    1.55
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 8UC4)   34.290 21.998    1.56
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 16UC4)  41.765 21.705    1.92
WarpPerspective::TestWarpPerspective::(1920x1080, INTER_LINEAR, BORDER_REPLICATE, 32FC4)  27.767 22.838    1.22
```

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-15 11:13:41 +03:00
Alexander Smorkalov
3c627b0a97 Merge pull request #26268 from mshabunin:cpp-array-test
C-API cleanup: rework ArrayTest to use new arrays only
2024-10-14 11:14:10 +03:00
Alexander Smorkalov
58fac15a98 Merge pull request #26301 from vpisarev:ttf3
updated embedded font & stb_truetype renderer
2024-10-14 10:51:08 +03:00
Vadim Pisarevsky
08c6d00d96 1. updated Rubik font:
1) numerals are now monospace, e.g. '1' has the same width as '0',
    2) '0' is different from capital 'o',
    3) new glyphs added
2. stb_truetype upgraded from 1.24 to 1.26 with some fixes in rendering.
2024-10-13 03:25:24 +03:00
Yuantao Feng
5aa45e9053 Merge pull request #26292 from fengyuentau:imgproc/warpaffine_opt_opencl
imgproc: update warpAffine opencl kernel to be in sync with cpu one #26292

Relates https://github.com/opencv/opencv/pull/26242

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-12 11:13:41 +03:00
Alexander Smorkalov
70380a7988 Merge pull request #26285 from vrabaud:5_countnonzero_overflow
Fix sanitizer issue in countNonZero32f
2024-10-10 20:30:40 +03:00
WU Jia
ef98c25d60 Merge pull request #25292 from kaingwade:features2d_parts_to_contrib
Features2d cleanup: Move several feature detectors and descriptors to opencv_contrib #25292

features2d cleanup: #24999

The PR moves KAZE, AKAZE, AgastFeatureDetector, BRISK and BOW to opencv_contrib/xfeatures2d.

Related PR: opencv/opencv_contrib#3709
2024-10-10 17:10:22 +03:00
Vincent Rabaud
16ea1382f7 Fix sanitizer issue in countNonZero32f
In that function, the floats are cast to int to be compared to 0.
But a float can be -0 or +0, hence
define CHECK_NZ_FP(x) ((x)*2 != 0)
to remove the sign bit. Except that can trigger the sanitizer:
runtime error: signed integer overflow: -1082130432 * 2 cannot be represented in type 'int'
Doing everything in uint instead of int is properly defined by the
standard.
2024-10-10 13:35:49 +02:00
Maksim Shabunin
d0e410da93 C-API cleanup: rework ArrayTest to use new arrays only 2024-10-09 22:36:20 +03:00
Alexander Smorkalov
9dbfba0fd8 Merge pull request #26253 from vrabaud:compilation_fix
Fix hash_tsdf_functions.cpp compilation on some platforms.
2024-10-09 08:31:21 +03:00
Alexander Smorkalov
26985f1043 Merge pull request #26255 from vpisarev:test_for_countnonzero_1d
added comprehensive test for countNonZero run on continuous and discontinuous 1D arrays
2024-10-07 17:11:24 +03:00
Alexander Smorkalov
ebc39adbe0 Merge pull request #26267 from mshabunin:fix-long-mv-test
calib: mark some multiview tests verylong
2024-10-07 17:08:27 +03:00
Vadim Pisarevsky
68a81888ec Merge pull request #26256 from vpisarev:expanded_tests_for_norm
extended Norm tests to prove that cv::norm() already supports all the types.

cv::norm() already provides enough functionality; just extended tests to prove it. See #24887

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-07 17:07:59 +03:00
Maksim Shabunin
a97c99e49f calib: mark some multiview tests verylong 2024-10-07 15:37:59 +03:00
Vadim Pisarevsky
254db60667 removed unnecessary check (checked many times in other tests) 2024-10-04 23:57:24 +03:00
Vadim Pisarevsky
56673d969a added comprehensive test for countNonZero run on continuous and dis-continuous 1D arrays 2024-10-04 23:54:01 +03:00
Alexander Smorkalov
ff9820ea5c Merge pull request #26251 from asmorkalov:as/reshape_umat_0d
Relax conditions to allow 0d reshape for UMat.
2024-10-04 20:27:29 +03:00
Vincent Rabaud
79e0763d17 Fix hash_tsdf_functions.cpp compilation on some platforms. 2024-10-04 17:57:17 +02:00
Alexander Smorkalov
91775af2dd Merge pull request #26248 from asmorkalov:as/multiview_split
Multiple calibrateMultiview improvements.
2024-10-04 16:37:15 +03:00
Alexander Smorkalov
b03dd764a1 Relax conditions to allow 0d reshape for UMat. 2024-10-04 16:32:59 +03:00
Alexander Smorkalov
110b701bba Multiple calibrateMultiview improvements.
- Added function overload for the simple case
- Added CV_Bool type support for masks
- `parallel_for_` for intrinsics calibration for faster inference
- Homogenize parameters order with other calibrateXXX functions
2024-10-04 14:07:17 +03:00
Yuantao Feng
97681bdfce Merge pull request #25984 from fengyuentau:imgproc/warpaffine_opt
imgproc: add optimized warpAffine kernels for 8U/16U/32F + C1/C3/C4 inputs #25984

Merge wtih https://github.com/opencv/opencv_extra/pull/1198.
Merge with https://github.com/opencv/opencv_contrib/pull/3787.


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-10-03 14:01:36 +03:00
Alexander Smorkalov
ebf11d36f4 Merge pull request #26231 from asmorkalov:as/multiview_hetero
Heterogenious cameras support in multiview calibration.
2024-10-02 17:49:27 +03:00
Alexander Smorkalov
ae52db549d Heterogenious cameras support in multiview calibration. 2024-10-02 10:33:01 +03:00
Alexander Smorkalov
916fb7df16 Merge pull request #26225 from mshabunin:cpp-imgcodecs
C-API cleanup: removed legacy headers in imgcodecs
2024-10-02 08:14:32 +03:00
Alexander Smorkalov
a669c5cb03 Merge pull request #26229 from mshabunin:cpp-photo
C-API cleanup: inpaint algorithms in photo (5.x)
2024-10-02 08:11:52 +03:00
Alexander Smorkalov
886934dba8 Merge pull request #26227 from mshabunin:cpp-features2d
C-API cleanup: use AutoBuffer in MSER (5.x)
2024-10-02 08:10:35 +03:00
Maksim Shabunin
2688248df7 C-API cleanup: inpaint algorithms in photo 2024-10-01 20:06:14 +03:00
Maksim Shabunin
6f18a10012 C-API cleanup: use AutoBuffer in MSER 2024-10-01 18:42:28 +03:00
Maksim Shabunin
5901170c78 C-API cleanup: removed legacy headers in imgcodecs 2024-10-01 18:34:35 +03:00
Alexander Smorkalov
3bcab8db0a Merge pull request #26221 from asmorkalov:as/refactor_multiview_interface
Reworked multiview calibration interface #26221

- Use InputArray / OutputArray
- Use enum for camera type
- Sort parameters according guidelines
- Made more outputs optional
- Introduce flags and added tests for intrinsics and extrinsics guess.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-10-01 16:53:16 +03:00
Alexander Smorkalov
6c743f8e4b Merge pull request #26213 from asmorkalov:as/register_hetero
registerCameras test for heterogenious pinhone + fisheye setup.
2024-09-30 15:49:34 +03:00
Alexander Smorkalov
6ed4e7acae registerCameras test for heterogenious pinhone + fisheye setup. 2024-09-30 12:38:15 +03:00
Alexander Smorkalov
6dcf6d9dd1 Merge pull request #26188 from asmorkalov:as/multiview_calib_accuracy_test
Multi-camera calibration tests with real cameras.
2024-09-28 09:53:01 +03:00
Alexander Smorkalov
e66d38e15f Merge pull request #26190 from mshabunin:fix-rvv-fp16-support
build: enable RISC-V FP16 support in the toolchain
2024-09-25 22:57:12 +03:00
Alexander Smorkalov
51ace51ea5 Merge pull request #26189 from mshabunin:fix-intrin-ops-5.x
build: fix AVX2/AVX512 builds failed due to intrinsics operator usage (5.x)
2024-09-25 22:56:15 +03:00
Alexander Smorkalov
0fa4b0ead2 Multi-camera calibration tests with real cameras. 2024-09-25 22:54:10 +03:00
Maksim Shabunin
bd26d02908 build: enable RISC-V FP16 support in the toolchain 2024-09-25 20:01:29 +03:00
Maksim Shabunin
4a81b4e51f build: fix AVX2/AVX512 builds failed due to intrinsics operator usage 2024-09-25 19:48:17 +03:00
Gursimar Singh
f9a297e52c Merge pull request #26186 from gursimarsingh:download_models_fixed
Add support for downloading DNN config files in download_models.py #26186

PR resloves #26160 related to downloading DNN config files using download_models.py

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-09-25 10:31:45 +03:00
Alexander Smorkalov
8256ef3321 Merge pull request #26183 from asmorkalov:as/multiview_calib_docs
Multiview calibration pipeline documentation update
2024-09-24 13:43:42 +03:00
Alexander Smorkalov
5c870bd5a2 Merge pull request #26184 from asmorkalov:as/js_merge_fix_5.x
Java Script config fix after 4.x merge.
2024-09-24 13:32:56 +03:00
lpanaf
938dabef0e Multiview calibration pipeline documentation update. 2024-09-24 11:54:25 +03:00
Alexander Smorkalov
4d5beef7db Java Script config fix after 4.x merge. 2024-09-24 11:44:09 +03:00
Alexander Smorkalov
fe1a4b61bc Merge pull request #25022 from asmorkalov:as/calib_multiview_charuco_cpp
Add Charuco board support to multiview calibration sample (C++)
2024-09-24 11:26:39 +03:00
lpanaf
9daad187af Add Charuco board support to multiview calibration sample (C++). 2024-09-24 10:26:27 +03:00
Alexander Smorkalov
317012e85e Merge pull request #26177 from asmorkalov:as/yolo_tutorial_links
Fixed code snippets in Yolo tutorial.
2024-09-23 16:49:24 +03:00
Alexander Smorkalov
cb3af0a08f Merge branch 4.x 2024-09-23 14:18:25 +03:00
Alexander Smorkalov
2529af9719 Fixed code snippets in Yolo tutorial. 2024-09-23 08:32:09 +03:00
Gursimar Singh
e823493af1 Merge pull request #25710 from gursimarsingh:improved_object_detection_sample
Merged yolo_detector and object detection sample #25710

Relates to #25006

This pull request merges the yolo_detector.cpp sample with the object_detector.cpp sample. It also beautifies the bounding box display on the output images

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-09-18 16:19:46 +03:00
Alexander Smorkalov
46b800f506 Merge pull request #26144 from asmorkalov:as/drop_CV_FUNCTION_NAME
Drop remaning C CV_FUNCTION_NAME as it's not used any more.
2024-09-12 16:03:27 +03:00
Alexander Smorkalov
f8a75bccab Drop remaning C CV_FUNCTION_NAME as it's not used any more. 2024-09-12 08:38:19 +03:00
Alexander Smorkalov
b574db2cff Merge branch 4.x 2024-09-10 10:15:22 +03:00
Gursimar Singh
99bc88c259 Merge pull request #25520 from gursimarsingh:add-bigvision-copyright
Add bigvision copyright #25520

This pull request adds Bigvision LLC to the copyright list to recognize our contributions to the project [#25433, #25415, #25304]. This update reflects our ongoing commitment to supporting and maintaining this project. Please let me know if there are any adjustments you would like me to make. Thank you for considering this addition.
2024-09-09 17:44:30 +03:00
Gursimar Singh
073488896e Merge pull request #25326 from gursimarsingh:improved_text_detection_sample
Improved and refactored text detection sample in dnn module #25326

Clean up samples: #25006

This pull requests merges and simplifies different text detection samples in dnn module of opencv in to one file. An option has been provided to choose the detection model from EAST or DB

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-09-09 17:43:15 +03:00
Maksim Shabunin
7bdc618697 Merge pull request #26025 from mshabunin:cpp-videoio-highgui
❗ Potential conflicts with #25958
C-API cleanup: highgui, videoio #26025

❗  Merge with: opencv/opencv_contrib#3780

This PR removes usage of C-API from highgui and videoio modules. Only source code is affected, tests were not using obsolete API.

It should be possible to backport these changes to 4.x branch preserving removed public headers and source files (`*_c.h` and `*_c.cpp`).


#### Checklist

I tried to verify as many backends as possible, though these checks were not as thorough as I'd like them to be. Below is the checklist covering all modified backends with their statuses.

> 🔹 - small changes
> 🟢 - consider working
> ⚪ - considered untested

##### highgui

Pass | Backend | Local check | CI check
-----|---------|-------------|---------
🟢 | GTK2 | build + test, plugin build | build + test ❔ 
🟢 | GTK3 | build + test, plugin build | build + test
🟢 | QT | build + test, plugin build |
⚪ | Wayland 🔹 | |
🟢 | WIN32 🔹 | | build + test
🟢 | Cocoa 🔹 | | build + test
⚪ | WinRT | | 

##### videoio 

Pass | Backend | Local check | CI check
-----|---------|-------------|---------
🟢 | Android Camera/MediaNDK 🔹 | | build
🟢 | Aravis | build |
🟢 | AVFoundation OSX | | build + test
⚪ | AVFoundation iOS | | build
🟢 | DC1394 | build |
🟢 | DShow 🔹 | | build
🟢 | FFMpeg | build, plugin build | build + test
🟢 | GPhoto 🔹 | build |
🟢 | GStreamer | build, plugin build | build + test
🟢 | Images | build | build + test
🟢 | MSMF 🔹 | | build + test
🟢 | OpenNI | build |
🟢 | PVAPI | build |
🟢 | V4L | build + test | build
🟢 | XIMEA | build |
🟢 | XINE 🔹 | build |

#### Notes

- local linux build checks performed using [this framework](https://github.com/mshabunin/opencv-videoio-build-check)
- minor extra changes made in both `cap_avfoundation*.mm` to make them slightly more synchronized - it would be better to combine them into a single one in the future
- configurations with plugins have been build but not tested
- **moved unrelated changes to separate PRs** ~two issues have been fixed in separate commits:~
  - ~imgproc: missing `cv::hal::` color conversion functions has been used in MediaSDK backend~
  - ~videoio/V4L: wrong color conversion mode caused bad colors for NV12 camera input format (RGB instead of BGR)~

It would be nice to check following functionality manually:
- [ ] OSX: camera input
- [ ] iOS: camera and file input
- [ ] WinRT: build, some testing
- [x] Linux/Wayland: build
2024-09-09 16:42:44 +03:00
Yuantao Feng
ce5823c5eb Merge pull request #26124 from fengyuentau:dnn/topk_dtype
dnn(5.x): handle topk data type #26124

Resolves https://github.com/opencv/opencv/issues/26076

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-09-09 15:15:04 +03:00
Abduragim Shtanchaev
8263c804de Merge pull request #26106 from Abdurrahheem:ash/add-gatherND
Support for GatherND layer #26106

This PR adds support for GatherND layer. The layer was in comformance deny list initially.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-09-09 11:37:33 +03:00
Abduragim Shtanchaev
a18d793dbd Merge pull request #26110 from Abdurrahheem:ash/hardmax-backend-fix
Switch off OpenVINO backend for Hardmax #26110

Fix Hardmax Issue with backend mentioned in #26107 

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-09-06 13:14:25 +03:00
Gursimar Singh
f8fb3a7f55 Merge pull request #25515 from gursimarsingh:improved_edge_detection_sample
#25006 #25314 
This pull request removes hed_pretrained caffe model to the SOTA dexined onnx model for edge detection. Usage of conventional methods like canny has also been added

The obsolete cpp and python sample has been removed

TODO:
- [  ]  Remove temporary hack for quantized models. Refer issue https://github.com/opencv/opencv_zoo/issues/273

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-09-06 12:47:04 +03:00
Maksim Shabunin
f73560293f Merge pull request #26101 from mshabunin:cpp-error-ts
C-API cleanup: moved cvErrorStr to new interface, minor ts changes #26101

Merge with opencv/opencv_contrib#3786

**Note:** `toString` might be too generic name (even though it is in `cv::Error::` namespace), another variant is `codeToString` (we have `typeToString` and `depthToString` in check.hpp).

**Note:** _ts_ module seem to have no other C API usage except for `ArrayTest` class which requires refactoring.
2024-09-06 12:05:47 +03:00
Alexander Smorkalov
babc669dba Merge pull request #26119 from mshabunin:fix-rvv-init
RISC-V: remove statically initialized global RVV variables (5.x)
2024-09-06 08:23:17 +03:00
Maksim Shabunin
ea8f091a08 RISC-V: remove statically initialized global RVV variables 2024-09-05 19:49:50 +03:00
Alexander Smorkalov
82da334ff3 Merge pull request #26100 from mshabunin:fix-riscv-build
RISC-V: fix XuanTie and Andes builds
2024-09-03 15:14:55 +03:00
Maksim Shabunin
8b3b19d185 RISC-V: fix XuanTie and Andes builds 2024-09-02 17:14:04 +03:00
Wanli
a735660cc3 Merge pull request #26023 from WanliZhong:vfunc_hfloat
Fix hfloat, float16_t, float collision in 5.x about v_exp and v_log #26023

This PR try to fix https://github.com/opencv/opencv/issues/25922
Because the `hfloat` is defined as explicit conversion, the test code should be modified as it. The `vx_setall_f16` problem has already been fixed.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-09-02 12:37:57 +03:00
Abduragim Shtanchaev
0f8bbf4677 Merge pull request #26079 from Abdurrahheem:ash/hardmax-support
Add Support for Hardmax Layer #26079

This PR add support for `Hardmax` layer, which as previously listed in conformance deny list. 

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-09-02 12:32:55 +03:00
Alexander Smorkalov
8def9f75c8 Merge pull request #26096 from mshabunin:fix-riscv-install
RISC-V: fix installation process
2024-09-02 08:57:25 +03:00
Maksim Shabunin
81ab6a3fbd RISC-V: fix installation process 2024-09-01 20:59:57 +03:00
Alexander Smorkalov
100db1bc0b Merge branch 4.x 2024-08-28 15:06:19 +03:00
Alexander Smorkalov
41097a48ad Merge pull request #25743 from hanliutong:rvv-fp16
Add FP16 support for RISC-V
2024-08-23 15:29:21 +03:00
Abduragim Shtanchaev
050085c996 Merge pull request #25950 from Abdurrahheem:ash/add-inpainting-sample
Diffusion Inpainting Sample #25950

This PR adds inpaiting sample that is based on [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/pdf/2112.10752) paper (reference github [repository](https://github.com/CompVis/latent-diffusion)).


Steps to run the model:

1. Firstly needs ONNX graph of the Latent Diffusion Model. You can get it in two different ways. 

> a. Generate the using this [repo](https://github.com/Abdurrahheem/latent-diffusion/tree/ash/export2onnx) and follow instructions below

```bash
git clone https://github.com/Abdurrahheem/latent-diffusion.git
cd latent-diffusion
conda env create -f environment.yaml
conda activate ldm
wget -O models/ldm/inpainting_big/last.ckpt https://heibox.uni-heidelberg.de/f/4d9ac7ea40c64582b7c9/?dl=1
python -m scripts.inpaint.py --indir data/inpainting_examples/ --outdir outputs/inpainting_results --export=True
```

> b. Download the ONNX graph (there 3 fiels) using this link: TODO make a link

2. Build opencv (preferebly with CUDA support enabled
3. Run the script 

```bash
cd opencv/samples/dnn
python ldm_inpainting.py 
python ldm_inpainting.py -e=<path-to-InpaintEncoder.onnx file> -d=<path-to-InpaintDecoder.onnx file> -df=<path-to-LatenDiffusion.onnx file> -i=<path-to-image>
```
Right after the last command you will be prompted with image. You can click on left mouse bottom and starting selection a region you would like to be inpainted (deleted). Once you finish marking the region, click on left mouse botton again and press esc button on your keyboard. The inpainting proccess will start. 

Note: If you are running it on CPU it might take a large chank of time. Also make sure to have about 15GB of RAM to make process faster (other wise swapping will click in and everything will be slower)
 
Current challenges: 

1. Diffusion process is slow (many layers fallback to CPU with running with CUDA backend) 
2. The diffusion result is does exactly mach that of the original torch pipeline

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x]The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-08-21 14:48:37 +03:00
Alexander Smorkalov
9dcac41c66 Merge pull request #26043 from Abdurrahheem:ash/fix-nll-layer
Support Matrices with axes > 6 CUDA
2024-08-21 11:12:43 +03:00
Alexander Smorkalov
7d31463fea Merge pull request #26048 from alexlyulkov:al/dnn-opencl-int
Added integer and bool support to dnn OpenCL layers
2024-08-21 09:39:59 +03:00
Abduragim Shtanchaev
79a731aff0 Fix for support matrixes with number of axes = 6. 2024-08-21 09:06:46 +03:00
Alexander Smorkalov
eee383fde8 Merge pull request #26050 from asmorkalov:as/supress_qdq_tests
Supress more ONNX conformance test cases for quant-dequant with CUDA.
2024-08-20 17:46:58 +03:00
Alexander Smorkalov
d69db7aac4 Supress more ONNX conformance test cases for quant-dequant with CUDA. 2024-08-20 17:12:26 +03:00
Abduragim Shtanchaev
45fd4d8217 Merge pull request #26026 from Abdurrahheem:ash/python_bool_binding
Add support for boolan input/outputs in python bindings #26026

This PR add support boolean input/output binding in python. The issue what mention in ticket https://github.com/opencv/opencv/issues/26024 and the PR soleves it. Data and models are located in [here](https://github.com/opencv/opencv_extra/pull/1201)

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-08-20 16:38:21 +03:00
Alexander Lyulkov
a69cd7d6ba Added integer and bool support to dnn OpenCL layers 2024-08-20 12:33:08 +03:00
Liutong HAN
f3cc5a9e1e Support fp16 for RISC-V. 2024-08-07 16:52:11 +00:00
Alexander Smorkalov
7e8f2a1bc4 Merge branch 4.x 2024-08-06 15:31:30 +03:00
Gursimar Singh
35eba9ca90 Merge pull request #25519 from gursimarsingh:improved_classification_sample
Improved classification sample #25519

#25006 #25314

This pull requests replaces the caffe model for classification with onnx versions. It also adds resnet in model.yml. 

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-08-06 09:16:11 +03:00
Gursimar Singh
3dcc8c38b4 Merge pull request #25268 from gursimarsingh:samples_cleanup_python
Removed obsolete python samples #25268

Clean Samples #25006 
This PR removes 36 obsolete python samples from the project, as part of an effort to keep the codebase clean and focused on current best practices. Some of these samples will be updated with latest algorithms or will be combined with other existing samples. 

Removed Samples:

> browse.py
camshift.py
coherence.py
color_histogram.py
contours.py
deconvolution.py
dft.py
dis_opt_flow.py
distrans.py
edge.py
feature_homography.py
find_obj.py
fitline.py
gabor_threads.py
hist.py
houghcircles.py
houghlines.py
inpaint.py
kalman.py
kmeans.py
laplace.py
lk_homography.py
lk_track.py
logpolar.py
mosse.py
mser.py
opt_flow.py
plane_ar.py
squares.py
stitching.py
text_skewness_correction.py
texture_flow.py
turing.py
video_threaded.py
video_v4l2.py
watershed.py

These changes aim to improve the repository's clarity and usability by removing examples that are no longer relevant or have been superseded by more up-to-date techniques.
2024-07-31 16:11:00 +03:00
Alexander Smorkalov
f24e80297a Merge pull request #25972 from kaingwade:update_orbbec_tutorial
Update orbbec(uvc) tutorial
2024-07-31 12:42:47 +03:00
kaingwade
ca2d17758f Update orbbec(uvc) tutorial 2024-07-31 15:19:23 +08:00
Vincent Rabaud
ae4c67e3a0 Merge pull request #25945 from vrabaud:02_fix
Fix size() for 0d matrix #25945

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-30 12:44:12 +03:00
Alexander Smorkalov
908c59ae25 Merge pull request #25965 from mshabunin:cpp-imgproc-test-5.x
imgproc: C-API cleanup 5.x
2024-07-29 18:05:05 +03:00
Maksim Shabunin
7d12392a7d imgproc: remove C-API leftovers 2024-07-29 13:23:30 +03:00
Alexander Smorkalov
672a662dff Merge branch 4.x 2024-07-26 09:10:36 +03:00
Alexander Smorkalov
459a9c60ed Merge pull request #25902 from asmorkalov:as/core_mask_cvbool
Mask support with CV_Bool in ts and core #25902

Partially cover https://github.com/opencv/opencv/issues/25895

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-07-24 16:32:25 +03:00
Alexander Smorkalov
8ba70194b1 Merge pull request #25939 from vrabaud:slash_warning
Fix "'/*' within block comment " warning
2024-07-19 14:40:31 +03:00
Vincent Rabaud
b8f5c08306 Fix "'/*' within block comment " warning 2024-07-19 13:03:48 +02:00
Abduragim Shtanchaev
88f05e49be Merge pull request #25868 from Abdurrahheem:ash/add-gpt2-sample
Add sample for GPT2 inference #25868

### Pull Request Readiness Checklist

This PR adds sample for inferencing GPT-2 model. More specificly implementation of GPT-2 from [this repository](https://github.com/karpathy/build-nanogpt). Currently inference in OpenCV is only possible to do with fixed window size due to not supported dynamic shapes. 

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-18 16:47:12 +03:00
Abduragim Shtanchaev
060c24bec9 Merge pull request #25101 from Abdurrahheem:ash/1D-reduce-test
1D test for Reduce layer #25101

This PR introduces test for `Reduce` layer to test its functionality for 1D arrays

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-17 19:19:18 +03:00
Abduragim Shtanchaev
d05047ae41 Merge pull request #25917 from Abdurrahheem:ash/reduce-parser-fix
Fix Reduce layer for cosnt inputs #25917

### Pull Request Readiness Checklist

This PR adds support for const inputs for reducing the layer. Particularly, it fixes the following case. The test model and data are located in [1194](https://github.com/opencv/opencv_extra/pull/1194)

<img width="190" alt="image" src="https://github.com/user-attachments/assets/45a90f0a-b798-4529-bece-24c7bfc9e7ba">


See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-17 19:17:44 +03:00
Alexander Smorkalov
fc9208cff5 Merge branch 4.x 2024-07-17 10:08:16 +03:00
Yuantao Feng
420663498f Merge pull request #25900 from fengyuentau:dnn/nary_elementwise_multi_thread
dnn: merge #25630 to 5.x #25900

Sync changes from https://github.com/opencv/opencv/pull/25630 to 5.x.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-15 08:57:50 +03:00
Gursimar Singh
9aa5f3f1db Merge pull request #25252 from gursimarsingh:cpp_samples_cleanup
Move API focused C++ samples to snippets #25252

Clean Samples #25006
This PR removes 39 outdated C++ samples from the project, as part of an effort to keep the codebase clean and focused on current best practices.
2024-07-11 15:07:21 +03:00
HAN Liutong
1d9ca7160b Merge pull request #25796 from hanliutong:hfloat
Use hfloat instead of __fp16. #25796

Related: #25743

Currently, the type for the half-precision floating point data in the OpenCV source code is `__fp16`, which is a unique(?) type supported by the ARM compiler. Other compilers have very limited support for `__fp16`, so in order to introduce more backends that support FP16 (such as RISC-V), we may need a the more general FP16 type.

In this patch, we use `hfloat` instead of `__fp16` in non-ARM code blocks, mainly affected parts are:
- `core/hal/intrin.hpp`: Type Traits, REG Traits and `vx_` interface.
- `core/hal/intrin_neon.hpp`: Universal Intrinsic API for FP16 type.
- `core/test/test_intrin_utils.hpp`: Usage of Univseral Intrinsic
- `core/include/opencv2/core/cvdef.h`: Definition of class `hfloat`

If I understand correctly, class `hfloat` acts as a wrapper around FP16 types in different platform (`__fp16` for ARM and `_Float16` for RISC-V). Any OpenCV generic interface/source code should use `hfloat`, while platform-specific FP16 types only used in macro-guarded code blocks.

/cc @fengyuentau  @mshabunin 

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [ ] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-07-07 11:38:02 +03:00
Alexander Smorkalov
6a11847d57 Merge pull request #25860 from asmorkalov:as/fix_linux_32bit
Fixed 32-bit build with some GCC versions
2024-07-04 16:05:31 +03:00
WU Jia
bd1f9cd1ed Merge pull request #25410 from kaingwade:add_videocapture_depth_sample
Add videocapture_depth.cpp sample #25410

The PR is to combine the examples `videocapture_openni.cpp`, `videocapture_realsense.cpp` and `videocapture_obsensor.cpp` into `videocapture_depth.cpp`.

Tested cameras and OS using this sample are listed below:

|                        | Windows 10   | Ubuntu 22.04 | Mac M1 14.3   |
|------------------------|--------------|--------------|---------------|
| Orbbec Gemini 2 Series | &#x2713;     | &#x2713;     | &#x2713;      |
| RealSense D435, D455   | &#x2713;     | &#x2713;     | &#x2717;      |
| Kinect, XtionPRO       |  -           | -            | -             |

Note:
- OpenNI based cameras (Kinect, XtionPRO) are not tested as I don't have them.
- RealSense D435 and D455 don't work on Mac with OpenCV.
2024-07-03 17:44:13 +03:00
Alexander Smorkalov
48b457f8c7 Merge pull request #25863 from asmorkalov:as/js_test_fixes_5.x
Fixed failed JavaScript tests in 5.x
2024-07-03 17:03:25 +03:00
Alexander Smorkalov
fc85d2a551 Fixed failed JavaScript tests in 5.x 2024-07-03 16:15:36 +03:00
Alexander Smorkalov
b083d36d68 Fixed 23-bit build with some GCC versions. 2024-07-03 14:13:34 +03:00
Gursimar Singh
96a8e6d76c Merge pull request #25756 from gursimarsingh:bug_fix/segmentation_sample
[BUG FIX] Segmentation sample u2netp model results #25756

PR resloves #25753 related to incorrect output from u2netp model in segmentation sample

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-07-03 14:03:12 +03:00
Alexander Smorkalov
55a2a945b6 Merge pull request #25855 from asmorkalov:as/ci_ubuntu_24.04_5.x
Added Ubuntu 24.04 pipeline for 5.x
2024-07-03 11:49:48 +03:00
Alexander Smorkalov
9772ec861b Added Ubuntu 24.04 pipeline for 5.x 2024-07-03 09:21:54 +03:00
Alexander Smorkalov
fef2c95472 Merge pull request #25848 from asmorkalov:as/ubuntu_2404_warn_fix
Warnings fix for Ubuntu 24.04.
2024-07-02 17:21:53 +03:00
Alexander Smorkalov
b39ca66a5d Merge pull request #25847 from asmorkalov:as/lut_all
Added lut support for all new types in 5.x
2024-07-02 17:21:36 +03:00
Alexander Smorkalov
190eddf8c3 Warnings fix for Ubuntu 24.04. 2024-07-02 15:01:48 +03:00
Alexander Smorkalov
07ec6cb2c2 Added lut support for all new types in 5.x 2024-07-02 14:44:55 +03:00
Alexander Smorkalov
3abd9f2a28 Merge branch 4.x 2024-07-01 15:59:43 +03:00
alexlyulkov
12b8ed1443 Merge pull request #25755 from alexlyulkov:al/more-types
Added more types support to dnn layers #25755

Added support of more types to dnn layers for CPU, CUDA and OpenVINO backends.
Now most of the multi-type layers support uint8, int8, int32, int64, float32, float16, bool types.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-06-28 09:02:15 +03:00
alexlyulkov
fd7cb1be85 Merge pull request #25739 from alexlyulkov:al/openvino2022-fixed-blank
Fixed blank layer for OpenVINO 2022.1 #25739

Changed blank layer because it didn't work with old OpenVINO versions(2022.1). The blank layer was implemented using ConvertLike layer, now it is implemented using ShapeOf and Reshape layers.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-06-27 18:51:35 +03:00
Alexander Smorkalov
719b49ffa9 Merge pull request #25764 from alexlyulkov:al/cumsum-fix
Fixed cumsum layer, enabled conformance tests
2024-06-27 18:50:15 +03:00
Maksim Shabunin
26ea34c4cb Merge branch '4.x' into '5.x' 2024-06-26 19:01:34 +03:00
Alexander Lyulkov
759fc701ab Fixed cumsum layer, enablem conformance tests 2024-06-14 13:02:57 +03:00
Abduragim Shtanchaev
a2d2ea6536 Merge pull request #25727 from Abdurrahheem:ash/comf-denylist-reduce
Additional Comments for Conformance Denylist #25727

This PR adds additional comments on conformance denylist. Once  BOOL type got support in 5.x, some test layer changed their failing issue.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-06-10 13:51:47 +03:00
alexlyulkov
70df023317 Merge pull request #25605 from alexlyulkov:al/bool-dnn
Added bool support to dnn #25605

Added bool support to dnn pipeline (CPU, OpenVINO and CUDA pipelines).

Added bool support to these layers(CPU and OpenVINO):
- Equal, Greater, GreaterOrEqual, Less, LessOrEqual
- Not
- And, Or, Xor
- Where

Enabled all the conformance tests for these layers.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-06-06 12:52:06 +03:00
Alexander Smorkalov
5bc450d211 Merge pull request #25617 from Abdurrahheem:ash/01D-einsum-test
Fixed out-of-bound access in Einsum layer for 0d
2024-05-22 12:37:30 +03:00
Abduragim Shtanchaev
1f874028fb fixed for openvino einsum 2024-05-22 10:30:10 +04:00
Abduragim Shtanchaev
6feb765ebb Merge pull request #25116 from Abdurrahheem:ash/elementwise-1d-test
Element-wise test for 1D #25116

This PR introduces 1D parametrized test for element wise layer. The means that the tests covers following layer: 

`Clip`, `ReLU6`, `ReLU`,
                        `GeLU`, `GeluApprox`, `TanH`,
                        `Swish`, `Mish`, `Sigmoid`,
                        `ELULayer`, `Abs`, `BNLL`,
                        `Ceil`, `Floor`, `LogLayer`,
                        `Round`, `Sqrt`, `Acos`,
                        `Acosh`, `Asin`, `Asinh`,
                        `Atan`, `Atanh`, `Cos`,
                        `Sin`, `Sinh`, `Tan`, `Erf`,
                        `Reciprocal`, `Cosh`, `HardSwish`,
                        `Softplus`, `Softsign`, `Celu`,
                        `HardSigmid`, `Selu`, `ThresholdedRelu`,
                        `Power`, `Exp`, `Sign`, `Shrink`,
                        `ChannelsPReLU`

Not sure if this is best way to implement this test.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-21 14:05:01 +03:00
Abduragim Shtanchaev
f676cb3c62 Merge pull request #25595 from Abdurrahheem:ash/01D-einsum-test
Add support for scalar and matrix multiplication in einsum #25595

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-21 13:36:12 +03:00
alexlyulkov
9238eb2ab2 Merge pull request #25555 from alexlyulkov:al/int8-uint8-dnn-input
Disabled conversion to float of model's input #25555

In dnn 4.x usually any model's input is converted to float32 or float16 (except quantized models). Also mean and scale can be applied. In current dnn 5.x there is the same conversion except int32 and int64 types. I removed this conversion.

Here is how the pipeline works now:
- if input Mat type is float32, the pipeline applies mean and scale and may convert it to float16.
- if input Mat type is not float32, the pipeline preserves the input type and doesn't apply mean and scale

There was a conflict in protobuf parser between ONNX importer and tests. In ONNX importer any uint8 weight was handled as quantized weight and x = int8(x_uint8 - 128) conversion was used inside the protobuf parser. ONNX conformance tests used the same protobuf reader, so tests with uint8 inputs couldn't read the input values properly. I've made this conversion optional.

These ONNX conformance tests are enabled:
- test_add_uint8
- test_div_uint8
- test_mul_uint8
- test_sub_uint8
- test_max_int8
- test_max_uint8
- test_min_int8
- test_min_uint8
- test_mod_mixed_sign_int8
- test_mod_uint8

These tests were removed:
- Test_two_inputs.basic (when input is uint8)
- setInput.normalization (when input is uint8)

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-16 15:54:00 +03:00
alexlyulkov
6af0394cd2 Merge pull request #25458 from alexlyulkov:al/dnn-openvino-int-support
Added int support for OpenVINO dnn backend #25458

Modified dnn OpenVINO integration to support type inference and int operations.

Added OpenVINO support to Cast, CumSum, Expand, Gather, GatherElements, Scatter, ScatterND, Tile layers.
I tried to add Reduce layer, but looks like OpenVINO uses float values inside Reduce operation so it can't pass our int tests.

OpenVINO uses int32 precision for int64 operations, so I've modified input values for int64 tests when backend is OpenVINO.

OpenVINO has a strange behavior with custom layers and int64 values. After model compilation OpenVINO may change types, so the model can have different output type. That's why these tests were disabled:
- Test_ArgMax_Int.random/0, where GetParam() = (4, NGRAPH/CPU)
- Test_ArgMax_Int.random/6, where GetParam() = (11, NGRAPH/CPU)
- Test_Reduce_Int.random/6, where GetParam() = (11, NGRAPH/CPU)
- Test_Reduce_Int.two_axes/6, where GetParam() = (11, NGRAPH/CPU)

Also these tests were temporary disabled, they didn't work on both 4.x and 5.x branches:
- Test_Caffe_layers.layer_prelu_fc/0, where GetParam() = NGRAPH/CPU
- Test_ONNX_layers.LSTM_Activations/0, where GetParam() = NGRAPH/CPU
- Test_ONNX_layers.Quantized_Convolution/0, where GetParam() = NGRAPH/CPU
- Test_ONNX_layers.Quantized_Eltwise_Scalar/0, where GetParam() = NGRAPH/CPU
- Test_TFLite.EfficientDet_int8/0, where GetParam() = NGRAPH/CPU


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-15 11:51:59 +03:00
Abduragim Shtanchaev
5bdc41964a Merge pull request #25487 from Abdurrahheem:ash/01D-additional-fixes
Additional fixes to 0/1D tests #25487

This has additional fixes requited for 0/1D tests.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-15 10:50:03 +03:00
Abduragim Shtanchaev
5260b48695 Merge pull request #25390 from Abdurrahheem:ash/0d-padding-layer
1/0D test padding layer #25390

This PR introduces 0/1D test for `padding` layer.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-15 10:26:26 +03:00
Gursimar Singh
48c31bddc4 Merge pull request #25559 from gursimarsingh:improved_segmentation_sample
Improved segmentation sample #25559

#25006

This pull request replaces caffe models with onnx for the dnn segmentation sample in cpp and python
fcnresnet-50 and fcnresnet-101 has been replaced
u2netp (foreground-background) segmentation onnx model has been added [U2NET](https://github.com/xuebinqin/U-2-Net) 

### Pull Request Readiness Checklist

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-15 09:39:34 +03:00
Abduragim Shtanchaev
17e6b3f931 Merge pull request #25409 from Abdurrahheem:ash/0D-tile-test
0/1D test for tile layer #25409

This PR introduces `0/1D` test for `Tile` layer. It also add fuctionality to support `0/1D` cases.  


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-14 19:34:04 +03:00
Abduragim Shtanchaev
021e5184bc Merge pull request #25567 from Abdurrahheem:ash/01D-einsum-test
0/1D Einsum Layer Test #25567

This PR introduces 0/1D test cases for Einsum layer.

TODO:
- Add support for 0D tensors to Einsum layer

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-14 15:45:56 +03:00
Wanli
b637e3a66e Merge pull request #25463 from WanliZhong:ocvface2YuNet
Change opencv_face_detector related tests and samples from caffe to onnx #25463

Part of https://github.com/opencv/opencv/issues/25314

This PR aims to change the tests related to opencv_face_detector from caffe framework to onnx. Tests in `test_int8_layer.cpp` and `test_caffe_importer.cpp` will be removed in https://github.com/opencv/opencv/pull/25323

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-05-08 15:49:10 +03:00
Yuantao Feng
4422bc9a7f Merge pull request #25196 from fengyuentau:fp16_bf16_arithm
core: add universal intrinsics for fp16 #25196

Partially resolves the section "Universal intrinsics evolution in OpenCV 5.0" in  https://github.com/opencv/opencv/issues/25019.

Universal intrinsics for bf16 will be added in a subsequent pull request.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-08 15:23:19 +03:00
Alexander Smorkalov
039cf6592c Merge pull request #25544 from FantasqueX:remove-libjpeg-1
Remove deprecated libjpeg build
2024-05-08 15:06:13 +03:00
Wanli
d231b4e362 Merge pull request #25503 from WanliZhong:remove_goturn
Remove goturn caffe model #25503

**Merged with:** https://github.com/opencv/opencv_extra/pull/1174
**Merged with:** https://github.com/opencv/opencv_contrib/pull/3729

Part of https://github.com/opencv/opencv/issues/25314

This PR aims to remove goturn tracking model because Caffe importer will be remove in 5.0

The GOTURN model will take **388 MB** of traffic for each download if converted to onnx. If the user wants to use the tracking method, we can recommend they use Vit or dasimRPN.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-05-06 11:57:30 +03:00
Letu Ren
76f607a44c Remove deprecated libjpeg build 2024-05-05 18:03:40 +08:00
WU Jia
94f4678d3a Merge pull request #25324 from kaingwade:clean_haarcascades_jsbindings
Fix broken js build after moving HaarCascades to contrib #25324

The HaarCascades related are not completely cleaned up #25311 after #25198, which breaks the JavaScript build. The PR is to fix the issue.

Related PR: opencv/opencv_contrib#3712
2024-04-27 14:37:40 +03:00
alexlyulkov
72ad06bcf3 Merge pull request #25492 from alexlyulkov:al/range-fixed-5.x
Fixed ONNX Range layer to support any input type #25492

Fixed ONNX Range layer to support any input type

Extra PR: https://github.com/opencv/opencv_extra/pull/1173
Fixes #25363

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-26 18:59:43 +03:00
Abduragim Shtanchaev
bbe86e6dea Merge pull request #25480 from Abdurrahheem:ash/comf-denylist-reduce
Add logs of test failure to test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp #25480

### Pull Request Readiness Checklist

This PR add logs to test failures to  `test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp` and it continuation of #25442

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-24 11:42:04 +03:00
Abduragim Shtanchaev
f08933b051 Merge pull request #25420 from Abdurrahheem:ash/01D-batchnorm
0/1D test for BatchNorm layer #25420

This PR introduces support for 0/1D inputs in `BatchNorm` layer.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-23 12:03:39 +03:00
Abduragim Shtanchaev
4f81d78c39 Merge pull request #25465 from Abdurrahheem:ash/parser-conf-denylist-reduce
Comments for parser denylist #25465

Relates to https://github.com/opencv/opencv/issues/21078

This PR is designed to figure out why the test in `test_onnx_conformance_layer_parser_denylist.inl.hpp` fails. Currently, conformance tests do not pass for the following reasons:

1. BOOL, INT(8, 16) types are not supported **(MAJOR)**
2. Some layers can not be created due to various reasons  **(MAJOR)**
3. Shape mismatches while creating layers  **(MAJOR)**
4. Some layers are expected to support dynamic parameter initialization  **(MAJOR)**
5. Some layers are expected to receive weight as inputs (no idea why that is needed)   **(MAJOR)**
6. Other unknown reasons

 **(MAJOR)** - These are the most frequently encountered reasons for test failure.

The style of comments is not consistent everywhere. Let's keep this PR without merging, just for our reference.
A couple of tests are commented on since they have passed on the MacOS platform.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-22 16:31:15 +03:00
Alexander Smorkalov
b5ffdd4673 Merge pull request #25428 from asmorkalov:as/win32_arm_ci_5.x
CI pipeline with Windows 10 ARM64 for 5.x #25428

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-04-22 15:56:08 +03:00
Alexander Smorkalov
ac37f337d0 Merge pull request #25467 from fengyuentau:drop_half_members
5.x core: sync changes that drop some member functions in class hfloat
2024-04-22 14:10:22 +03:00
Alexander Smorkalov
43d243dd0e Merge branch 4.x 2024-04-22 11:08:39 +03:00
fengyuentau
65d86b2628 remove zero() and bits() from hfloat 2024-04-22 14:49:51 +08:00
Alexander Smorkalov
c28342f7f2 Merge pull request #25451 from savuor:rv/fix_win_near_far
Fix build for Windows: bad var names in testdata generator
2024-04-19 09:31:01 +03:00
Rostislav Vasilikhin
18a78988a1 fix var names for win 2024-04-19 04:14:46 +02:00
Gursimar Singh
448375d1e7 Merge pull request #25433 from gursimarsingh:colorization_onnx_sample
Replaced caffe model with onnx for colorization sample #25433

#25006

Improved sample for colorization with onnx model in cpp and python. Added a demo image in data folder for testing

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-18 18:15:05 +03:00
Abduragim Shtanchaev
b009a63e6b Merge pull request #25442 from Abdurrahheem:ash/comf-denylist-reduce
Conformance test denylist reduce #25442

Comment out all passing tests in `test_onnx_conformance_layer_filter_opencv_all_denylist.inl.hpp` file. 


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-18 17:22:56 +03:00
Alexander Smorkalov
9d14ce3739 Merge pull request #25438 from mshabunin:cpp-approx-5
imgproc: approx C-API cleanup
2024-04-18 09:38:13 +03:00
Maksim Shabunin
3d88db02d4 imgproc: approx C-API cleanup 2024-04-17 22:25:23 +03:00
Alexander Smorkalov
c3fdb9769d Merge pull request #25431 from mshabunin:cpp-contours-5
imgproc: contours C-API cleanup
2024-04-17 16:15:04 +03:00
Maksim Shabunin
3def7d09bc imgproc: contours C-API cleanup 2024-04-17 14:50:11 +03:00
Alexander Smorkalov
153f147cde Merge pull request #25231 from Abdurrahheem:ash/0D-const-test
Constant layer 0/1D test.
2024-04-17 14:17:05 +03:00
Alexander Smorkalov
5c1fbc2d0f Merge pull request #25429 from asmorkalov:as/drop_float16_t
Drop float16_t alias in 5.x after 4.x merge
2024-04-17 12:40:07 +03:00
Abdurrahheem
6b438835eb Constant layer 0/1D test. 2024-04-17 11:39:31 +03:00
Alexander Smorkalov
7c966efcad Drop float16_t alias in 5.x after 4.x merge. 2024-04-17 10:48:41 +03:00
Alexander Smorkalov
db3e5620cd Merge branch 4.x 2024-04-16 17:28:18 +03:00
Gursimar Singh
68967cf6d7 Merge pull request #25415 from gursimarsingh:improved_drawing_cpp_sample
Improving the drawing cpp sample to draw shapes based on user input #25415

Relates to #25006

The updated samples allows user to draw random shapes by using hot keys.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-16 12:48:18 +03:00
Rostislav Vasilikhin
6699ca1a40 Merge pull request #25382 from savuor:rv/fix_mesh_load
Fix mesh loading for texture coordinates and face indices #25382

### This PR changes

* Texture coordinates were stored incorrectly (3-channel array is read as if there were 2 channels), fixed
* Faces were pushed back to the output array instead of indexed writing which produced a lot of empty faces, fixed
* A set of ground truth tests were added to cover these issues
* `std::vector<cv::Mat>` support added for `saveMesh()` which is required for Python bindings
* More command line args were added to rasterization test data generator

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-16 10:20:44 +03:00
Gursimar Singh
3e561d8353 Merge pull request #25304 from gursimarsingh:geometry_sample_cpp
Geometry C++ sample combining other shape detection samples #25304

Clean Samples #25006
This PR removes adds a new cpp sample (geometry) which combines different methods of finding and drawing shapes in an image. It makes separate samples for convexHull, fitellipse, minAreaRect, minAreaCircle redudant. Shapes can be changed using hotkeys after running the program

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-16 10:13:34 +03:00
Abduragim Shtanchaev
869016d8b1 Merge pull request #25208 from Abdurrahheem:ash/0D-fullyConnected-test
Fully connected 0D test. #25208

This PR introduces parametrized `0/1D` input support test for `Fullyconnected` layer.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-15 09:15:36 +03:00
Alexander Smorkalov
282c762ead Merge branch 4.x 2024-04-10 11:27:47 +03:00
Maksim Shabunin
0e1d326ed0 Merge pull request #25379 from mshabunin:fix-unaligned-filter-5.x
Fix unaligned filters + increase test thresholds (5.x) #25379

Port of #25364 to 5.x + minor changes in 3d tests to pass on RISC-V platform

Failed tests:
```
[ RUN      ] AP3P.ctheta1p_nan_23607
/home/ci/opencv/modules/3d/test/test_solvepnp_ransac.cpp:2320: Failure
Expected: (cvtest::norm(res.colRange(0, 2), expected, NORM_INF)) <= (3e-16), actual: 3.33067e-16 vs 3e-16
[  FAILED  ] AP3P.ctheta1p_nan_23607 (1 ms)

[ RUN      ] Rendering/RenderingTest.accuracy/4, where GetParam() = ((320, 240), Flat, CW, Color, CV_32F, CV_32S)
/home/ci/opencv/modules/3d/test/test_rendering.cpp:430: Failure
Expected: (normL2Depth) <= (normL2Threshold), actual: 0.00102317 vs 0.000989
[  FAILED  ] Rendering/RenderingTest.accuracy/4, where GetParam() = ((320, 240), Flat, CW, Color, CV_32F, CV_32S) (22 ms)

[ RUN      ] Rendering/RenderingTest.accuracy/5, where GetParam() = ((320, 240), Shaded, None, Color, CV_32F, CV_32S)
/home/ci/opencv/modules/3d/test/test_rendering.cpp:430: Failure
Expected: (normL2Depth) <= (normL2Threshold), actual: 0.00102317 vs 0.000989
[  FAILED  ] Rendering/RenderingTest.accuracy/5, where GetParam() = ((320, 240), Shaded, None, Color, CV_32F, CV_32S) (22 ms)

[ RUN      ] Rendering/RenderingTest.accuracy/8, where GetParam() = ((320, 240), Flat, CW, Clipping, CV_32F, CV_32S)
/home/ci/opencv/modules/3d/test/test_rendering.cpp:430: Failure
Expected: (normL2Depth) <= (normL2Threshold), actual: 0.00162132 vs 0.0016
[  FAILED  ] Rendering/RenderingTest.accuracy/8, where GetParam() = ((320, 240), Flat, CW, Clipping, CV_32F, CV_32S) (22 ms)

[ RUN      ] Rendering/RenderingTest.accuracy/9, where GetParam() = ((320, 240), Shaded, None, Clipping, CV_32F, CV_32S)
/home/ci/opencv/modules/3d/test/test_rendering.cpp:430: Failure
Expected: (normL2Depth) <= (normL2Threshold), actual: 0.000554117 vs 0.000544
[  FAILED  ] Rendering/RenderingTest.accuracy/9, where GetParam() = ((320, 240), Shaded, None, Clipping, CV_32F, CV_32S) (27 ms)
```

Related CI PR: https://github.com/opencv/ci-gha-workflow/pull/165
2024-04-10 09:33:10 +03:00
alexlyulkov
f454303f6a Merge pull request #25241 from alexlyulkov:al/int64-padding
Added int support to padding layer #25241

Added int32 and int64 support to padding layer (CPU and CUDA).
ONNX parser doesn't convert non-zero padding value to float now.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-09 11:20:56 +03:00
Alexander Smorkalov
e8a52c7e94 Merge pull request #25099 from Abdurrahheem:ash/slice-1d-test
Slice Layer 1D test
2024-04-09 09:29:53 +03:00
Abdurrahheem
ab7ab7b6be Slice Layer 1D test. 2024-04-09 08:52:49 +03:00
Alexander Smorkalov
f2c3d4dfe3 Merge pull request #25369 from dkurt:resolve_valgrind_warnings
Resolve valgrind warnings
2024-04-08 12:48:59 +03:00
Alexander Smorkalov
3b02f3b7ae Merge pull request #25201 from Abdurrahheem:ash/0D-permute-test
Permute Layer Test 0D
2024-04-08 12:38:51 +03:00
Abdurrahheem
a31f4f4040 git squash 2024-04-08 10:47:23 +03:00
Dmitry Kurtaev
bfd1504de3 Resolve valgrind warnings 2024-04-08 09:35:21 +03:00
Alexander Smorkalov
719830959c Merge pull request #25339 from dkurt:mathjax_formula_in_table_css
Update doc CSS to fit MathJAX formula in table
2024-04-06 13:28:15 +03:00
Abduragim Shtanchaev
22b1b1edac Merge pull request #25071 from Abdurrahheem:ash/1D-scatter
1D Scatter Layer Test #25071

This PR introduces parametrized test for `Scatter` layer to test its functionality for 1D arrays


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-05 15:55:23 +03:00
Dmitry Kurtaev
244c771fb6 Update doc CSS to fit MathJAX formula in table 2024-04-05 11:00:55 +03:00
Alexander Smorkalov
2e784bc7e6 Merge pull request #25330 from alexlyulkov:al/dnn-int64-more-tests
Added int tests for Const, Concat, ScatterND, NaryEltwise, Arg, Blank layers
2024-04-05 09:58:06 +03:00
Alexander Smorkalov
5f98674fe3 Merge pull request #25335 from dkurt:fix_valgrind_3d
Resolve valgrind issue in 3d module
2024-04-04 18:01:24 +03:00
Dmitry Kurtaev
ba62811cc8 Resolve valgrind issue in 3d module 2024-04-04 15:48:14 +03:00
alexlyulkov
5144766380 Merge pull request #25277 from alexlyulkov:al/dnn-int-tests
Added int tests for CumSum, Scatter, Tile and ReduceSum dnn layers #25277

Fixed bug in tile layer.
Fixed bug in reduce layer by reimplementing the layer. 

Fixed types filter in Scatter and ScatterND layers

PR for extra: https://github.com/opencv/opencv_extra/pull/1161


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-04 14:23:48 +03:00
Alexander Smorkalov
87e0246bb0 Merge pull request #25328 from dkurt:fix_rng_fill_oob
Resolve out of bound write in RNG::fill
2024-04-04 14:21:49 +03:00
Alexander Smorkalov
5196b575fe Merge pull request #25074 from Abdurrahheem:ash/1D-softmax-test
1D Input Softmax test
2024-04-04 12:59:53 +03:00
Abdurrahheem
753e2c1dfa Added 1d tensors support to SoftMax layer. 2024-04-04 11:10:24 +03:00
Rostislav Vasilikhin
82038be4cd Merge pull request #25221 from savuor:rv/bench_3d
OBJ and PLY loaders extention to support texture coordinates and difused colors #25221

### This PR changes
* Texture coordinates support added to `loadMesh()` and `saveMesh()`
* `loadMesh()` changes its behavior: all vertex attribute arrays (vertex coordinates, colors, normals, texture coordinates) now have the same size and same-index corresponce
  - This makes sense for OBJ files where vertex attribute arrays are independent from each other and are randomly accessed when defining faces
  - Looks like this behavior may also happen in some PLY files; however, it is not implemented until we encounter such files in a wild nature
  - At the same time `loadPointCloud()` keeps its behavior and loads vertex attributes as they are given in the file
* PLY loader supports synonyms for the properties: `diffuse_red`, `diffuse_green` and `diffuse_blue` along with `red`, `green` and `blue`
* `std::vector<cv::Vec3i>` supported as an index array type
* Colors are loaded as [0, 1] floats instead of uchars
  - Since colors are usually saved as floats, internal conversion to uchar at loading significantly drops accuracy
  - Performing uchar conversion does not always makes sense and can be performed by a user if they needs it
* PLY loading fixed: wrong offset ruined x coordinate
* Python tests added for `loadPointCloud` and `loadMesh`

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-04 11:04:52 +03:00
Abduragim Shtanchaev
65074651a4 Merge pull request #25224 from Abdurrahheem:ash/0D-concat-test
Concat Layer 0/1D test #25224

This PR introduces parametrized `0/1D` input support test for `Concat` layer.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-04 10:36:00 +03:00
Dmitry Kurtaev
56d586aa3e Lest debug checks 2024-04-03 21:55:27 +03:00
Alexander Lyulkov
b64ce1e7f1 Added tests for Const, Concat, ScatterND, NaryEltwise, Arg, Blanc 2024-04-03 18:41:53 +03:00
Dmitry Kurtaev
357203facd Resolve out of bound write in RNG::fill 2024-04-03 18:20:45 +03:00
Alexander Smorkalov
c1e2f16f91 Merge pull request #25225 from Abdurrahheem:ash/0d-expand-test
Expand 0D layer test
2024-04-03 09:53:46 +03:00
Alexander Smorkalov
cb6d295f15 Merge branch 4.x 2024-04-02 16:39:54 +03:00
Abdurrahheem
eddace4d98 git squash 2024-04-01 17:22:39 +04:00
Abdul Rahman ArM
55426ee195 Merge pull request #25197 from invarrow:invbranch-cleanup
Remove OpenVX  #25197

resolves https://github.com/opencv/opencv/issues/24995
OpenCV cleanup https://github.com/opencv/opencv/issues/25007
2024-03-26 15:17:18 +03:00
Abduragim Shtanchaev
5319772a56 Merge pull request #25205 from Abdurrahheem:ash/0D-split-test
0D test for split layer #25205

This PR introduces parametrized `0/1D` input support test for `Split` layer.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-03-26 15:13:41 +03:00
alexlyulkov
f0323fdd1e Merge pull request #25218 from alexlyulkov:al/int64-tile
Allowed int types in Tile and Reduce layers #25218

Allowed any Mat type in Tile layer.
Allowed int64 type in Reduce layer.

ONNX tests with int32 and int64 inputs will be added later in a separate PR


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-03-26 14:00:35 +03:00
Alexander Smorkalov
a33de44b0b Merge pull request #25212 from alexlyulkov:al/dnn-int64-scatter
Added int64 values support to scatter, scatterND and maxunpool layers
2024-03-26 13:52:28 +03:00
alexlyulkov
f8319de976 Added int support to CumSum layer (#25214)
* Added int support to CumSum layer

* Allowed int types in CumSum layer

---------

Co-authored-by: Alexander Lyulkov <alexander.lyulkov@opencv.ai>
2024-03-22 04:35:43 +03:00
Abduragim Shtanchaev
d188319b82 0D test for Reshape layer (#25206)
* reshape test for 0D

* fix comments according to PR
2024-03-22 03:59:08 +03:00
Yuantao Feng
8e342f8857 5.x core: rename cv::bfloat16_t to cv::bfloat (#25232)
* rename cv::bfloat16_t to cv::bfloat

* clean class bfloat
2024-03-22 03:45:59 +03:00
alexlyulkov
aa9e80b07b Added native int64 indices support to gather layer (#25211)
Co-authored-by: Alexander Lyulkov <alexander.lyulkov@opencv.ai>
2024-03-22 03:43:20 +03:00
alexlyulkov
f2cf3c8890 Added int support to flatten, permute, reshape, slice layers (#25236)
Co-authored-by: Alexander Lyulkov <alexander.lyulkov@opencv.ai>
2024-03-22 03:39:42 +03:00
WU Jia
aa5ea340f7 Move objdetect HaarCascadeClassifier and HOGDescriptor to contrib xobjdetect (#25198)
* Move objdetect parts to contrib

* Move objdetect parts to contrib

* Minor fixes.
2024-03-21 23:40:10 +03:00
Alexander Alekhin
213e1a4d9d Merge pull request #25234 from mshabunin:doc-auto-dot-5.x 2024-03-20 09:20:57 +00:00
Maksim Shabunin
11eac62ac3 doc: auto-enabling DOT support in documentation if dot executable has been found 2024-03-19 19:19:11 +03:00
Alexander Lyulkov
d2d6869a26 Added int64 values support to scatter, scatterND and maxunpool layers 2024-03-13 15:40:07 +03:00
alexlyulkov
85cc02f4de Allowed int64 constants in ONNX parser (#25148)
* Removed automatic int64 to int32 conversion in ONNX parser

* Fixed wrong rebase code

* added tests, minor fixes

* fixed Cast layer

* Fixed Cast layer for fp16 backend

* Fixed Cast layer for fp16 backend

* Fixed Cast layer for fp16 backend

* Allowed uint32, int64, uint64 types in OpenCL

* Fixed Cast layer for fp16 backend

* Use randu in test_int

---------

Co-authored-by: Alexander Lyulkov <alexander.lyulkov@opencv.ai>
2024-03-13 11:48:23 +03:00
Maksim Shabunin
de29223217 Merge pull request #25161 from mshabunin:doc-upgrade-5.x
Documentation transition to fresh Doxygen (5.x) #25161 

Port of #25042

Merge with opencv/opencv_contrib#3687
CI part: opencv/ci-gha-workflow#162
2024-03-06 08:50:31 +03:00
Alexander Smorkalov
c6776ec136 Merge pull request #25159 from Kumataro:trial_to_fix_cv_check_24411
dnn: fix to iteration variable scope
2024-03-05 16:01:25 +03:00
Kumataro
216c6c3da1 dnn: fix to iteration variable scope 2024-03-05 18:33:56 +09:00
Maksim Shabunin
8cbdd0c833 Merge pull request #25075 from mshabunin:cleanup-imgproc-1
C-API cleanup: apps, imgproc_c and some constants #25075

Merge with https://github.com/opencv/opencv_contrib/pull/3642

* Removed obsolete apps - traincascade and createsamples (please use older OpenCV versions if you need them). These apps relied heavily on C-API
* removed all mentions of imgproc C-API headers (imgproc_c.h, types_c.h) - they were empty, included core C-API headers
* replaced usage of several C constants with C++ ones (error codes, norm modes, RNG modes, PCA modes, ...) - most part of this PR (split into two parts - all modules and calib+3d - for easier backporting)
* removed imgproc C-API headers (as separate commit, so that other changes could be backported to 4.x)

Most of these changes can be backported to 4.x.
2024-03-05 12:18:31 +03:00
alexlyulkov
1d1faaabef Merge pull request #24411 from alexlyulkov:al/dnn-type-inference
Added int32, int64 support and type inference to dnn #24411

**Added a type inference to dnn similar to the shape inference, added int32 and int64 support.**

- Added getTypes method for layers that calculates layer outputs types and internals types from inputs types (Similar to getMemoryShapes). By default outputs and internals types = input[0] type
- Added type inference pipeline similar to shape inference pipeline. LayersShapes struct (that is used in shape inference pipeline) now contains both shapes and types
- All layers output blobs are now allocated using the calculated types from the type inference.
- Inputs and constants with int32 and int64 types are not automatically converted into float32 now.
- Added int32 and int64 support for all the layers with indexing and for all the layers required in tests.

Added  int32 and int64 support for CUDA:
- Added host<->device data moving for int32 and int64
- Added int32 and int64 support for several layers (just slightly modified CUDA C++ templates)

Passed all the accuracy tests on CPU, OCL, OCL_FP16, CUDA, CUDA_FP16. (except RAFT model)

**CURRENT PROBLEMS**:
-  ONNX parser always converts int64 constants and layers attributes to int32, so some models with int64 constants doesn't work (e.g. RAFT). The solution is to disable int64->int32 conversion and fix attributes reading in a lot of ONNX layers parsers (https://github.com/opencv/opencv/issues/25102)
- I didn't add type inference and int support to VULCAN, so it doesn't work at all now.
- Some layers don't support int yet, so some unknown models may not work.

**CURRENT WORKAROUNDS**:
- CPU arg_layer indides are implemented in int32 followed by a int32->int64 conversion (the master branch has the same workaround with int32->float conversion)
- CPU and OCL pooling_layer indices are implemented in float followed by a float->int64 conversion
- CPU gather_layer indices are implemented in int32, so int64 indices are converted to int32 (the master branch has the same workaround with float->int32 conversion)

**DISABLED TESTS**:
- RAFT model

**REMOVED TESTS**:
- Greater_input_dtype_int64 (because it doesn't fit ONNX rules, the whole test is just comparing float tensor with int constant)

**TODO IN NEXT PULL REQUESTS**:
- Add int64 support for ONNX parser
- Add int support for more layers
- Add int support for OCL (currently int layers just run on CPU)
- Add int tests
- Add int support for other backends
2024-03-01 17:07:38 +03:00
Alexander Smorkalov
81956ad83e Merge pull request #25124 from asmorkalov:as/dnn_1d
Extracted 1d test cases to reduce conflicts with 4.x.
2024-02-29 14:50:28 +03:00
Zhangjie Chen
0e47b05106 Merge pull request #23985 from starga2er777:pcc
[GSoC] Update octree methods and create frames for PCC #23985

## PR for GSoC Point Cloud Compression
[Issue for GSoC 2023](https://github.com/opencv/opencv/issues/23624)

* We are **updating the Octree method create() by using OctreeKey**: Through voxelization, directly calculate the leaf nodes that the point cloud belongs to, and omit the judgment whether the point cloud is in the range when inserted. The index of the child node is calculated by bit operation.
* We are also **introducing a new header file pcc.h (Point Cloud Compression) with API framework**.
* We added tests for restoring point clouds from an octree.
* Currently, the features related to octree creation and point cloud compression are part of the internal API, which means they are not directly accessible to users. However, our plan for the future is to **include only the 'PointCloudCompression' class in the 'opencv2/3d.hpp' header file**. This will provide an interface for utilizing the point cloud compression functionality.

The previous PR of this was closed due to repo name conflicts, therefore we resubmitted in this PR.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-02-29 14:02:44 +03:00
Alexander Smorkalov
010772b492 Extracted 1d test cases to reduce conflicts with 4.x. 2024-02-29 12:02:00 +03:00
Alexander Smorkalov
92b940792a Merge pull request #25117 from Abdurrahheem:ash/scale-layer-1D-test
Scale layer 1d test
2024-02-29 11:32:13 +03:00
Alexander Smorkalov
a22130fbfa Merge branch 4.x 2024-02-28 18:49:05 +03:00
Alexander Smorkalov
e02d256ff3 Merge pull request #25063 from asmorkalov:as/multiview_calib_sample_py
Ground truth check and Charuco support in multiview_calibration.py
2024-02-28 16:36:56 +03:00
Abdurrahheem
161c402f02 seperated working scale layer 1d test. 2024-02-28 13:04:48 +04:00
lpanaf
40dfe8e8fe Ground truth check and Charuco support in multiview_calibration.py 2024-02-28 10:31:56 +03:00
WU Jia
6722d4a524 Merge pull request #25017 from kaingwade:ml_to_contrib
Move ml to opencv_contrib #25017
OpenCV cleanup: #24997

opencv_contrib: opencv/opencv_contrib#3636
2024-02-27 15:54:08 +03:00
Alexander Smorkalov
cb7d38b477 Merge branch 4.x 2024-02-26 18:05:36 +03:00
Alexander Smorkalov
4c549b8707 Merge pull request #25061 from asmorkalov:as/register_cameras
RegisterCameras function for heterogenious cameras pair #25061

Credits to Linfei Pan
Extracted from https://github.com/opencv/opencv/pull/24052

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

---------

Co-authored-by: lpanaf <linpan@student.ethz.ch>
2024-02-26 15:45:18 +03:00
Abduragim Shtanchaev
093ed08892 Merge pull request #24977 from Abdurrahheem:ash/primitive_1d_tests
Primitive 1D Tests #24977

This PR is designed to add tests for 1D inputs for layer, which is required after introducing 1d support in 5.x. Currently tests are written for following layers: 

- [x] `Add`, `Sub`
- [x]  `Product`, `Div`
- [x]  `Min`, `Max`
- [x] `Argmin`, `Argmax`
- [x] `Gather` 

This list is to be extended for more layer such `gemm`, `conv` etc.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-02-21 17:37:49 +03:00
Alexander Smorkalov
a0df2f5328 Merge pull request #25021 from asmorkalov:as/multiview_calib_generator_ext
Multiview calibration generator improvements
2024-02-20 15:15:16 +03:00
Rostislav Vasilikhin
fa745553bf Merge pull request #24459 from savuor:tri_rasterize
Triangle rasterization function #24459

#24065 reopened since the previous one was automatically closed after rebase
Connected PR with ground truth data: [#1113@extra](https://github.com/opencv/opencv_extra/pull/1113)

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-02-19 12:23:05 +03:00
Alexander Smorkalov
f084a229b4 Merge branch 4.x 2024-02-19 09:06:26 +03:00
Yuantao Feng
d4fd5157fa Merge pull request #24980 from fengyuentau:on-fly-quantization-removal
dnn cleanup: On-fly-quantization removal #2498

On-fly-quantization is first introduced via https://github.com/opencv/opencv/pull/20228.
We decided to remove it but keep int8 layers implementation because on-fly-quantization
is less practical given the fact that there has been so many dedicated tools for model
quantization.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-02-16 18:21:45 +03:00
Martin Štefaňák
3125f9708d Merge pull request #24989 from zteffi:enable-warpPointBackward-in-python
Remove bypass for ABI check in warpPointBackward #24989

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] ~~There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.~~
- [x] The feature is well documented and sample code can be built with the project CMake

### What? 
In my [PR](d31b6c3480) regarding `warpPointBackward`, I was asked by alalek to [add a bypass](https://github.com/opencv/opencv/pull/18607/files#r508423486) to python wrapper class, presumably to ship the changes in the newest patch release (4.5.1).

The bypass was not removed in 4.6.0 release, so please remove it in either 4.10.0 or 4.11.0. Thanks!

Co-authored-by: Martin Stefanak <martin.stefanak@codasip.com>
Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>
2024-02-16 16:27:29 +03:00
Alexander Smorkalov
12b7aac1a0 Dump board poses human-readable and machine-readable format. 2024-02-14 15:17:01 +03:00
lpanaf
0957437bbe Save ground truth in calibration data generator. 2024-02-14 14:26:18 +03:00
Alexander Smorkalov
201a753e4a Merge pull request #25015 from asmorkalov:as/out_of_bound_mat_formatter
Fixed possible out-of-bound access in cv::Mat output formatter
2024-02-14 09:33:21 +03:00
Alexander Smorkalov
52be0b64fb Fixed possible out-of-bound access in cv::Mat output formatter. 2024-02-13 17:34:40 +03:00
Alexander Smorkalov
fa3f1822ae Merge pull request #24993 from asmorkalov:as/FastNeuralStyle_eccv16_CUDA
Relax test requirements for CUDA in DNNTestNetwork.FastNeuraStyle_eccv16
2024-02-12 16:37:57 +03:00
Rostislav Vasilikhin
f96111ef05 Merge pull request #24961 from savuor:rv/ply_mesh
PLY mesh support #24961

**Warning:** The PR changes exising API.

Fixes #24960
Connected PR: [#1145@extra](https://github.com/opencv/opencv_extra/pull/1145)

### Changes
* Adds faces loading from and saving to PLY files
* Fixes incorrect PLY loading (see issue)
* Adds per-vertex color loading / saving

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-02-12 15:34:54 +03:00
Alexander Smorkalov
466ad96b1d Merge pull request #24992 from Kumataro:fix24991
ts: Extended getTypeName() to support new types
2024-02-12 15:32:52 +03:00
Alexander Smorkalov
5ce0acce40 Relax test requirements for CUDA in DNNTestNetwork.FastNeuraStyle_eccv16 2024-02-12 14:47:37 +03:00
Alexander Smorkalov
3a55f50133 Merge branch 4.x 2024-02-12 14:20:35 +03:00
Kumataro
3b85d5fac7 ts: Extended getTypeName() to support new types 2024-02-12 17:56:43 +09:00
Vadim Pisarevsky
1d18aba587 Extended several core functions to support new types (#24962)
* started adding support for new types (16f, 16bf, 32u, 64u, 64s) to arithmetic functions

* fixed several tests; refactored and extended sum(), extended inRange().

* extended countNonZero(), mean(), meanStdDev(), minMaxIdx(), norm() and sum() to support new types (F16, BF16, U32, U64, S64)

* put missing CV_DEPTH_MAX to some function dispatcher tables
* extended findnonzero, hasnonzero with the new types support

* extended mixChannels() to support new types

* minor fix

* fixed a few compile errors on Linux and a few failures in core tests

* fixed a few more warnings and test failures

* trying to fix the remaining warnings and test failures. The test `MulTestGPU.MathOpTest` was disabled - not clear whether to set tolerance - it's not bit-exact operation, as possibly assumed by the test, due to the use of scale and possibly limited accuracy of the intermediate floating-point calculations.

* found that in the current snapshot G-API produces incorrect results in Mul, Div and AddWeighted (at least when using OpenCL on Windows x64 or MacOS x64). Disabled the respective tests.
2024-02-11 10:42:41 +03:00
Alexander Smorkalov
f05ef64df8 Merge pull request #24922 from asmorkalov:as/static_aar_fix
Fix AAR build with static OpenCV libraries for Android.
2024-01-27 12:46:09 +03:00
Alexander Smorkalov
4930c9cebc Fix AAR build with static OpenCV libraries for Android. 2024-01-25 18:15:45 +03:00
Alexander Smorkalov
decf6538a2 Merge branch 4.x 2024-01-23 17:06:52 +03:00
Alexander Smorkalov
d6424233f0 Merge pull request #24906 from Abdurrahheem:ash/fix_einsum_inner
Einsum Layer Inner Product Issue Solution
2024-01-23 09:26:22 +03:00
Alexander Smorkalov
dcc4dcedba Merge pull request #24900 from asmorkalov:as/windows_warn_fix_5.x
Fixed type cast warning in CV_ELEM_SIZE1 for cv::Mat::type
2024-01-23 09:18:43 +03:00
Alexander Smorkalov
f1e1145546 Merge pull request #24899 from asmorkalov:as/style_transfer_ocl
Relax test requirements for OpenCL in test DNNTestNetwork.FastNeuraStyle_eccv16
2024-01-23 09:17:48 +03:00
Abduragim
0e6b7f1656 fix 1D handling issue in inner product 2024-01-22 20:10:34 +04:00
Alexander Smorkalov
775210e701 Relax test requirements for OpenCL in test DNNTestNetwork.FastNeuralStyle_eccv16. 2024-01-22 17:11:41 +03:00
Alexander Smorkalov
4e2c7221f2 Fixed type cast warning in CV_ELEM_SIZE1 for cv::Mat::type. 2024-01-22 12:08:55 +03:00
Alexander Smorkalov
c739117a7c Merge branch 4.x 2024-01-19 17:32:22 +03:00
Alexander Smorkalov
788c7252dc Merge pull request #24830 from Abdurrahheem:ash/einsum_1d_support
1d  operation support for einsum layer
2024-01-12 14:21:13 +03:00
Abduragim
6c28d7140a 1d support for einsum 2024-01-08 21:34:47 +03:00
Kumataro
bae435a5a7 Merge pull request #24578 from Kumataro:fix_verify_unsupported_new_mat_depth
Fix verify unsupported new mat depth for nonzero/minmax/lut #24578

`cv::LUI()`, `cv::minMaxLoc()`, `cv::minMaxIdx()`, `cv::countNonZero()`, `cv::findNonZero()` and `cv::hasNonZero()` uses depth-based function table. However, it is too short for `CV_16BF`, `CV_Bool`, `CV_64U`, `CV_64S` and `CV_32U` and it may occur out-boundary-access. This patch fix it. And If necessary, when someone extends these functions to support, please relax this test.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-11-23 12:15:58 +03:00
Alexander Smorkalov
4b4c130f0a Merge pull request #24561 from asmorkalov:usac_bug_fix_port
Port of Replace double atomic in USAC
2023-11-20 21:26:45 +03:00
Maksym Ivashechkin
607d92858f Port of Replace double atomic in USAC
Port of solution for:
- https://github.com/opencv/opencv/issues/24482
- https://github.com/opencv/opencv/issues/24281

Original PR: https://github.com/opencv/opencv/pull/24499
2023-11-20 16:42:00 +03:00
Alexander Alekhin
3af68fa857 Merge pull request #24517 from mshabunin:fix-3d-test 2023-11-09 20:06:31 +00:00
Maksim Shabunin
fefbcfeb0b 3d: fix static init in test 2023-11-09 22:07:59 +03:00
Rostislav Vasilikhin
53aad98a1a Merge pull request #23098 from savuor:nanMask
finiteMask() and doubles for patchNaNs() #23098

Related to #22826
Connected PR in extra: [#1037@extra](https://github.com/opencv/opencv_extra/pull/1037)

### TODOs:
- [ ] Vectorize `finiteMask()` for 64FC3 and 64FC4

### Changes

This PR:
* adds a new function `finiteMask()`
* extends `patchNaNs()` by CV_64F support
* moves `patchNaNs()` and `finiteMask()` to a separate file

**NOTE:** now the function is called `finiteMask()` as discussed with the OpenCV core team

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-11-09 10:32:47 +03:00
Alexander Smorkalov
34f34f6227 Merge branch 4.x 2023-11-08 14:39:48 +03:00
Alexander Smorkalov
0e6430abcb Merge pull request #24453 from asmorkalov:as/riscv-ci-5.x
Enable RISC-V CI configuration for 5.x
2023-10-26 13:28:03 +03:00
alexlyulkov
b71be65f57 Merge pull request #24294 from alexlyulkov:al/remove-torch7-from-dnn
Remove torch (old torch7) from dnn in 5.x #24294

Merge with https://github.com/opencv/opencv_extra/pull/1097

Completely removed torch (old torch7) from dnn:
- removed modules/dnn/src/torch directory that contained torch7 model parser
- removed readNetFromTorch() and readTorchBlob() public functions
- removed torch7 references from comments and help texts
- replaced links to t7 models by links to similar onnx models in js_style_transfer turtorial (similar to https://github.com/opencv/opencv/pull/24245/files)
2023-10-26 11:27:56 +03:00
Alexander Smorkalov
8495910165 Enable RISC-V CI configuration for 5.x 2023-10-26 08:26:37 +03:00
Alexander Smorkalov
97620c053f Merge branch 4.x 2023-10-23 11:53:04 +03:00
Yuantao Feng
d789cb459c Merge pull request #24231 from fengyuentau:halide_cleanup_5.x
dnn: cleanup of halide backend for 5.x #24231

Merge with https://github.com/opencv/opencv_extra/pull/1092.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-10-13 16:53:18 +03:00
Alexander Smorkalov
0976765c62 Merge pull request #24357 from Kumataro:fix24121
imgproc: move stb_truetype functions into cv namespace
2023-10-05 09:37:08 +03:00
Kumataro
3a424b7f1c imgproc: move stb_trutype functions into cv namespace 2023-10-03 20:45:23 +00:00
Alexander Smorkalov
163d544ecf Merge branch 4.x 2023-10-02 10:17:23 +03:00
Alexander Alekhin
c5ff405d94 Merge pull request #24262 from mshabunin:fix-riscv-5x 2023-09-22 21:11:59 +00:00
Maksim Shabunin
c3a37d0fcb RISC-V: fix compilation in RVV scalable mode 2023-09-22 21:08:33 +03:00
Vadim Pisarevsky
416bf3253d attempt to add 0d/1d mat support to OpenCV (#23473)
* attempt to add 0d/1d mat support to OpenCV

* revised the patch; now 1D mat is treated as 1xN 2D mat rather than Nx1.

* a step towards 'green' tests

* another little step towards 'green' tests

* calib test failures seem to be fixed now

* more fixes _core & _dnn

* another step towards green ci; even 0D mat's (a.k.a. scalars) are now partly supported!

* * fixed strange bug in aruco/charuco detector, not sure why it did not work
* also fixed a few remaining failures (hopefully) in dnn & core

* disabled failing GAPI tests - too complex to dig into this compiler pipeline

* hopefully fixed java tests

* trying to fix some more tests

* quick followup fix

* continue to fix test failures and warnings

* quick followup fix

* trying to fix some more tests

* partly fixed support for 0D/scalar UMat's

* use updated parseReduce() from upstream

* trying to fix the remaining test failures

* fixed [ch]aruco tests in Python

* still trying to fix tests

* revert "fix" in dnn's CUDA tensor

* trying to fix dnn+CUDA test failures

* fixed 1D umat creation

* hopefully fixed remaining cuda test failures

* removed training whitespaces
2023-09-21 18:24:38 +03:00
Alexander Smorkalov
fdab565711 Merge branch 4.x 2023-09-13 14:49:25 +03:00
Alexander Smorkalov
a6748df587 Merge branch 4.x 2023-08-08 17:32:17 +03:00
Alexander Smorkalov
b47704eabc Merge pull request #24125 from asmorkalov:as/pack_store_bfloat16
Fix v_pack_store alignment issue on Windows 32-bit.
2023-08-08 17:21:43 +03:00
Alexander Smorkalov
2311c14582 Fix v_pack_store alignment issue on Windows 32-bit. 2023-08-08 14:10:29 +03:00
Alexander Smorkalov
5f5fb11c66 Merge pull request #24118 from asmorkalov:as/prev_merge_artifact
Removed merge previous 4.x->5.x merge artifact
2023-08-08 09:01:42 +03:00
Alexander Smorkalov
b5a189a978 Removed merge previous 4.x->5.x merge artifact. 2023-08-07 17:45:58 +03:00
Vadim Pisarevsky
518486ed3d Added new data types to cv::Mat & UMat (#23865)
* started working on adding 32u, 64u, 64s, bool and 16bf types to OpenCV

* core & imgproc tests seem to pass

* fixed a few compile errors and test failures on macOS x86

* hopefully fixed some compile problems and test failures

* fixed some more warnings and test failures

* trying to fix small deviations in perf_core & perf_imgproc by revering randf_64f to exact version used before

* trying to fix behavior of the new OpenCV with old plugins; there is (quite strong) assumption that video capture would give us frames with depth == CV_8U (0) or CV_16U (2). If depth is > 7 then it means that the plugin is built with the old OpenCV. It needs to be recompiled, of course and then this hack can be removed.

* try to repair the case when target arch does not have FP64 SIMD

* 1. fixed bug in itoa() found by alalek
2. restored ==, !=, > and < univ. intrinsics on ARM32/ARM64.
2023-08-04 10:50:03 +03:00
Alexander Smorkalov
fa91c1445e Merge pull request #24096 from asmorkalov:as/vrabaud_calibration_port
Port stereoRectify grid fix #24035
2023-08-04 10:40:38 +03:00
Alexander Smorkalov
da28c62855 Port stereoRectify grid fix #24035. 2023-08-03 11:27:59 +03:00
Alexander Smorkalov
9ddf1e5c77 Merge pull request #24084 from asmorkalov:as/stereoRectify
Finalize calib3d module split for fisheye part
2023-08-03 11:00:00 +03:00
Alexander Smorkalov
285108e2e1 Finalize calib3d module split for fisheye part. 2023-08-03 09:21:05 +03:00
Alexander Smorkalov
802af10e44 Merge pull request #24095 from asmorkalov:as/5.x-ci-ubuntu22
Add CI configuration with Ubuntu 22.04 for 5.x branch.
2023-08-02 20:37:28 +03:00
Alexander Smorkalov
7889ed7f80 Merge pull request #23957 from lpanaf:multi-calib-fix
add error in the first camera to the cost function
2023-08-02 17:45:15 +03:00
lpanaf
36d688ec10 add error in the first camera to the cost function 2023-08-02 15:45:23 +03:00
Alexander Smorkalov
eab8eb8f3b Add CI configuration with Ubuntu 22.04 for 5.x branch. 2023-08-02 11:43:25 +03:00
Alexander Smorkalov
47188b7c7e Merge branch 4.x 2023-07-28 13:05:36 +03:00
Maksym Ivashechkin
0e8748746f Merge pull request #24005 from ivashmak:merge_usac_5.x
Merge usac to 5.x #24005

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake


Base branch is PR #23979. Merging PR #23078, 23900 and PR #23806  to 5.x
2023-07-27 17:51:16 +03:00
Zhangjie Chen
4d695cd2f4 Merge pull request #23805 from starga2er777:5.x
GSoC: Modified PLY reader to support color attribute read/write #23805

* Modified PLY reader to support color attribute read/write
* Fix bugs & Modified OBJ reader for color IO
* Replace with correct test file
* Fix I/O of property [w] in OBJ files

### Pull Request Readiness Checklist

**Merged with https://github.com/opencv/opencv_extra/pull/1075**

[Issue for GSoC 2023](https://github.com/opencv/opencv/issues/23624)
The ply loader in 3D module doesn't support color attribute reading. I modified that to support color attribute reading & writing for the color attribute compression as described in proposal.

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-07-25 16:05:56 +03:00
Alexander Smorkalov
18f280b869 Merge pull request #23990 from asmorkalov:as/5.x_calib_api_cleanup
Unify Pinhole and Fisheye camera models
2023-07-23 09:55:49 +03:00
Alexander Smorkalov
8595066afc Unify Pinhole and Fisheye camera calibration flags. 2023-07-19 14:58:08 +03:00
Alexander Smorkalov
a484f39f47 Merge pull request #23988 from asmorkalov:as/drop_python2
Drop Python2 support
2023-07-18 09:59:15 +03:00
Alexander Smorkalov
1a3523d2d8 Drop Python2 support. 2023-07-14 15:06:53 +03:00
Alexander Smorkalov
cea26341a5 Merge branch 4.x 2023-07-13 09:28:36 +03:00
Alexander Smorkalov
eb717a7e91 Merge pull request #23919 from asmorkalov:as/5.x-vulkan
Enable Vulkan tests for 5.x branch after 4.x->5.x merge
2023-07-06 12:30:04 +03:00
Alexander Smorkalov
bd9a3ee161 Enable Vulkan tests for 5.x branch after 4.x->5.x merge. 2023-07-06 10:16:52 +03:00
Alexander Smorkalov
f987bf2961 Merge pull request #23814 from Avasam:fix-type-confindece
Fix typo `confindece`
2023-07-05 17:51:32 +03:00
Alexander Smorkalov
5af40a0269 Merge branch 4.x 2023-07-05 15:51:10 +03:00
Avasam
277b0231f2 fix typo confindece 2023-06-16 20:26:26 -04:00
Alexander Smorkalov
d24ffe9a65 Merge pull request #23705 from asmorkalov:as/cxx-named-arguments
Re-implement named parameters bindings for Python #23705

Reverted named argument handling from #19156.
Ported new solution from #23224
The port is required to harmonize 4.x -> 5.x merges.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2023-05-30 17:41:41 +03:00
Maksym Ivashechkin
67a3d35b4e Merge pull request #22363 from ivashmak:multiview-calib
Add multiview calibration [GSOC 2022]

### Pull Request Readiness Checklist

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake

The usage tutorial is on Google Docs following this link: https://docs.google.com/document/d/1k6YpD0tpSVqnVnvU2nzE34K3cp_Po6mLWqXV06CUHwQ/edit?usp=sharing
2023-03-23 15:42:41 +03:00
Vladimir Ponomarev
0c55ed0ca8 Merge pull request #23291 from vovka643:5.x_depricated_backends
Merge with https://github.com/opencv/opencv_contrib/pull/3446
Related issue: https://github.com/opencv/opencv/issues/11810

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-03-15 09:41:36 +03:00
Alexander Smorkalov
a792252b55 Merge pull request #23283 from vrabaud:5_overflow
Fix signed integer overflow.
2023-03-10 10:04:08 +03:00
Vincent Rabaud
f7ce715596 Fix signed integer overflow.
The overflow happens for INT_MAX so the code just needs to be moved down.
2023-02-20 23:52:22 +01:00
Rostislav Vasilikhin
23dec329b4 Merge pull request #23150 from savuor:port5_stereo_calib_per_obj
### Changes

* Port of #22519 to 5.x
* Distortion coefficients were not copied properly, fixed
* Minor coding style chages

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-02-02 16:44:28 +03:00
Alexander Smorkalov
29dc07b1f3 Merge pull request #23186 from savuor:warnings_3d
MSVC warnings fixed in 3d module
2023-01-30 10:09:01 +03:00
Alexander Alekhin
e880d51e1c Merge pull request #23189 from alalek:5.x-merge-4.x 2023-01-30 05:32:39 +00:00
Alexander Alekhin
3c8e97ff6a 3d(test): change tolerance of Volume/VolumeTestFixture.valid_points 2023-01-30 05:27:02 +00:00
Alexander Alekhin
1d530eb2e2 core(test_math): replace the_rng() => cv::theRNG() 2023-01-29 19:51:18 +00:00
Alexander Alekhin
4500a5369c 3d(test): don't use RNG in SetUp() 2023-01-29 17:14:25 +00:00
Alexander Alekhin
f33598f55e Merge branch 4.x 2023-01-28 17:31:32 +00:00
Rostislav Vasilikhin
285218915c msvc cast warnings 2023-01-27 17:20:12 +01:00
Rostislav Vasilikhin
8329c09ba8 Merge pull request #23178 from savuor:stddev_calib_fisheye
Fixes #23057

Parameter uncertainty fixed + ground truth test data fixed

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2023-01-27 09:40:08 +03:00
Alexander Alekhin
a42d879925 Merge branch 4.x 2023-01-18 22:03:42 +00:00
Alexander Alekhin
6904207b60 Merge pull request #23143 from vrabaud:compil5_1 2023-01-17 20:25:20 +03:00
Vincent Rabaud
44c46e545a Fix compilation with msan 2023-01-17 13:26:59 +01:00
Alexander Alekhin
593a376566 Merge branch 4.x 2023-01-09 11:08:02 +00:00
Maksim Shabunin
8a62b03761 Merge pull request #22754 from mshabunin:c-cleanup
C-API cleanup for OpenCV 5.x (imgproc, highgui)

* imgproc: C-API cleanup

* imgproc: increase cvtColor test diff threshold

* imgproc: C-API cleanup pt.2

* imgproc: C-API cleanup pt.3

* imgproc: C-API cleanup pt.4

* imgproc: C-API cleanup pt.5

* imgproc: C-API cleanup pt.5

* imgproc: C-API cleanup pt.6

* highgui: C-API cleanup

* highgui: C-API cleanup pt.2

* highgui: C-API cleanup pt.3

* highgui: C-API cleanup pt.3

* imgproc: C-API cleanup pt.7

* fixup! highgui: C-API cleanup pt.3

* fixup! imgproc: C-API cleanup pt.6

* imgproc: C-API cleanup pt.8

* imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9
2022-12-14 18:57:08 +00:00
Rostislav Vasilikhin
d49958141e Merge pull request #22925 from savuor:pytsdf_from_scratch
Fixes #22799

Replaces #21559 which was taken as a base

Connected PR in contrib: [#3388@contrib](https://github.com/opencv/opencv_contrib/pull/3388)

### Changes
OK, now this is more Odometry-related PR than Volume-related. Anyway,
* `Volume` class gets wrapped
* The same was done for helper classes like `VolumeSettings`, `OdometryFrame` and `OdometrySettings`
* `OdometryFrame` constructor signature changed to more convenient where depth goes on 1st place, RGB image on 2nd.
This works better for depth-only `Odometry` algorithms.
* `OdometryFrame` is checked for amount of pyramid layers inside `Odometry::compute()`
* `Odometry` was fully wrapped + more docs added
* Added Python tests for `Odometry`, `OdometryFrame` and `Volume`
* Added Python sample for `Volume`
* Minor fixes including better var names

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2022-12-12 09:40:12 +03:00
Rostislav Vasilikhin
86c6e07326 Merge pull request #22863 from savuor:tsdf_tests_join
### Changes
* Duplicated code removal in TSDF tests by implementing them with fixtures and GTest params
  * e.g. separate OCL tests file removed
  * as a result, more test cases are covered
  * the same's done for perf tests

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2022-12-06 12:15:39 +03:00
Rostislav Vasilikhin
a423b07149 Merge pull request #22845 from savuor:volume_interface_etc
Corresponding contrib PR: #3382@contrib

Changes

- Volume::raycast(): camera intrinsics can be explicitly passed to the function. If not, the ones from current volume settings are used
- getVolumeDimensions() renamed to getVolumeStrides() because they are strides actually
- TSDF tests: OpenCLStatusRevert and parametrized fixture
- ColorTSDF::integrate(): extra RGB projector is redundant, removed
- Minor changes
2022-11-24 17:16:18 +03:00
Rostislav Vasilikhin
2407ab4e61 Merge pull request #22178 from savuor:hash_tsdf_fixes
This PR contains:

- a new property enableGrowth which controls should the HashTSDF be extended during integration by adding new volume units or not
- a new method getBoundingBox which calculates the size of currently occupied data
- a set of tests to check that new functionality
- a fix for TSDF GPU reset (data is correctly zeroed now using floatToTsdf() function)
    minor changes
2022-11-22 09:24:41 +03:00
Rostislav Vasilikhin
a9d98bfb34 Merge pull request #22741 from savuor:hashtsdf_volposerot_fix
There's a bug which appears when volume pose contains non-trivial rotation.
It results in wrong depth integration which can be observed during raycasting 
or points/normals export.

- This PR fixes the bug for both CPU and OpenCL
- There is a reproducer for the bug
- The copy behavior of VolumeSettings fixed (now copy constructor creates a deep copy)
- Minor changes (e.g. unused vars removed)
2022-11-17 09:10:35 +03:00
Yuhang Wang
d976272d23 Merge pull request #22682 from TsingYiPainter:5.x
3D: Handle cases where the depth of Octree setting is too large

* Handle cases where the depth setting is too large
2022-11-03 07:15:17 +00:00
Alexander Smorkalov
7e3d56e2ff Merge pull request #22691 from savuor:icp_oframe_docs
Docs added for Odometry and OdometryFrame
2022-10-26 13:18:25 +03:00
Alexander Smorkalov
733fb673c8 Merge pull request #22693 from asmorkalov:as/arm_debug_5x
5.x: Added ARM64 debug configuration to CI.
2022-10-26 12:01:04 +03:00
Rostislav Vasilikhin
a09bb3c2f6 doc fixes 2022-10-25 22:37:38 +02:00
Alexander Smorkalov
b00ac7b07a Added ARM64 debug configuration to CI. 2022-10-25 13:44:14 +03:00
Rostislav Vasilikhin
95ab8517ae trailing whitespaces 2022-10-25 02:58:55 +02:00
Rostislav Vasilikhin
a1820ff3d4 unused function removed 2022-10-25 02:45:42 +02:00
Rostislav Vasilikhin
097b0245da getScaledDepth -> getProcessedDepth 2022-10-25 02:45:28 +02:00
Rostislav Vasilikhin
52d82bb44a docs for Odometry+Frame 2022-10-25 02:44:12 +02:00
Rostislav Vasilikhin
8b7e586faa Merge pull request #22598 from savuor:icp_oframe_readonly
Complement PR: #3366@contrib
Changes

    OdometryFrame losts its getters: a user can provide data at construction stage only, pyramids and other generated data is read-only now
    OdometryFrame is based on UMats: no TMat templates inside, CPU operations are done with UMat::getMat() method, chaining issues are solved ad-hoc
    No more Odometry::createOdometryFrame() method, frames are compatible with all odometry algorithms
    Normals computer is cached inside Odometry and exposed to API as well as its settings
    Volume::raycast() won't return the result in OdometryFrame anymore
    Added test for Odometry::prepareFrame*() & other test fixes
    Minor code improvements

TODOs:

    fix TODOs in code
    lower acceptable accuracy errors
2022-10-24 16:34:01 +03:00
Alexander Smorkalov
8358efaca1 Merge pull request #22655 from asenyaev:asen/cuda_trigger_5.x
Trigger on dnn (onnx) label (5.x)
2022-10-18 10:30:17 +03:00
Andrey Senyaev
3aaa9251e9 Trigger on dnn (onnx) label (5.x) 2022-10-18 09:03:27 +03:00
Alexander Smorkalov
6c2eba2877 Merge pull request #22630 from asenyaev:asen/cuda_pipeline_5.x
Workflow Ubuntu 20.04 x64 with CUDA support (5.x)
2022-10-13 12:18:35 +03:00
Andrey Senyaev
67be6a334f Workflow Ubuntu 20.04 x64 with CUDA support (5.x) 2022-10-12 14:42:40 +03:00
Alexander Smorkalov
5b97f6abec Merge pull request #22136 from sturkmen72:HOGDescriptor_update
HOGDescriptor
2022-10-07 15:17:57 +03:00
Suleyman TURKMEN
07b62376af Update objdetect.hpp 2022-10-06 23:13:44 +03:00
Alexander Smorkalov
3857173845 Merge pull request #22287 from asenyaev:asen/disabled_compiling_warnings_5.x
Disabled compiling warnings in case of symbols in cmake for 5.x
2022-09-20 16:19:08 +03:00
Andrey Senyaev
752e5fdc26 Disabled compiling warnings in case of symbols in cmake for 5.x 2022-09-20 13:36:59 +03:00
Alexander Smorkalov
520bf4697e Merge pull request #22524 from savuor:calib_refactor_msvc_fix
Fix MSVC15 compilation
2022-09-19 08:30:16 +03:00
Rostislav Vasilikhin
f92a1aa07d trying to fix MSVC compilation
double -> float warning

fix warnings in the rest 3d module files

extra var removed

try to fix warnings
2022-09-19 00:27:26 +02:00
Alexander Smorkalov
44d6872837 Merge pull request #22499 from savuor:calib_ptrs_refactor
Calibration internals refactored
2022-09-16 07:41:06 +03:00
Rostislav Vasilikhin
9ba4bb7355 initIntrisicParams2D() refactored
variables refactoring

levmarq fix

initIntrinsicParams2D() refactoring

undo LM fix

cameraCalcJErr: made a lambda; warnings fixed; vars rearranged & renamed, jacobian buffers, perViewErrors and allErrors fix, etc.

stereoCalibrate: internal vars in callback

stereoCalibrate: capture only useful variables

stereoCalibrate: perViewError fix + minors

rvecs and tvecs are not pointers anymore

no extra lambda

newObjPoints: no pointers

stdDevs: no pointers

_Jo removed: not used

Range::all() -> rowRange, colRange

param and mask are std::vectors now

indices shortened

tabs

less func-scoped vars; TODOs

less formatting & renaming changes

trailing whitespaces

less diff

less changes

less changes

Range::all() back

perViewErr ptr fix

NINTRINSIC captured

try to fix warning

trying to fix a warning

fix warnings, another attempt
2022-09-15 22:55:40 +02:00
Alexander Smorkalov
f199cf91f3 Merge pull request #22491 from savuor:calib_perview_fix
Calibration per view error fixed
2022-09-10 09:27:04 +03:00
Rostislav Vasilikhin
b1020639f1 perViewErr fix 2022-09-09 17:40:26 +02:00
Alexander Smorkalov
8bfb419b0f Merge pull request #22460 from savuor:levmarq_stereocalib_fix
Stereo calibration fixed when intrinsic guess is given
2022-09-06 11:33:34 +03:00
Rostislav Vasilikhin
a8b4ffac50 volatile variable made mask-fixed as it should be 2022-09-05 18:42:17 +02:00
Rostislav Vasilikhin
8a43956a1b less pointers
rtsort + formatting

less pointers + more compact code

less reallocations, cleaner code

less pointers, less GEMMs

trailing whitespace
2022-09-05 18:42:15 +02:00
Rostislav Vasilikhin
bfc4bdd9d0 regression test added
test data moved to opencv_extra, loads from yaml.gz file now
2022-09-05 18:42:12 +02:00
Rostislav Vasilikhin
96e2d32618 fixing broken stereo calibration 2022-09-05 18:42:12 +02:00
Rostislav Vasilikhin
487619e5fe no address arithmetics
less address arithmetics

happy valgrind: copy recomputed intrinsics only
2022-09-05 18:42:09 +02:00
Alexander Smorkalov
335d7bd16e Merge pull request #22241 from savuor:normals_scale_test
More tests for normals
2022-08-24 10:25:55 +03:00
Alexander Smorkalov
3a02561c40 Merge pull request #22417 from savuor:levmarq_log_level_fix 2022-08-24 07:17:22 +00:00
Rostislav Vasilikhin
eb571b500b fixes warnings 2022-08-23 10:22:28 +02:00
Alexander Smorkalov
505bbab75b Merge pull request #22413 from savuor:levmarq_log_level
LevMarq: log level lowered
2022-08-23 09:22:39 +03:00
Rostislav Vasilikhin
3cf3e3f6f7 LevMarq: log level lowered 2022-08-22 23:53:49 +02:00
Rostislav Vasilikhin
232a83ecb8 check mask values 2022-08-22 16:07:07 +02:00
Alexander Alekhin
c25f776151 Merge branch 4.x 2022-08-21 15:27:31 +00:00
Rostislav Vasilikhin
48c10620cb depthTo3d: fixed bug, added regression test
RgbdNormals: setMethod() removed as useless

RgbdNormals: tests + cross product, to be fixed

+ cross product

LINEMOD: diffThreshold param added + tests fixed

minor

diffThreshold fix

points3dToDepth16U fix

normals computer diffThreshold fix

random plane generation fixed + diffThreshold fix

Rendered normals test rewritten to GTest Params

random plane generation: scale

RGBD_Normals tests: thresholds tuned

Rendered normals tests: 64F support added

Random planes normal tests rewritten to GTest Params

LINEMOD and CrossProduct fix

SRI threshold raised

NormalsRandomPlanes: thresholds raised

assert on unknown alg; minor

fix

frame size reduced

TIFF replaced by YAML.GZ

depthTo3d test changed

cv::transform is used

fix warning

nanMask()

flipAxes()

absDotPixel() + forgotten code

helper functions removed

RGBDNormals: checkNormals() and compare LINEMOD's pts3d to depth input

Rendered: another criteria; thresholds; LINEMOD's pts3d to depth input comparison

thresholds raised a bit

SRI slightly optimized

assert change

normal tests refactored, parametrized, split

trailing namespace, thresholds raised

SRI caching optimized a lot

normal tests rewritten to fixture, no loop

minor

runCase() joined with testIt()

thresholds were put into GTest params

ternary operator

RgbdNormalsTest merged into NormalsRandomPlanes; RgbdPlanes moved closer to tests

normal test minor refactoring

plane finder tests refactored to GTest Params

skip tests

thresholds raised

plane test minor

plane tests: timers dropped, nPlanes put into GTest Params; refactoring

generated normals tests: minor refactoring

flipAxes() templated

rendered normals tests refactored: thresholds to GTest Params

CV_Error -> ASSERT_FALSE
2022-08-19 20:16:08 +02:00
Alexander Smorkalov
99d216c8d4 Merge pull request #22150 from savuor:warpFrameTests
warpFrame() fixed & covered by tests
2022-08-03 12:27:19 +03:00
Alexander Smorkalov
a2593a392f Merge pull request #22319 from asenyaev:asen/docs_5.x 2022-08-02 06:25:40 +00:00
Andrey Senyaev
4c1f9fb042 Docs workflow in GHA for 5.x 2022-07-28 17:47:03 +03:00
Rostislav Vasilikhin
869123d6f9 "FAIL() <<" replaced by "ASSERT_*() <<" 2022-07-24 18:40:55 +02:00
Rostislav Vasilikhin
02d864070a minor 2022-07-24 18:29:34 +02:00
Rostislav Vasilikhin
0b34d90dfa minor 2022-07-24 18:28:26 +02:00
Rostislav Vasilikhin
7bdacb8098 threshold comparison made more obvious 2022-07-24 18:27:35 +02:00
Rostislav Vasilikhin
d4e28f27b7 warpFrame test parametrized 2022-07-24 18:22:48 +02:00
Alexander Alekhin
638a0788fe Merge pull request #22281 from asenyaev:asen/android_5.x 2022-07-22 09:58:56 +00:00
Andrey Senyaev
7ea095cc38 Android GHA workflow for 5.x branch 2022-07-21 17:59:31 +03:00
Alexander Alekhin
d2603cbf94 Merge pull request #22268 from asenyaev:asen/rename_lin_arm_pipelines_5.x 2022-07-19 14:25:07 +00:00
Andrey Senyaev
c2ab4c052d Linux ARM64 rename ubuntu version on 5.x 2022-07-19 13:14:09 +03:00
Yuantao Feng
8d38922571 Merge pull request #22187 from fengyuentau:ci_job_rename_5.x
Rename jobs for better understanding for branch 5.x

* rename jobs

* remove dots from job names

* correct ubuntu version for linux arm64
2022-07-05 01:46:49 +03:00
Alexander Alekhin
ee8b414a1e Merge pull request #22112 from asenyaev:asen/ios_workflow_5.x 2022-07-01 10:06:42 +00:00
Rostislav Vasilikhin
75a8e3e956 minor 2022-06-30 21:32:41 +02:00
Rostislav Vasilikhin
3c3eba868a floatL2 threshold raised a bit 2022-06-30 17:22:58 +02:00
Rostislav Vasilikhin
2ae7438c6b odometry tests fixed 2022-06-30 17:10:26 +02:00
Rostislav Vasilikhin
2b767f9bc8 whitespace fix 2022-06-30 16:51:01 +02:00
Andrey Senyaev
9c78dc2490 Workflow for labeled iOS PRs in 5.x branch 2022-06-30 11:27:53 +03:00
Rostislav Vasilikhin
94e5ae6043 depth generator moved from main repo to extra 2022-06-30 00:00:47 +02:00
Rostislav Vasilikhin
fd14b959cf warpFrame() rewritten, interface changed 2022-06-29 23:55:07 +02:00
Rostislav Vasilikhin
492d9dba1e warpFrame() tests big update 2022-06-29 23:51:07 +02:00
Rostislav Vasilikhin
44c0b58258 depth generator fixed at absent values 2022-06-29 23:45:33 +02:00
Rostislav Vasilikhin
6b2d1033bd warpFrame() test: more test cases 2022-06-27 01:24:39 +02:00
Rostislav Vasilikhin
162bd5be4c distCoeffs removed from warpFrame() signature 2022-06-27 01:23:07 +02:00
Rostislav Vasilikhin
d56e8f053f python depth generator: no numba, imageio -> PIL, requirements.txt 2022-06-26 22:33:31 +02:00
Rostislav Vasilikhin
bf8f7b4e57 more scale stuff removed 2022-06-23 23:53:57 +02:00
Rostislav Vasilikhin
4e1ce3e0eb odometry python sample got rid of scale parameter 2022-06-23 23:51:16 +02:00
Rostislav Vasilikhin
770c0d1416 1. removed (almost all) additional scale parameter mentions
2. refactored funcptrs to switch/cases & more
2022-06-23 23:47:08 +02:00
Rostislav Vasilikhin
c12d4c82df python Odometry scale test removed 2022-06-23 23:25:30 +02:00
Rostislav Vasilikhin
bee410c748 warpFrame() test draft + script generating test data 2022-06-23 23:18:59 +02:00
Alexander Alekhin
83cfeb9f14 Merge pull request #22105 from fengyuentau:macOS_workflows_for_5.x 2022-06-15 07:57:00 +00:00
fengyuentau
66fee4a8d2 add workflows for macOS for 5.x 2022-06-15 11:06:52 +08:00
Saratovtsev
df490c6399 moving code from ICP+Scale 2022-06-14 13:40:14 +02:00
Wanli Zhong
b06544bd54 Merge pull request #21918 from No-Plane-Cannot-Be-Detected:5.x-region_growing_3d
Add normal estimation and region growing algorithm for point cloud

* Add normal estimation and region growing algorithm for point cloud

* 1.Modified documentation for normal estimation;2.Converted curvature in region growing to absolute values;3.Changed the data type of threshold from float to double;4.Fixed some bugs;

* Finished documentation

* Add tests for normal estimation. Test the normal and curvature of each point in the plane and sphere of the point cloud.

* Fix some warnings caused by to small numbers in test

* Change the test to calculate the average difference instead of comparing each normal and curvature

* Fixed the bugs found by testing

* Redesigned the interface and fixed problems:
1. Make the interface compatible with radius search.
2. Make region growing optionally sortable on results.
3. Modified the region growing interface.
4. Format reference.
5. Removed sphere test.

* Fix warnings

* Remove flann dependency

* Move the flann dependency to the corresponding test
2022-05-23 14:47:57 +00:00
Alexander Alekhin
6e9ab70359 Merge pull request #22014 from asenyaev:asen/move_workflows_5.x 2022-05-22 13:43:03 +00:00
Andrey Senyaev
2f65a1b501 Move workflows to a dedicated repository for 5.x branch 2022-05-20 19:46:37 +03:00
Alexander Alekhin
8b3d2a57ad Merge pull request #21968 from No-Plane-Cannot-Be-Detected:5.x-randomSampling_bug 2022-05-17 21:17:29 +00:00
Klepikov Dmitrii
a99b4071a2 Merge pull request #20471 from ibvfteh:pointcloudio
GSoC module to save and load point cloud

* Add functionality to read point cloud data from files

* address issues found on review, add tests for mesh, refactor

* enable fail-safe execution and empty arrays as output

* Some improvements for point cloud io module

Co-authored-by: Julie Bareeva <julia.bareeva@xperience.ai>
2022-05-13 18:10:39 +00:00
Wanli Zhong
627e6a0447 Modify randomSampling in point cloud 2022-05-11 15:30:58 +08:00
OpenCV Pushbot
6bffbe4938 Merge pull request #21908 from cpoerschke:issue-21459-alternative 2022-04-27 17:27:57 +00:00
OpenCV Pushbot
d5c45116cd Merge pull request #21877 from asenyaev:asen/workflow_only_linux_5x
Added workflow for Github Actions to build and test OpenCV on Linux for 5.x
2022-04-26 05:10:59 +00:00
Andrey Senyaev
c4c47d91e4 Added workflow for Github Actions to build and test OpenCV
Merged a build and tests jobs into one, split tests by steps, renamed job names
2022-04-26 00:11:59 +03:00
Christine Poerschke
08c268bfc5 remove Imgproc_cvWarpAffine.regression test 2022-04-24 21:32:44 +01:00
OpenCV Developers
0fbd58bef9 Merge branch 4.x 2022-04-23 22:07:14 +00:00
Artem Saratovtsev
3d12581798 Merge pull request #21741 from DumDereDum:odometry_prepareFrame_fix
Odometry prepareFrame fix

* fix issue; add tests

* img fix

* mask fix

* minor fix
2022-04-04 21:14:31 +00:00
Rostislav Vasilikhin
aa5055261f Merge pull request #21652 from savuor:fix/hash_tsdf_normals_simd32_compilation
Fix HashTSDF compilation

* big SIMD compilation fix (try 1)

* fixing compilation, try 2
2022-02-24 10:29:28 +00:00
Alexander Alekhin
899b4d1452 Merge branch 4.x 2022-02-22 19:55:26 +00:00
Ruan
e5d648d2d0 Merge pull request #21615 from No-Plane-Cannot-Be-Detected:5.x-ptcloud_comments
Added 3D point cloud code comments and copyright

1. update the code comments.
2. add author information.
2022-02-18 20:43:08 +03:00
Artem Saratovtsev
9c87d8bf9c Merge pull request #21189 from DumDereDum:new_volume
New Volume pipeline
2022-02-18 14:50:26 +00:00
Artem Saratovtsev
4ba2b05df8 Merge pull request #21439 from DumDereDum:python_odometry
Odometry python support
2022-02-07 16:16:17 +00:00
Pavel Rojtberg
0a0714bd1b Merge pull request #21065 from paroj:dawsome
docs: use doxygen-awesome theme

* docs: use doxygen-awesome theme

* docs: drop dark color-scheme from doxygen theme

* doxygen: fix mobile view size
2022-01-21 20:49:22 +00:00
Alexander Alekhin
2c2d7774b9 copyright: 2022 2022-01-04 12:49:47 +00:00
Alexander Alekhin
a0d5277e0d Merge branch 4.x 2021-12-30 21:43:45 +00:00
Ruan
80c5d18f9c Merge pull request #21276 from No-Plane-Cannot-Be-Detected:5.x-ptcloud
Add support for 3D point cloud segmentation, using the USAC framework.

* Modify the RANSAC framework in usac such that RANSAC can be used in 3D point cloud segmentation.

* 1. Add support for 3D point cloud segmentation, using the USAC framework.
2. Add solvers, error estimators for plane model and sphere model.

* Added code samples to the comments of class SACSegmentation.

* 1. Update the segment interface parameters of SACSegmentation.
2. Fix some errors in variable naming.

* Add tests for plane detection.

* 1. Add tests for sphere segmentation.
2. Fix some bugs found by tests.
3. Rename "segmentation" to "sac segmentation".
4. Rename "detect" to "segment".
TODO: Too much duplicate code, the structure of the test needs to be rebuilt.

* 1. Use SIMD acceleration for plane model and sphere model error estimation.
2. Optimize the RansacQualityImpl#getScore function to avoid multiple calls to the error#getError function.
3. Fix a warning in test_sac_segmentation.cpp.

* 1. Fix the warning of ModelConstraintFunction ambiguity.
2. Fix warning: no previous declaration for'void cv::usac::modelParamsToUsacConfig(cv::Ptr<cv::usac::SimpleUsacConfig>&, const cv::Ptr<const cv::usac::Model>& )

* Fix a warning in test_sac_segmentation.cpp about direct comparison of different types of data.

* Add code comments related to the interpretation of model coefficients.

* Update the use of custom model constraint functions.

* Simplified test code structure.

* Update the method of checking plane models.

* Delete test for cylinder.

* Add some comments about UniversalRANSAC.

* 1. The RANSAC paper in the code comments is referenced using the bibtex format.
2. The sample code in the code comments is replaced using @snippet.
3. Change the public API class SACSegmentation to interface.
4. Clean up the old useless code.

* fix warning(no previous declaration) in 3d_sac_segmentation.cpp.

* Fix compilation errors caused by 3d_sac_segmentation.cpp.

* Move the function sacModelMinimumSampleSize() from ptcloud.hpp to sac_segmentation.cpp.

* 1. Change the interface for setting the number of threads to the interface for setting whether to be parallel.
2. Move interface implementation code in ptcloud_utils.hpp to ptcloud_utils.cpp.

* SACSegmentation no longer inherits Algorithm.

* Add the constructor and destructor of SACSegmentation.

* 1. For the declaration of the common API, the prefix and suffix of the parameter names no longer contain underscores.
2. Rename the function _getMatFromInputArray -> getPointsMatFromInputArray.
3. Change part of CV_CheckDepth to CV_CheckDepthEQ.
4. Remove the doxygen flag from the source code.
5. Update the loop termination condition of SIMD in the point cloud section of 3D module.

* fix warning: passing 'bool' chooses 'int' over 'size_t {aka unsigned int}' .

* fix warning: passing 'bool' chooses 'int' over 'size_t {aka unsigned int}' .
2021-12-30 15:54:06 +00:00
Alexander Alekhin
7d05f92855 Merge pull request #21334 from catree:solvePnP_doc_page_5.x 2021-12-28 17:59:05 +00:00
Rostislav Vasilikhin
9d6f388809 Merge pull request #21018 from savuor:levmarqfromscratch
New LevMarq implementation

* Hash TSDF fix: apply volume pose when fetching pose

* DualQuat minor fix

* Pose Graph: getEdgePose(), getEdgeInfo()

* debugging code for pose graph

* add edge to submap

* pose averaging: DualQuats instead of matrix averaging

* overlapping ratio: rise it up; minor comment

* remove `Submap::addEdgeToSubmap`

* test_pose_graph: minor

* SparseBlockMatrix: support 1xN as well as Nx1 for residual vector

* small changes to old LMSolver

* new LevMarq impl

* Pose Graph rewritten to use new impl

* solvePnP(), findHomography() and findExtrinsicCameraParams2() use new impl

* estimateAffine...2D() use new impl

* calibration and stereo calibration use new impl

* BundleAdjusterBase::estimate() uses new impl

* new LevMarq interface

* PoseGraph: changing opt interface

* findExtrinsicCameraParams2(): opt interface updated

* HomographyRefine: opt interface updated

* solvePnPRefine opt interface fixed

* Affine2DRefine opt interface fixed

* BundleAdjuster::estimate() opt interface fixed

* calibration: opt interface fixed + code refactored a little

* minor warning fixes

* geodesic acceleration, Impl -> Backend rename

* calcFunc() always uses probe vars

* solveDecomposed, fixing negation

* fixing geodesic acceleration + minors

* PoseGraph exposes its optimizer now + its tests updated to check better convegence

* Rosenbrock test added for LevMarq

* LevMarq params upgraded

* Rosenbrock can do better

* fixing stereo calibration

* old implementation removed (as well as debug code)

* more debugging code removed

* fix warnings

* fixing warnings

* fixing Eigen dependency

* trying to fix Eigen deps

* debugging code for submat is now temporary

* trying to fix Eigen dependency

* relax sanity check for solvePnP

* relaxing sanity check even more

* trying to fix Eigen dependency

* warning fix

* Quat<T>: fixing warnings

* more warning fixes

* fixed warning

* fixing *KinFu OCL tests

* algo params -> struct Settings

* Backend moved to details

* BaseLevMarq -> LevMarqBase

* detail/pose_graph.hpp -> detail/optimizer.hpp

* fixing include stuff for details/optimizer.hpp

* doc fix

* LevMarqBase rework: Settings, pImpl, Backend

* Impl::settings and ::backend fix

* HashTSDFGPU fix

* fixing compilation

* warning fix for OdometryFrameImplTMat

* docs fix + compile warnings

* remake: new class LevMarq with pImpl and enums, LevMarqBase => detail, no Backend class, Settings() => .cpp, Settings==() removed, Settings.set...() inlines

* fixing warnings & whitespace
2021-12-27 21:51:32 +00:00
catree
9c61d80bc4 Summarize PnP pose computation on a single separate page. 2021-12-23 19:43:27 +01:00
Alexander Alekhin
4d9365990a Merge pull request #21272 from DumDereDum:new_odometry_fix1 2021-12-16 12:49:30 +00:00
Saratovtsev
5714868726 odometry warnings fix 2021-12-16 13:52:00 +03:00
Alexander Alekhin
196e6aaa50 Merge pull request #21201 from Baiyun-u-smartAI:patch-1 2021-12-10 11:40:16 +00:00
Baiyun-u-smartAI
b167115b5b fixed an error ------Context::p is protected whinin this context 2021-12-06 14:09:50 +08:00
Alexander Alekhin
5d04e5b063 Merge pull request #21089 from sturkmen72:clean-up-c-api 2021-12-03 15:11:59 +00:00
Artem Saratovtsev
6ab4659840 Merge pull request #20755 from DumDereDum:new_odometry
New odometry Pipeline

* first intergation

* tests run, but not pass

* add previous version of sigma calc

* add minor comment

* strange fixes

* fix fast ICP

* test changes; fast icp still not work correctly

* finaly, it works

* algtype fix

* change affine comparison

* boolean return

* fix bug with angle and cos

* test pass correctly

* fix for kinfu pipeline

* add compute points normals

* update for new odometry

* change odometry_evaluation

* odometry_evaluation works

* change debug logs

* minor changes

* change depth setting in odometryFrame

* fastICP works with 4num points

* all odometries work with 4mun points

* odometry full works on 4num points and normals

* replace ICP with DEPTH; comments replacements

* create prepareFrame; add docs for Odometry

* change getPyramids()

* delete extra code

* add intrinsics; but dont works

* bugfix with nan checking

* add gpu impl

* change createOdometryFrame func

* remove old fastICP code

* comments fix

* add comments

* minor fixes

* other minor fixes

* add channels assert

* add impl for odometry settings

* add pimpl to odometry

* linux warning fix

* linux warning fix 1

* linux warning fix 2

* linux error fix

* linux warning fix 3

* linux warning fix 4

* linux error fix 2

* fix test warnings

* python build fix

* doxygen fix

* docs fix

* change normal tests for 4channel point

* all Normal tests pass

* plane works

* add warp frame body

* minor fix

* warning fixes

* try to fix

* try to fix 1

* review fix

* lvls fix

* createOdometryFrame fix

* add comment

* const reference

* OPENCV_3D_ prefix

* const methods

* –OdometryFramePyramidType ifx

* add assert

* precomp moved upper

* delete types_c

* add assert for get and set functions

* minor fixes

* remove core.hpp from header

* ocl_run add

* warning fix

* delete extra comment

* minor fix

* setDepth fix

* delete underscore

* odometry settings fix

* show debug image fix

* build error fix

* other minor fix

* add const to signatures

* fix

* conflict fix

* getter fix
2021-12-02 20:53:44 +03:00
Ruan
0cf0a5e9d4 Merge pull request #21095 from No-Plane-Cannot-Be-Detected:next_SIMD
Accelerated 3D point cloud Farthest Point Sampling calculation using SIMD.

* Add several 3D point cloud sampling functions: Random, VoxelGrid, FarthestPoint.

* Made some code detail changes and exposed the random number generator parameters at the interface.

* Add simple tests for sampling.

* Modify interface output parameters.

* Modify interface return value.

* The sampling test is modified for the new changes of function interface.

* Improved test of VoxelGridFilterSampling

* Improved test of VoxelGridFilterSampling and FPS.

* Add test for the dist_lower_limit arguments of FPS function.

* Optimization function _getMatFromInputArray.

* Optimize the code style and some details according to the suggestions.

* Clear prefix cv: in the source code.

* Change the initialization of Mat in the sampling test.

* 1. Unified code style
2. Optimize randomSampling method

* 1. Optimize code comments.
2. Remove unused local variables.

* Rebuild the structure of the test, make the test case more reliable, and change the code style.

* Update test_sampling.cpp

Fix a warning.

* Use SIMD to optimize the farthest point sampling.

* Optimize the farthest point sampling SIMD code.

* 1. remove `\n` from the ptcloud.hpp comment.
2. updated the default value of the argument arrangement_of_points in the _getMatFromInputArray function in ptcloud_utils.hpp from 0 to 1, since the latter is more commonly used (such arrangement is easier for SIMD acceleration).
3. removed two functions in ptcloud_utils.hpp that were not used.

* Remove the <br> in the comment.

* Fix whitespace issues.
2021-11-30 12:33:44 +00:00
Suleyman TURKMEN
4f0fe1de96 clean up c-api 2021-11-28 12:09:34 +03:00
Ruan
1470f90c2a Merge pull request #20784 from No-Plane-Cannot-Be-Detected:next
Add 3D point cloud sampling functions to branch next

* Add several 3D point cloud sampling functions: Random, VoxelGrid, FarthestPoint.

* Made some code detail changes and exposed the random number generator parameters at the interface.

* Add simple tests for sampling.

* Modify interface output parameters.

* Modify interface return value.

* The sampling test is modified for the new changes of function interface.

* Improved test of VoxelGridFilterSampling

* Improved test of VoxelGridFilterSampling and FPS.

* Add test for the dist_lower_limit arguments of FPS function.

* Optimization function _getMatFromInputArray.

* Optimize the code style and some details according to the suggestions.

* Clear prefix cv: in the source code.

* Change the initialization of Mat in the sampling test.

* 1. Unified code style
2. Optimize randomSampling method

* 1. Optimize code comments.
2. Remove unused local variables.

* Rebuild the structure of the test, make the test case more reliable, and change the code style.

* Update test_sampling.cpp

Fix a warning.
2021-10-29 01:41:21 +03:00
Alexander Alekhin
6544c7b787 Merge pull request #20887 from alalek:5.x_cleanup_compatibility 2021-10-22 21:38:09 +00:00
Alexander Alekhin
fce4a19d0d 5.x: cleanup compatibility code (2021-10) 2021-10-20 17:40:04 +00:00
Alexander Alekhin
7ba26ada12 Merge branch 4.x 2021-10-15 21:53:39 +00:00
Alexander Alekhin
91a7a4523a Merge pull request #20861 from alalek:fix_abi_compatibility_5.x 2021-10-12 15:33:30 +00:00
Alexander Alekhin
8c7dc1f6b7 core: OPENCV_ABI_COMPATIBILITY=500 2021-10-12 12:07:12 +03:00
Alexander Alekhin
14dedda023 Merge pull request #20608 from zihaomu:loop_closure_detection_submap 2021-08-30 18:11:30 +00:00
Zihao Mu
19116471fe submap for loop closure detection in 3d 2021-08-26 11:26:12 +08:00
Rostislav Vasilikhin
bae9cef0b5 Merge pull request #20013 from savuor:rgbd_to_3d
Moving RGBD parts to 3d

* files moved from rgbd module in contrib repo

* header paths fixed

* perf file added

* lapack compilation fixed

* Rodrigues fixed in tests

* rgbd namespace removed

* headers fixed

* initial: rgbd files moved to 3d module

* rgbd updated from latest contrib master; less file duplication

* "std::" for sin(), cos(), etc.

* KinFu family -> back to contrib

* paths & namespaces

* removed duplicates, file version updated

* namespace kinfu removed from 3d module

* forgot to move test_colored_kinfu.cpp to contrib

* tests fixed: Params removed

* kinfu namespace removed

* it works without objc bindings

* include headers fixed

* tests: data paths fixed

* headers moved to/from public API

* Intr -> Matx33f in public API

* from kinfu_frame.hpp to utils.hpp

* submap: Intr -> Matx33f, HashTSDFVolume -> Volume; no extra headers

* no RgbdFrame class, no Mat fields & arg -> InputArray & pImpl

* get/setPyramidAt() instead of lots of methods

* Mat -> InputArray, TMat

* prepareFrameCache: refactored

* FastICPOdometry: +truncate threshold, +depthFactor; Mat/UMat choose

* Mat/UMat choose

* minor stuff related to headers

* (un)signed int warnings; compilation minor issues

* minors: submap: pyramids -> OdometryFrame; tests fix; FastICP minor; CV_EXPORTS_W for kinfu_frame.hpp

* FastICPOdometry: caching, rgbCameraMatrix

* OdometryFrame: pyramid%s% -> pyramids[]

* drop: rgbCameraMatrix from FastICP, RGB cache mode, makeColoredFrameFrom depth and all color-functions it calls

* makeFrameFromDepth, buildPyramidPointsNormals -> from public to internal utils.hpp

* minors

* FastICPOdometry: caching updated, init fields

* OdometryFrameImpl<UMat> fixed

* matrix building fixed; minors

* returning linemode back to contrib

* params.pose is Mat now

* precomp headers reorganized

* minor fixes, header paths, extra header removed

* minors: intrinsics -> utils.hpp; whitespaces; empty namespace; warning fixed

* moving declarations from/to headers

* internal headers reorganized (once again)

* fix include

* extra var fix

* fix include, fix (un)singed warning

* calibration.cpp: reverting back

* headers fix

* workaround to fix bindings

* temporary removed wrappers

* VolumeType -> VolumeParams

* (temporarily) removing wrappers for Volume and VolumeParams

* pyopencv_linemod -> contrib

* try to fix test_rgbd.py

* headers fixed

* fixing wrappers for rgbd

* fixing docs

* fixing rgbdPlane

* RgbdNormals wrapped

* wrap Volume and VolumeParams, VolumeType from enum to int

* DepthCleaner wrapped

* header folder "rgbd" -> "3d"

* fixing header path

* VolumeParams referenced by Ptr to support Python wrappers

* render...() fixed

* Ptr<VolumeParams> fixed

* makeVolume(... resolution -> [X, Y, Z])

* fixing static declaration

* try to fix ios objc bindings

* OdometryFrame::release...() removed

* fix for Odometry algos not supporting UMats: prepareFrameCache<>()

* preparePyramidMask(): fix to compile with TMat = UMat

* fixing debug guards

* removing references back; adding makeOdometryFrame() instead

* fixing OpenCL ICP hanging (some threads exit before reaching the barrier -> the rest threads hang)

* try to fix objc wrapper warnings; rerun builders

* VolumeType -> VolumeKind

* try to fix OCL bug

* prints removed

* indentation fixed

* headers fixed

* license fix

* WillowGarage licence notion removed, since it's in OpenCV's COPYRIGHT already

* KinFu license notion shortened

* debugging code removed

* include guards fixed

* KinFu license left in contrib module

* isValidDepth() moved to private header

* indentation fix

* indentation fix in src files

* RgbdNormals rewritten to pImpl

* minor

* DepthCleaner removed due to low code quality, no depthScale provided, no depth images found to be successfully filtered; can be replaced by bilateral filtering

* minors, indentation

* no "private" in public headers

* depthTo3d test moved from separate file

* Normals: setDepth() is useless, removing it

* RgbdPlane => findPlanes()

* rescaleDepth(): minor

* warpFrame: minor

* minor TODO

* all Odometries (except base abstract class) rewritten to pImpl

* FastICPOdometry now supports maxRotation and maxTranslation

* minor

* Odometry's children: now checks are done in setters

* get rid of protected members in Odometry class

* get/set cameraMatrix, transformType, maxRot/Trans, iters, minGradients -> OdometryImpl

* cameraMatrix: from double to float

* matrix exponentiation: Eigen -> dual quaternions

* Odometry evaluation fixed to reuse existing code

* "small" macro fixed by undef

* pixNorm is calculated on CPU only now (and then uploads on GPU)

* test registration: no cvtest classes

* test RgbdNormals and findPlanes(): no cvtest classes

* test_rgbd.py: minor fix

* tests for Odometry: no cvtest classes; UMat tests; logging fixed

* more CV_OVERRIDE to overriden functions

* fixing nondependent names to dependent

* more to prev commit

* forgotten fixes: overriden functions, (non)dependent names

* FastICPOdometry: fix UMat support when OpenCL is off

* try to fix compilation: missing namespaces

* Odometry: static const-mimicking functions to internal constants

* forgotten change to prev commit

* more forgotten fixes

* do not expose "submap.hpp" by default

* in-class enums: give names, CamelCase, int=>enums; minors

* namespaces, underscores, String

* std::map is used by pose graph, adding it

* compute()'s signature fixed, computeImpl()'s too

* RgbdNormals: Mat -> InputArray

* depth.hpp: Mat -> InputArray

* cameraMatrix: Matx33f -> InputArray + default value + checks

* "details" headers are not visible by default

* TSDF tests: rearranging checks

* cameraMatrix: no (realistic) default value

* renderPointsNormals*(): no wrappers for them

* debug: assert on empty frame in TSDF tests

* debugging code for TSDF GPU

* debug from integrate to raycast

* no (non-zero) default camera matrix anymore

* drop debugging code (does not help)

* try to fix TSDF GPU: constant -> global const ptr
2021-08-22 13:18:45 +00:00
Alexander Alekhin
6b199bd1bb Merge pull request #20317 from sturkmen72:upd_fast_agast 2021-07-09 08:59:15 +00:00
Suleyman TURKMEN
ee893a08ef Update features2d.hpp, agast.cpp, fast.cpp 2021-07-07 16:17:11 +03:00
Alexander Alekhin
7a5f554bc4 Merge branch 4.x 2021-06-13 10:27:44 +00:00
Vadim Pisarevsky
4dc811946d Merge pull request #19684 from zihaomu:octree_in_3d 2021-06-08 13:23:11 +00:00
zihaomu
5c0ac37163 add Octree to 3d module of next branch. 2021-06-08 11:19:01 +08:00
Vadim Pisarevsky
958d3e8c60 Merge pull request #20225 from vpisarev:remove_c_3d 2021-06-07 16:55:15 +00:00
Vadim Pisarevsky
eff6d32337 * refactored the remaining old-style functions in 3d and calib modules to use the new C++ API.
* extended C++ version of Levenberg-Marquardt (LM) solver to accommodate all features of the C counterpart.
* removed C version of LM solver
* made a few other little changes to make the code compile and run smoothly
2021-06-07 20:55:25 +08:00
Alexander Alekhin
b91e0dca90 Merge branch 4.x 2021-06-04 15:18:51 +00:00
Alexander Alekhin
b754406352 Merge pull request #20170 from danielenricocahall:fix-mser-grayscale-min-diversity 2021-05-29 14:44:59 +00:00
danielenricocahall
fa73b91e39 add logic for handling min diversity in mser 2021-05-27 19:16:24 -04:00
Alexander Alekhin
c105402dfc Merge pull request #19856 from danielenricocahall:remove-freatures2d-virtual-inheritance 2021-04-12 12:31:56 +00:00
Alexander Alekhin
fc628014bb Merge branch 4.x 2021-04-10 18:03:01 +00:00
danielenricocahall
4e691587ef remove virtual inheritance from features2d 2021-04-08 20:09:13 -04:00
Alexander Alekhin
263de1f86e Merge pull request #19595 from sturkmen72:patch-3 2021-03-05 15:01:51 +00:00
Suleyman TURKMEN
703dea4817 Clean up C API 2021-03-04 03:23:17 +03:00
Suleyman TURKMEN
178240ccf1 Clean up C API backport ready changes 2021-03-03 14:37:45 +03:00
Alexander Alekhin
c073e09956 copyright: 2021 2021-01-01 13:42:20 +00:00
Vadim Pisarevsky
71be47e04a Merge pull request #19156 from vpisarev:named_args1 2020-12-18 17:35:19 +00:00
Vadim Pisarevsky
ed8696566b * updated python wrapper generator to properly handle C++20-style named parameters
* added sample filter2D[p]() function and a little python test for it to demonstrate the concept
2020-12-18 20:00:42 +08:00
Alexander Alekhin
9668831c13 Merge pull request #19036 from asmorkalov:as/fix_js_next_issue_19017 2020-12-08 13:09:20 +03:00
Alexander Alekhin
89e059d8ac apple/build_xcframework.py: python syntax
- make happy old Python linters

(cherry picked from commit 77b986c7a1)
2020-12-08 10:55:59 +03:00
Alexander Smorkalov
6d06368760 Updated modules white list for JS after calib3d reorg. 2020-12-07 16:21:53 +03:00
Vadim Pisarevsky
65b0383059 Merge pull request #18940 from vpisarev:3d_light 2020-12-01 21:36:48 +00:00
Vadim Pisarevsky
d6c699c014 calib3d module in opencv is split into 3 modules: 3d, calib and stereo.
stereo module in opencv_contrib is renamed to xstereo
2020-12-01 23:42:15 +03:00
Alexander Alekhin
9d2eabaaa2 Merge remote-tracking branch 'upstream/master' into merge-4.x 2020-11-27 18:15:28 +00:00
Vadim Pisarevsky
3268cc46ba Merge pull request #18760 from vpisarev:ttf2_1 2020-11-11 20:12:24 +00:00
Vadim Pisarevsky
d42665d9e2 added truetype font support into OpenCV, based on STB_truetype 2020-11-11 22:17:05 +03:00
Alexander Alekhin
1088d95c50 Merge pull request #18707 from alalek:imgproc_drop_lsd 2020-11-07 17:29:21 +00:00
Vadim Pisarevsky
2ee9d21dae Merge pull request #18571 from vpisarev:add_lapack
Added clapack

* bring a small subset of Lapack, automatically converted to C, into OpenCV

* added missing lsame_ prototype

* * small fix in make_clapack script
* trying to fix remaining CI problems

* fixed character arrays' initializers

* get rid of F2C_STR_MAX

* * added back single-precision versions for QR, LU and Cholesky decompositions. It adds very little extra overhead.
* added stub version of sdesdd.
* uncommented calls to all the single-precision Lapack functions from opencv/core/src/hal_internal.cpp.

* fixed warning from Visual Studio + cleaned f2c runtime a bit

* * regenerated Lapack w/o forward declarations of intrinsic functions (such as sqrt(), r_cnjg() etc.)
* at once, trailing whitespaces are removed from the generated sources, just in case
* since there is no declarations of intrinsic functions anymore, we could turn some of them into inline functions

* trying to eliminate the crash on ARM

* fixed API and semantics of s_copy

* * CLapack has been tested successfully. It's now time to restore the standard LAPACK detection procedure
* removed some more trailing whitespaces

* * retained only the essential stuff in CLapack
* added checks to lapack calls to gracefully return "not implemented" instead of returning invalid results with "ok" status

* disabled warning when building lapack

* cmake: update LAPACK detection

Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
2020-11-05 21:46:51 +00:00
Alexander Alekhin
690725980c imgproc: drop LineSegmentDetector stubs 2020-10-30 00:57:09 +00:00
Alexander Alekhin
d0310c2a6a Merge pull request #18555 from alalek:next_versions 2020-10-13 10:12:26 +00:00
Alexander Alekhin
9794ff1398 next: update versions handling 2020-10-11 08:11:32 +00:00
Alexander Alekhin
53e6a25b6f next: OpenCV 5.0-pre 2020-10-07 21:53:09 +00:00
3547 changed files with 202541 additions and 1198951 deletions

View File

@@ -1,14 +0,0 @@
name: 4.x
on:
schedule:
- cron: '0 3 * * *'
workflow_dispatch:
jobs:
CodeQL:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-CodeQL.yaml@main
with:
target_branch: '4.x'
workflow_branch: main

View File

@@ -1,55 +0,0 @@
name: PR:4.x
on:
pull_request:
branches:
- 4.x
jobs:
Linux:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-Linux.yaml@main
with:
workflow_branch: main
Windows:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-Windows.yaml@main
with:
workflow_branch: main
Ubuntu2404-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-ARM64.yaml@main
Ubuntu2404-ARM64-Debug:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-ARM64-Debug.yaml@main
Ubuntu2004-x64-OpenVINO:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-U20-OpenVINO.yaml@main
Ubuntu2004-x64-CUDA:
if: "${{ contains(github.event.pull_request.labels.*.name, 'category: dnn') }} || ${{ contains(github.event.pull_request.labels.*.name, 'category: dnn (onnx)') }}"
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-U20-Cuda.yaml@main
macOS-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-macOS-ARM64.yaml@main
macOS-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-macOS-x86_64.yaml@main
macOS-ARM64-Vulkan:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-macOS-ARM64-Vulkan.yaml@main
iOS:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-iOS.yaml@main
Android-SDK:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-4.x-Android-SDK.yaml@main
TIM-VX:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-timvx-backend-tests-4.x.yml@main
docs:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-docs.yaml@main
Linux-RISC-V-Clang:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-4.x-RISCV.yaml@main

67
.github/workflows/PR-5.x.yaml vendored Normal file
View File

@@ -0,0 +1,67 @@
name: PR:5.x
on:
pull_request:
branches:
- 5.x
jobs:
Ubuntu2004-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-ARM64.yaml@main
Ubuntu2004-ARM64-Debug:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-ARM64-Debug.yaml@main
Ubuntu2004-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-U20.yaml@main
Ubuntu2004-x64-OpenVINO:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-U20-OpenVINO.yaml@main
Ubuntu2204-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-U22.yaml@main
Ubuntu2404-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-U24.yaml@main
Ubuntu2004-x64-CUDA:
if: "${{ contains(github.event.pull_request.labels.*.name, 'category: dnn') }} || ${{ contains(github.event.pull_request.labels.*.name, 'category: dnn (onnx)') }}"
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-U20-Cuda.yaml@main
Windows10-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-W10.yaml@main
Windows10-x64-UWP:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-W10-UWP.yaml@main
Windows10-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-W10-ARM64.yaml@main
# Vulkan configuration disabled as Vulkan backend for DNN does not support int/int64 for now
# Details: https://github.com/opencv/opencv/issues/25110
# Windows10-x64-Vulkan:
# uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-W10-Vulkan.yaml@main
macOS-ARM64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-macOS-ARM64.yaml@main
# macOS-ARM64-Vulkan:
# uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-macOS-ARM64-Vulkan.yaml@main
macOS-x64:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-macOS-x86_64.yaml@main
iOS:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-iOS.yaml@main
Android:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-Android.yaml@main
TIM-VX:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-timvx-backend-tests-4.x.yml@main
docs:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-docs.yaml@main
Linux-RISC-V-Clang:
uses: opencv/ci-gha-workflow/.github/workflows/OCV-PR-5.x-RISCV.yaml@main

View File

@@ -21,7 +21,6 @@ jobs:
crossbuild-essential-arm64 \
git \
cmake \
libpython-dev:arm64 \
libpython3-dev:arm64 \
python-numpy \
python3-numpy
@@ -34,10 +33,7 @@ jobs:
run: |
mkdir build
cd build
cmake -DPYTHON2_INCLUDE_PATH=/usr/include/python2.7/ \
-DPYTHON2_LIBRARIES=/usr/lib/aarch64-linux-gnu/libpython2.7.so \
-DPYTHON2_NUMPY_INCLUDE_DIRS=/usr/lib/python2.7/dist-packages/numpy/core/include \
-DPYTHON3_INCLUDE_PATH=/usr/include/python3.6m/ \
cmake -DPYTHON3_INCLUDE_PATH=/usr/include/python3.6m/ \
-DPYTHON3_LIBRARIES=/usr/lib/aarch64-linux-gnu/libpython3.6m.so \
-DPYTHON3_NUMPY_INCLUDE_DIRS=/usr/lib/python3/dist-packages/numpy/core/include \
-DCMAKE_TOOLCHAIN_FILE=../platforms/linux/aarch64-gnu.toolchain.cmake \

View File

@@ -119,7 +119,7 @@ private: \
#define TEGRA_BINARYOP(type, op, src1, sz1, src2, sz2, dst, sz, w, h) \
( \
CAROTENE_NS::isSupportedConfiguration() ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_##op##_Invoker<const type, type>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK \
@@ -154,7 +154,7 @@ TegraUnaryOp_Invoker(bitwiseNot, bitwiseNot)
#define TEGRA_UNARYOP(type, op, src1, sz1, dst, sz, w, h) \
( \
CAROTENE_NS::isSupportedConfiguration() ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_##op##_Invoker<const type, type>(src1, sz1, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK \
@@ -254,32 +254,32 @@ TegraGenOp_Invoker(cmpLE, cmpGE, 2, 1, 0, RANGE_DATA(ST, src2_data, src2_step),
( \
CAROTENE_NS::isSupportedConfiguration() ? \
((op) == cv::CMP_EQ) ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_cmpEQ_Invoker<const type, CAROTENE_NS::u8>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
((op) == cv::CMP_NE) ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_cmpNE_Invoker<const type, CAROTENE_NS::u8>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
((op) == cv::CMP_GT) ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_cmpGT_Invoker<const type, CAROTENE_NS::u8>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
((op) == cv::CMP_GE) ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_cmpGE_Invoker<const type, CAROTENE_NS::u8>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
((op) == cv::CMP_LT) ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_cmpLT_Invoker<const type, CAROTENE_NS::u8>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
((op) == cv::CMP_LE) ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_cmpLE_Invoker<const type, CAROTENE_NS::u8>(src1, sz1, src2, sz2, dst, sz, w, h), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
@@ -310,7 +310,7 @@ TegraGenOp_Invoker(cmpLE, cmpGE, 2, 1, 0, RANGE_DATA(ST, src2_data, src2_step),
#define TEGRA_BINARYOPSCALE(type, op, src1, sz1, src2, sz2, dst, sz, w, h, scales) \
( \
CAROTENE_NS::isSupportedConfiguration() ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_##op##_Invoker<const type, type>(src1, sz1, src2, sz2, dst, sz, w, h, scales), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK \
@@ -332,7 +332,7 @@ TegraBinaryOpScale_Invoker(divf, div, 1, scale)
#define TEGRA_UNARYOPSCALE(type, op, src1, sz1, dst, sz, w, h, scales) \
( \
CAROTENE_NS::isSupportedConfiguration() ? \
parallel_for_(cv::Range(0, h), \
parallel_for_(Range(0, h), \
TegraGenOp_##op##_Invoker<const type, type>(src1, sz1, dst, sz, w, h, scales), \
(w * h) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK \
@@ -928,17 +928,17 @@ TegraRowOp_Invoker(split4, split4, 1, 4, 0, RANGE_DATA(ST, src1_data, 4*sizeof(S
( \
CAROTENE_NS::isSupportedConfiguration() ? \
cn == 2 ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_split2_Invoker<const type, type>(src, dst[0], dst[1]), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
cn == 3 ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_split3_Invoker<const type, type>(src, dst[0], dst[1], dst[2]), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
cn == 4 ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_split4_Invoker<const type, type>(src, dst[0], dst[1], dst[2], dst[3]), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
@@ -990,17 +990,17 @@ TegraRowOp_Invoker(combine4, combine4, 4, 1, 0, RANGE_DATA(ST, src1_data, sizeof
( \
CAROTENE_NS::isSupportedConfiguration() ? \
cn == 2 ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_combine2_Invoker<const type, type>(src[0], src[1], dst), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
cn == 3 ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_combine3_Invoker<const type, type>(src[0], src[1], src[2], dst), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
cn == 4 ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_combine4_Invoker<const type, type>(src[0], src[1], src[2], src[3], dst), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
@@ -1033,7 +1033,7 @@ TegraRowOp_Invoker(phase, phase, 2, 1, 1, RANGE_DATA(ST, src1_data, sizeof(CAROT
#define TEGRA_FASTATAN(y, x, dst, len, angleInDegrees) \
( \
CAROTENE_NS::isSupportedConfiguration() ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_phase_Invoker<const CAROTENE_NS::f32, CAROTENE_NS::f32>(x, y, dst, angleInDegrees ? 1.0f : M_PI/180), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK \
@@ -1049,7 +1049,7 @@ TegraRowOp_Invoker(magnitude, magnitude, 2, 1, 0, RANGE_DATA(ST, src1_data, size
#define TEGRA_MAGNITUDE(x, y, dst, len) \
( \
CAROTENE_NS::isSupportedConfiguration() ? \
parallel_for_(cv::Range(0, len), \
parallel_for_(Range(0, len), \
TegraRowOp_magnitude_Invoker<const CAROTENE_NS::f32, CAROTENE_NS::f32>(x, y, dst), \
(len) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK \
@@ -1563,17 +1563,17 @@ TegraCvtColor_Invoker(rgbx2bgrx, rgbx2bgrx, src_data + static_cast<size_t>(range
scn == 3 ? \
dcn == 3 ? \
swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2bgr_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
CV_HAL_ERROR_NOT_IMPLEMENTED : \
dcn == 4 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2bgrx_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2rgbx_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
@@ -1581,16 +1581,16 @@ TegraCvtColor_Invoker(rgbx2bgrx, rgbx2bgrx, src_data + static_cast<size_t>(range
scn == 4 ? \
dcn == 3 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2bgr_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2rgb_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
dcn == 4 ? \
swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2bgrx_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
@@ -1613,19 +1613,19 @@ TegraCvtColor_Invoker(rgbx2rgb565, rgbx2rgb565, src_data + static_cast<size_t>(r
greenBits == 6 && CAROTENE_NS::isSupportedConfiguration() ? \
scn == 3 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2bgr565_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2rgb565_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
scn == 4 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2bgr565_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2rgb565_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
@@ -1646,19 +1646,19 @@ TegraCvtColor_Invoker(bgrx2gray, bgrx2gray, CAROTENE_NS::COLOR_SPACE_BT601, src_
depth == CV_8U && CAROTENE_NS::isSupportedConfiguration() ? \
scn == 3 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2gray_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgr2gray_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
scn == 4 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2gray_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgrx2gray_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
@@ -1674,12 +1674,12 @@ TegraCvtColor_Invoker(gray2rgbx, gray2rgbx, src_data + static_cast<size_t>(range
( \
depth == CV_8U && CAROTENE_NS::isSupportedConfiguration() ? \
dcn == 3 ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_gray2rgb_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
dcn == 4 ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_gray2rgbx_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)), \
CV_HAL_ERROR_OK : \
@@ -1700,19 +1700,19 @@ TegraCvtColor_Invoker(bgrx2ycrcb, bgrx2ycrcb, src_data + static_cast<size_t>(ran
isCbCr && depth == CV_8U && CAROTENE_NS::isSupportedConfiguration() ? \
scn == 3 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2ycrcb_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgr2ycrcb_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
scn == 4 ? \
(swapBlue ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2ycrcb_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgrx2ycrcb_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
@@ -1742,34 +1742,34 @@ TegraCvtColor_Invoker(bgrx2hsvf, bgrx2hsv, src_data + static_cast<size_t>(range.
scn == 3 ? \
(swapBlue ? \
isFullRange ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2hsvf_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgb2hsv_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
isFullRange ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgr2hsvf_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgr2hsv_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \
scn == 4 ? \
(swapBlue ? \
isFullRange ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2hsvf_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_rgbx2hsv_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
isFullRange ? \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgrx2hsvf_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) : \
parallel_for_(cv::Range(0, height), \
parallel_for_(Range(0, height), \
TegraCvtColor_bgrx2hsv_Invoker(src_data, src_step, dst_data, dst_step, width, height), \
(width * height) / static_cast<double>(1<<16)) ), \
CV_HAL_ERROR_OK : \

View File

@@ -359,7 +359,7 @@ namespace CAROTENE_NS {
/*
For each point `p` within `size`, do:
dst[p] = src0[p] * scale / src1[p]
dst[p] = src0[p] * scale / src1[p]
NOTE: ROUND_TO_ZERO convert policy is used
*/
@@ -420,7 +420,7 @@ namespace CAROTENE_NS {
/*
For each point `p` within `size`, do:
dst[p] = scale / src[p]
dst[p] = scale / src[p]
NOTE: ROUND_TO_ZERO convert policy is used
*/
@@ -1040,7 +1040,7 @@ namespace CAROTENE_NS {
s32 maxVal, size_t * maxLocPtr, s32 & maxLocCount, s32 maxLocCapacity);
/*
Among each pixel `p` within `src` find min and max values and its first occurrences
Among each pixel `p` within `src` find min and max values and its first occurences
*/
void minMaxLoc(const Size2D &size,
const s8 * srcBase, ptrdiff_t srcStride,

View File

@@ -378,7 +378,7 @@ void extract4(const Size2D &size,
vst1q_##sgn##bits(dst1 + d1j, vals.v4.val[3]); \
}
#endif
#endif
#define SPLIT4ALPHA(sgn,bits) void split4(const Size2D &_size, \
const sgn##bits * srcBase, ptrdiff_t srcStride, \

49
3rdparty/clapack/CMakeLists.txt vendored Normal file
View File

@@ -0,0 +1,49 @@
# ----------------------------------------------------------------------------
# CMake file for opencv_lapack. See root CMakeLists.txt
#
# ----------------------------------------------------------------------------
project(clapack)
# TODO: extract it from sources somehow
set(CLAPACK_VERSION "3.9.0" PARENT_SCOPE)
include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include")
# The .cpp files:
file(GLOB lapack_srcs src/*.c)
file(GLOB runtime_srcs runtime/*.c)
file(GLOB lib_hdrs include/*.h)
# ----------------------------------------------------------------------------------
# Define the library target:
# ----------------------------------------------------------------------------------
set(the_target "libclapack")
add_library(${the_target} STATIC ${lapack_srcs} ${runtime_srcs} ${lib_hdrs})
ocv_warnings_disable(CMAKE_C_FLAGS -Wno-parentheses -Wno-uninitialized -Wno-array-bounds
-Wno-implicit-function-declaration -Wno-unused -Wunused-parameter -Wstringop-truncation
-Wtautological-negation-compare) # gcc/clang warnings
ocv_warnings_disable(CMAKE_C_FLAGS /wd4244 /wd4554 /wd4723 /wd4819) # visual studio warnings
set_target_properties(${the_target}
PROPERTIES OUTPUT_NAME ${the_target}
DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
COMPILE_PDB_NAME ${the_target}
COMPILE_PDB_NAME_DEBUG "${the_target}${OPENCV_DEBUG_POSTFIX}"
ARCHIVE_OUTPUT_DIRECTORY ${3P_LIBRARY_OUTPUT_PATH}
)
set(CLAPACK_INCLUDE_DIR "${CMAKE_CURRENT_SOURCE_DIR}/include" PARENT_SCOPE)
set(CLAPACK_LIBRARIES ${the_target} PARENT_SCOPE)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(${the_target} PROPERTIES FOLDER "3rdparty")
endif()
if(NOT BUILD_SHARED_LIBS)
ocv_install_target(${the_target} EXPORT OpenCVModules ARCHIVE DESTINATION ${OPENCV_3P_LIB_INSTALL_PATH} COMPONENT dev)
endif()
ocv_install_3rdparty_licenses(clapack lapack_LICENSE)

102
3rdparty/clapack/include/cblas.h vendored Normal file
View File

@@ -0,0 +1,102 @@
#ifndef __CBLAS_H__
#define __CBLAS_H__
/* most of the stuff is in lapacke.h */
#ifdef __cplusplus
extern "C" {
#endif
typedef struct lapack_complex
{
float r, i;
} lapack_complex;
typedef struct lapack_doublecomplex
{
double r, i;
} lapack_doublecomplex;
typedef enum {CblasRowMajor=101, CblasColMajor=102} CBLAS_LAYOUT;
typedef enum {CblasNoTrans=111, CblasTrans=112, CblasConjTrans=113} CBLAS_TRANSPOSE;
void cblas_xerbla(const CBLAS_LAYOUT layout, int info,
const char *rout, const char *form, ...);
void cblas_sgemm(CBLAS_LAYOUT layout, CBLAS_TRANSPOSE TransA,
CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const float alpha, const float *A,
const int lda, const float *B, const int ldb,
const float beta, float *C, const int ldc);
void cblas_dgemm(CBLAS_LAYOUT layout, CBLAS_TRANSPOSE TransA,
CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const double alpha, const double *A,
const int lda, const double *B, const int ldb,
const double beta, double *C, const int ldc);
void cblas_cgemm(CBLAS_LAYOUT layout, CBLAS_TRANSPOSE TransA,
CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const void *alpha, const void *A,
const int lda, const void *B, const int ldb,
const void *beta, void *C, const int ldc);
void cblas_zgemm(CBLAS_LAYOUT layout, CBLAS_TRANSPOSE TransA,
CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const void *alpha, const void *A,
const int lda, const void *B, const int ldb,
const void *beta, void *C, const int ldc);
int xerbla_(char *, int *);
int lsame_(char *, char *);
double slamch_(char* cmach);
double slamc3_(float *a, float *b);
double dlamch_(char* cmach);
double dlamc3_(double *a, double *b);
int dgels_(char *trans, int *m, int *n, int *nrhs, double *a,
int *lda, double *b, int *ldb, double *work, int *lwork, int *info);
int dgesv_(int *n, int *nrhs, double *a, int *lda, int *ipiv,
double *b, int *ldb, int *info);
int dgetrf_(int *m, int *n, double *a, int *lda, int *ipiv,
int *info);
int dposv_(char *uplo, int *n, int *nrhs, double *a, int *
lda, double *b, int *ldb, int *info);
int dpotrf_(char *uplo, int *n, double *a, int *lda, int *
info);
int sgels_(char *trans, int *m, int *n, int *nrhs, float *a,
int *lda, float *b, int *ldb, float *work, int *lwork, int *info);
int sgeev_(char *jobvl, char *jobvr, int *n, float *a, int *
lda, float *wr, float *wi, float *vl, int *ldvl, float *vr, int *
ldvr, float *work, int *lwork, int *info);
int sgeqrf_(int *m, int *n, float *a, int *lda, float *tau,
float *work, int *lwork, int *info);
int sgesv_(int *n, int *nrhs, float *a, int *lda, int *ipiv,
float *b, int *ldb, int *info);
int sgetrf_(int *m, int *n, float *a, int *lda, int *ipiv,
int *info);
int sposv_(char *uplo, int *n, int *nrhs, float *a, int *
lda, float *b, int *ldb, int *info);
int spotrf_(char *uplo, int *n, float *a, int *lda, int *
info);
int sgesdd_(char *jobz, int *m, int *n, float *a, int *lda,
float *s, float *u, int *ldu, float *vt, int *ldvt, float *work,
int *lwork, int *iwork, int *info);
#ifdef __cplusplus
}
#endif
#endif /* __CBLAS_H__ */

129
3rdparty/clapack/include/f2c.h vendored Normal file
View File

@@ -0,0 +1,129 @@
/* f2c.h -- Standard Fortran to C header file */
/** barf [ba:rf] 2. "He suggested using FORTRAN, and everybody barfed."
- From The Shogakukan DICTIONARY OF NEW ENGLISH (Second edition) */
#ifndef __F2C_H__
#define __F2C_H__
#include <assert.h>
#include <math.h>
#include <ctype.h>
#include <stdlib.h>
#include <string.h>
#include <stdio.h>
#include "cblas.h"
#include "lapack.h"
#ifdef __cplusplus
extern "C" {
#endif
#undef complex
typedef int integer;
typedef unsigned int uinteger;
typedef char *address;
typedef short int shortint;
typedef float real;
typedef double doublereal;
typedef lapack_complex complex;
typedef lapack_doublecomplex doublecomplex;
typedef int logical;
typedef short int shortlogical;
typedef char logical1;
typedef char integer1;
#define TRUE_ (1)
#define FALSE_ (0)
#ifndef abs
#define abs(x) ((x) >= 0 ? (x) : -(x))
#endif
#define dabs(x) (double)abs(x)
#ifndef min
#define min(a,b) ((a) <= (b) ? (a) : (b))
#endif
#ifndef max
#define max(a,b) ((a) >= (b) ? (a) : (b))
#endif
#define dmin(a,b) (double)min(a,b)
#define dmax(a,b) (double)max(a,b)
#define bit_test(a,b) ((a) >> (b) & 1)
#define bit_clear(a,b) ((a) & ~((uinteger)1 << (b)))
#define bit_set(a,b) ((a) | ((uinteger)1 << (b)))
static __inline double r_lg10(float *x)
{
return 0.43429448190325182765*log(*x);
}
static __inline double d_lg10(double *x)
{
return 0.43429448190325182765*log(*x);
}
static __inline double d_sign(double *a, double *b)
{
double x = fabs(*a);
return *b >= 0 ? x : -x;
}
static __inline double r_sign(float *a, float *b)
{
double x = fabs((double)*a);
return *b >= 0 ? x : -x;
}
static __inline int i_nint(float *x)
{
return (int)(*x >= 0 ? floor(*x + .5) : -floor(.5 - *x));
}
int pow_ii(int *ap, int *bp);
double pow_di(double *ap, int *bp);
static __inline double pow_ri(float *ap, int *bp)
{
double apd = *ap;
return pow_di(&apd, bp);
}
static __inline double pow_dd(double *ap, double *bp)
{
return pow(*ap, *bp);
}
static __inline void d_cnjg(doublecomplex *r, doublecomplex *z)
{
double zi = z->i;
r->r = z->r;
r->i = -zi;
}
static __inline void r_cnjg(complex *r, complex *z)
{
float zi = z->i;
r->r = z->r;
r->i = -zi;
}
static __inline int s_copy(char *a, char *b, int maxlen)
{
strncpy(a, b, maxlen);
a[maxlen] = '\0';
return 0;
}
int s_cat(char *lp, char **rpp, int* rnp, int *np);
int s_cmp(char *a0, char *b0);
static __inline int i_len(char* s)
{
return (int)strlen(s);
}
#ifdef __cplusplus
}
#endif
#endif

386
3rdparty/clapack/include/lapack.h vendored Normal file
View File

@@ -0,0 +1,386 @@
// this is auto-generated header for Lapack subset
#ifndef __CLAPACK_H__
#define __CLAPACK_H__
#include "cblas.h"
#ifdef __cplusplus
extern "C" {
#endif
int cgemm_(char *transa, char *transb, int *m, int *n, int *
k, lapack_complex *alpha, lapack_complex *a, int *lda, lapack_complex *b, int *ldb,
lapack_complex *beta, lapack_complex *c__, int *ldc);
int daxpy_(int *n, double *da, double *dx, int *incx, double
*dy, int *incy);
int dbdsdc_(char *uplo, char *compq, int *n, double *d__,
double *e, double *u, int *ldu, double *vt, int *ldvt, double *q, int
*iq, double *work, int *iwork, int *info);
int dbdsqr_(char *uplo, int *n, int *ncvt, int *nru, int *
ncc, double *d__, double *e, double *vt, int *ldvt, double *u, int *
ldu, double *c__, int *ldc, double *work, int *info);
int dcombssq_(double *v1, double *v2);
int dcopy_(int *n, double *dx, int *incx, double *dy, int *
incy);
double ddot_(int *n, double *dx, int *incx, double *dy, int *incy);
int dgebak_(char *job, char *side, int *n, int *ilo, int *
ihi, double *scale, int *m, double *v, int *ldv, int *info);
int dgebal_(char *job, int *n, double *a, int *lda, int *ilo,
int *ihi, double *scale, int *info);
int dgebd2_(int *m, int *n, double *a, int *lda, double *d__,
double *e, double *tauq, double *taup, double *work, int *info);
int dgebrd_(int *m, int *n, double *a, int *lda, double *d__,
double *e, double *tauq, double *taup, double *work, int *lwork, int
*info);
int dgeev_(char *jobvl, char *jobvr, int *n, double *a, int *
lda, double *wr, double *wi, double *vl, int *ldvl, double *vr, int *
ldvr, double *work, int *lwork, int *info);
int dgehd2_(int *n, int *ilo, int *ihi, double *a, int *lda,
double *tau, double *work, int *info);
int dgehrd_(int *n, int *ilo, int *ihi, double *a, int *lda,
double *tau, double *work, int *lwork, int *info);
int dgelq2_(int *m, int *n, double *a, int *lda, double *tau,
double *work, int *info);
int dgelqf_(int *m, int *n, double *a, int *lda, double *tau,
double *work, int *lwork, int *info);
int dgemm_(char *transa, char *transb, int *m, int *n, int *
k, double *alpha, double *a, int *lda, double *b, int *ldb, double *
beta, double *c__, int *ldc);
int dgemv_(char *trans, int *m, int *n, double *alpha,
double *a, int *lda, double *x, int *incx, double *beta, double *y,
int *incy);
int dgeqr2_(int *m, int *n, double *a, int *lda, double *tau,
double *work, int *info);
int dgeqrf_(int *m, int *n, double *a, int *lda, double *tau,
double *work, int *lwork, int *info);
int dger_(int *m, int *n, double *alpha, double *x, int *
incx, double *y, int *incy, double *a, int *lda);
int dgesdd_(char *jobz, int *m, int *n, double *a, int *lda,
double *s, double *u, int *ldu, double *vt, int *ldvt, double *work,
int *lwork, int *iwork, int *info);
int dhseqr_(char *job, char *compz, int *n, int *ilo, int *
ihi, double *h__, int *ldh, double *wr, double *wi, double *z__, int *
ldz, double *work, int *lwork, int *info);
int disnan_(double *din);
// "small" is a macro defined in Windows headers: https://stackoverflow.com/a/27794577
#ifdef small
#undef small
#endif
int dlabad_(double *small, double *large);
int dlabrd_(int *m, int *n, int *nb, double *a, int *lda,
double *d__, double *e, double *tauq, double *taup, double *x, int *
ldx, double *y, int *ldy);
int dlacpy_(char *uplo, int *m, int *n, double *a, int *lda,
double *b, int *ldb);
int dladiv1_(double *a, double *b, double *c__, double *d__,
double *p, double *q);
double dladiv2_(double *a, double *b, double *c__, double *d__, double *r__,
double *t);
int dladiv_(double *a, double *b, double *c__, double *d__,
double *p, double *q);
int dlaed6_(int *kniter, int *orgati, double *rho, double *
d__, double *z__, double *finit, double *tau, int *info);
int dlaexc_(int *wantq, int *n, double *t, int *ldt, double *
q, int *ldq, int *j1, int *n1, int *n2, double *work, int *info);
int dlahqr_(int *wantt, int *wantz, int *n, int *ilo, int *
ihi, double *h__, int *ldh, double *wr, double *wi, int *iloz, int *
ihiz, double *z__, int *ldz, int *info);
int dlahr2_(int *n, int *k, int *nb, double *a, int *lda,
double *tau, double *t, int *ldt, double *y, int *ldy);
int dlaisnan_(double *din1, double *din2);
int dlaln2_(int *ltrans, int *na, int *nw, double *smin,
double *ca, double *a, int *lda, double *d1, double *d2, double *b,
int *ldb, double *wr, double *wi, double *x, int *ldx, double *scale,
double *xnorm, int *info);
int dlamrg_(int *n1, int *n2, double *a, int *dtrd1, int *
dtrd2, int *index);
double dlange_(char *norm, int *m, int *n, double *a, int *lda, double *work);
double dlanst_(char *norm, int *n, double *d__, double *e);
int dlanv2_(double *a, double *b, double *c__, double *d__,
double *rt1r, double *rt1i, double *rt2r, double *rt2i, double *cs,
double *sn);
double dlapy2_(double *x, double *y);
int dlaqr0_(int *wantt, int *wantz, int *n, int *ilo, int *
ihi, double *h__, int *ldh, double *wr, double *wi, int *iloz, int *
ihiz, double *z__, int *ldz, double *work, int *lwork, int *info);
int dlaqr1_(int *n, double *h__, int *ldh, double *sr1,
double *si1, double *sr2, double *si2, double *v);
int dlaqr2_(int *wantt, int *wantz, int *n, int *ktop, int *
kbot, int *nw, double *h__, int *ldh, int *iloz, int *ihiz, double *
z__, int *ldz, int *ns, int *nd, double *sr, double *si, double *v,
int *ldv, int *nh, double *t, int *ldt, int *nv, double *wv, int *
ldwv, double *work, int *lwork);
int dlaqr3_(int *wantt, int *wantz, int *n, int *ktop, int *
kbot, int *nw, double *h__, int *ldh, int *iloz, int *ihiz, double *
z__, int *ldz, int *ns, int *nd, double *sr, double *si, double *v,
int *ldv, int *nh, double *t, int *ldt, int *nv, double *wv, int *
ldwv, double *work, int *lwork);
int dlaqr4_(int *wantt, int *wantz, int *n, int *ilo, int *
ihi, double *h__, int *ldh, double *wr, double *wi, int *iloz, int *
ihiz, double *z__, int *ldz, double *work, int *lwork, int *info);
int dlaqr5_(int *wantt, int *wantz, int *kacc22, int *n, int
*ktop, int *kbot, int *nshfts, double *sr, double *si, double *h__,
int *ldh, int *iloz, int *ihiz, double *z__, int *ldz, double *v, int
*ldv, double *u, int *ldu, int *nv, double *wv, int *ldwv, int *nh,
double *wh, int *ldwh);
int dlarf_(char *side, int *m, int *n, double *v, int *incv,
double *tau, double *c__, int *ldc, double *work);
int dlarfb_(char *side, char *trans, char *direct, char *
storev, int *m, int *n, int *k, double *v, int *ldv, double *t, int *
ldt, double *c__, int *ldc, double *work, int *ldwork);
int dlarfg_(int *n, double *alpha, double *x, int *incx,
double *tau);
int dlarft_(char *direct, char *storev, int *n, int *k,
double *v, int *ldv, double *tau, double *t, int *ldt);
int dlarfx_(char *side, int *m, int *n, double *v, double *
tau, double *c__, int *ldc, double *work);
int dlartg_(double *f, double *g, double *cs, double *sn,
double *r__);
int dlas2_(double *f, double *g, double *h__, double *ssmin,
double *ssmax);
int dlascl_(char *type__, int *kl, int *ku, double *cfrom,
double *cto, int *m, int *n, double *a, int *lda, int *info);
int dlasd0_(int *n, int *sqre, double *d__, double *e,
double *u, int *ldu, double *vt, int *ldvt, int *smlsiz, int *iwork,
double *work, int *info);
int dlasd1_(int *nl, int *nr, int *sqre, double *d__, double
*alpha, double *beta, double *u, int *ldu, double *vt, int *ldvt, int
*idxq, int *iwork, double *work, int *info);
int dlasd2_(int *nl, int *nr, int *sqre, int *k, double *d__,
double *z__, double *alpha, double *beta, double *u, int *ldu,
double *vt, int *ldvt, double *dsigma, double *u2, int *ldu2, double *
vt2, int *ldvt2, int *idxp, int *idx, int *idxc, int *idxq, int *
coltyp, int *info);
int dlasd3_(int *nl, int *nr, int *sqre, int *k, double *d__,
double *q, int *ldq, double *dsigma, double *u, int *ldu, double *u2,
int *ldu2, double *vt, int *ldvt, double *vt2, int *ldvt2, int *idxc,
int *ctot, double *z__, int *info);
int dlasd4_(int *n, int *i__, double *d__, double *z__,
double *delta, double *rho, double *sigma, double *work, int *info);
int dlasd5_(int *i__, double *d__, double *z__, double *
delta, double *rho, double *dsigma, double *work);
int dlasd6_(int *icompq, int *nl, int *nr, int *sqre, double
*d__, double *vf, double *vl, double *alpha, double *beta, int *idxq,
int *perm, int *givptr, int *givcol, int *ldgcol, double *givnum, int
*ldgnum, double *poles, double *difl, double *difr, double *z__, int *
k, double *c__, double *s, double *work, int *iwork, int *info);
int dlasd7_(int *icompq, int *nl, int *nr, int *sqre, int *k,
double *d__, double *z__, double *zw, double *vf, double *vfw,
double *vl, double *vlw, double *alpha, double *beta, double *dsigma,
int *idx, int *idxp, int *idxq, int *perm, int *givptr, int *givcol,
int *ldgcol, double *givnum, int *ldgnum, double *c__, double *s, int
*info);
int dlasd8_(int *icompq, int *k, double *d__, double *z__,
double *vf, double *vl, double *difl, double *difr, int *lddifr,
double *dsigma, double *work, int *info);
int dlasda_(int *icompq, int *smlsiz, int *n, int *sqre,
double *d__, double *e, double *u, int *ldu, double *vt, int *k,
double *difl, double *difr, double *z__, double *poles, int *givptr,
int *givcol, int *ldgcol, int *perm, double *givnum, double *c__,
double *s, double *work, int *iwork, int *info);
int dlasdq_(char *uplo, int *sqre, int *n, int *ncvt, int *
nru, int *ncc, double *d__, double *e, double *vt, int *ldvt, double *
u, int *ldu, double *c__, int *ldc, double *work, int *info);
int dlasdt_(int *n, int *lvl, int *nd, int *inode, int *
ndiml, int *ndimr, int *msub);
int dlaset_(char *uplo, int *m, int *n, double *alpha,
double *beta, double *a, int *lda);
int dlasq1_(int *n, double *d__, double *e, double *work,
int *info);
int dlasq2_(int *n, double *z__, int *info);
int dlasq3_(int *i0, int *n0, double *z__, int *pp, double *
dmin__, double *sigma, double *desig, double *qmax, int *nfail, int *
iter, int *ndiv, int *ieee, int *ttype, double *dmin1, double *dmin2,
double *dn, double *dn1, double *dn2, double *g, double *tau);
int dlasq4_(int *i0, int *n0, double *z__, int *pp, int *
n0in, double *dmin__, double *dmin1, double *dmin2, double *dn,
double *dn1, double *dn2, double *tau, int *ttype, double *g);
int dlasq5_(int *i0, int *n0, double *z__, int *pp, double *
tau, double *sigma, double *dmin__, double *dmin1, double *dmin2,
double *dn, double *dnm1, double *dnm2, int *ieee, double *eps);
int dlasq6_(int *i0, int *n0, double *z__, int *pp, double *
dmin__, double *dmin1, double *dmin2, double *dn, double *dnm1,
double *dnm2);
int dlasr_(char *side, char *pivot, char *direct, int *m,
int *n, double *c__, double *s, double *a, int *lda);
int dlasrt_(char *id, int *n, double *d__, int *info);
int dlassq_(int *n, double *x, int *incx, double *scale,
double *sumsq);
int dlasv2_(double *f, double *g, double *h__, double *ssmin,
double *ssmax, double *snr, double *csr, double *snl, double *csl);
int dlasy2_(int *ltranl, int *ltranr, int *isgn, int *n1,
int *n2, double *tl, int *ldtl, double *tr, int *ldtr, double *b, int
*ldb, double *scale, double *x, int *ldx, double *xnorm, int *info);
double dnrm2_(int *n, double *x, int *incx);
int dorg2r_(int *m, int *n, int *k, double *a, int *lda,
double *tau, double *work, int *info);
int dorgbr_(char *vect, int *m, int *n, int *k, double *a,
int *lda, double *tau, double *work, int *lwork, int *info);
int dorghr_(int *n, int *ilo, int *ihi, double *a, int *lda,
double *tau, double *work, int *lwork, int *info);
int dorgl2_(int *m, int *n, int *k, double *a, int *lda,
double *tau, double *work, int *info);
int dorglq_(int *m, int *n, int *k, double *a, int *lda,
double *tau, double *work, int *lwork, int *info);
int dorgqr_(int *m, int *n, int *k, double *a, int *lda,
double *tau, double *work, int *lwork, int *info);
int dorm2r_(char *side, char *trans, int *m, int *n, int *k,
double *a, int *lda, double *tau, double *c__, int *ldc, double *work,
int *info);
int dormbr_(char *vect, char *side, char *trans, int *m, int
*n, int *k, double *a, int *lda, double *tau, double *c__, int *ldc,
double *work, int *lwork, int *info);
int dormhr_(char *side, char *trans, int *m, int *n, int *
ilo, int *ihi, double *a, int *lda, double *tau, double *c__, int *
ldc, double *work, int *lwork, int *info);
int dorml2_(char *side, char *trans, int *m, int *n, int *k,
double *a, int *lda, double *tau, double *c__, int *ldc, double *work,
int *info);
int dormlq_(char *side, char *trans, int *m, int *n, int *k,
double *a, int *lda, double *tau, double *c__, int *ldc, double *work,
int *lwork, int *info);
int dormqr_(char *side, char *trans, int *m, int *n, int *k,
double *a, int *lda, double *tau, double *c__, int *ldc, double *work,
int *lwork, int *info);
int drot_(int *n, double *dx, int *incx, double *dy, int *
incy, double *c__, double *s);
int dscal_(int *n, double *da, double *dx, int *incx);
int dswap_(int *n, double *dx, int *incx, double *dy, int *
incy);
int dtrevc3_(char *side, char *howmny, int *select, int *n,
double *t, int *ldt, double *vl, int *ldvl, double *vr, int *ldvr,
int *mm, int *m, double *work, int *lwork, int *info);
int dtrexc_(char *compq, int *n, double *t, int *ldt, double
*q, int *ldq, int *ifst, int *ilst, double *work, int *info);
int dtrmm_(char *side, char *uplo, char *transa, char *diag,
int *m, int *n, double *alpha, double *a, int *lda, double *b, int *
ldb);
int dtrmv_(char *uplo, char *trans, char *diag, int *n,
double *a, int *lda, double *x, int *incx);
int idamax_(int *n, double *dx, int *incx);
int ieeeck_(int *ispec, float *zero, float *one);
int iladlc_(int *m, int *n, double *a, int *lda);
int iladlr_(int *m, int *n, double *a, int *lda);
int ilaenv_(int *ispec, char *name__, char *opts, int *n1, int *n2, int *n3,
int *n4);
int iparmq_(int *ispec, char *name__, char *opts, int *n, int *ilo, int *ihi,
int *lwork);
int sgemm_(char *transa, char *transb, int *m, int *n, int *
k, float *alpha, float *a, int *lda, float *b, int *ldb, float *beta,
float *c__, int *ldc);
int zgemm_(char *transa, char *transb, int *m, int *n, int *
k, lapack_doublecomplex *alpha, lapack_doublecomplex *a, int *lda, lapack_doublecomplex *b,
int *ldb, lapack_doublecomplex *beta, lapack_doublecomplex *c__, int *ldc);
#ifdef __cplusplus
}
#endif
#endif

48
3rdparty/clapack/lapack_LICENSE vendored Normal file
View File

@@ -0,0 +1,48 @@
Copyright (c) 1992-2017 The University of Tennessee and The University
of Tennessee Research Foundation. All rights
reserved.
Copyright (c) 2000-2017 The University of California Berkeley. All
rights reserved.
Copyright (c) 2006-2017 The University of Colorado Denver. All rights
reserved.
$COPYRIGHT$
Additional copyrights may follow
$HEADER$
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer listed
in this license in the documentation and/or other materials
provided with the distribution.
- Neither the name of the copyright holders nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
The copyright holders provide no reassurances that the source code
provided does not infringe any patent, copyright, or any other
intellectual property rights of third parties. The copyright holders
disclaim any liability to any recipient for claims brought against
recipient by any third party for infringement of that parties
intellectual property rights.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

272
3rdparty/clapack/make_clapack.py vendored Normal file
View File

@@ -0,0 +1,272 @@
appdoc = """
This is generator of CLapack subset.
The usage:
1. Make sure you have the special version of f2c installed.
Grab it from https://github.com/vpisarev/f2c/tree/for_lapack.
2. Download fresh version of Lapack from
https://github.com/Reference-LAPACK/lapack.
You may choose some specific version or the latest snapshot.
3. If necessary, edit "roots" and "banlist" variables in this script, specify the needed and unneeded functions
4. From within a working directory run
$ python3 <opencv_root>/3rdparty/clapack/make_clapack.py <lapack_root>
or
$ F2C=<path_to_custom_f2c> python3 <opencv_root>/3rdparty/clapack/make_clapack.py <lapack_root>
it will generate "new_clapack" directory with "include" and "src" subdirectories.
5. erase opencv/3rdparty/clapack/src and replace it with new_clapack/src.
6. copy new_clapack/include/lapack.h to opencv/3rdparty/clapack/include.
7. optionally, edit opencv/3rdparty/clapack/CMakeLists.txt and update CLAPACK_VERSION as needed.
This is it. Now build it and enjoy.
"""
import glob, re, os, shutil, subprocess, sys
roots = ["cgemm_", "dgemm_", "sgemm_", "zgemm_",
"dgeev_", "dgesdd_",
#"dsyevr_",
#"dgesv_", "dgetrf_", "dposv_", "dpotrf_", "dgels_", "dgeqrf_",
#"sgesv_", "sgetrf_", "sposv_", "spotrf_", "sgels_", "sgeqrf_"
]
banlist = ["slamch_", "slamc3_", "dlamch_", "dlamc3_", "lsame_", "xerbla_"]
if len(sys.argv) < 2:
print(appdoc)
sys.exit(0)
lapack_root = sys.argv[1]
dst_path = "."
def error(msg):
print ("error: " + msg)
sys.exit(0)
def file2fun(fname):
return (os.path.basename(fname)[:-2]).upper()
def print_graph(m):
for (k, neighbors) in sorted(m.items()):
print (k + " : " + ", ".join(sorted(list(neighbors))))
blas_path = os.path.join(lapack_root, "BLAS/SRC")
lapack_path = os.path.join(lapack_root, "SRC")
roots = [f[:-1].upper() for f in roots]
banlist = [f[:-1].upper() for f in banlist]
def fun2file(func):
filename = func.lower() + ".f"
blas_loc = blas_path + "/" + filename
lapack_loc = lapack_path + "/" + filename
if os.path.exists(blas_loc):
return blas_loc
elif os.path.exists(lapack_loc):
return lapack_loc
else:
error("neither %s nor %s exist" % (blas_loc, lapack_loc))
all_files = glob.glob(blas_path + "/*.f") + glob.glob(lapack_path + "/*.f")
all_funcs = [file2fun(fname) for fname in all_files]
all_funcs_set = set(all_funcs).difference(set(banlist))
all_funcs = sorted(list(all_funcs_set))
func_deps = {}
#print all_funcs
words_regexp = re.compile(r'\w+')
def scan_deps(func):
global func_deps
if func in func_deps:
return
func_deps[func] = set([]) # to avoid possibly infinite recursion
f = open(fun2file(func), 'rt')
deps = []
external_mode = False
for l in f.readlines():
if l.startswith('*'):
continue
l = l.strip().upper()
if l.startswith('EXTERNAL '):
external_mode = True
elif l.startswith('$') and external_mode:
pass
else:
external_mode = False
if not external_mode:
continue
for w in words_regexp.findall(l):
if w in all_funcs_set:
deps.append(w)
f.close()
# remove func from its dependencies
deps = set(deps).difference(set([func]))
func_deps[func] = deps
for d in deps:
scan_deps(d)
for r in roots:
scan_deps(r)
selected_funcs = sorted(func_deps.keys())
print ("total files before amalgamation: %d" % len(selected_funcs))
inv_deps = {}
for func in selected_funcs:
inv_deps[func] = set([])
for (func, deps) in func_deps.items():
for d in deps:
inv_deps[d] = inv_deps[d].union(set([func]))
#print_graph(inv_deps)
func_home = {}
for func in selected_funcs:
func_home[func] = func
def get_home0(func, func0):
used_by = inv_deps[func]
if len(used_by) == 1:
p = list(used_by)[0]
if p != func and p != func0:
return get_home0(p, func0)
return func
return func
# try to merge some files
for func in selected_funcs:
func_home[func] = get_home0(func, func)
# try to merge some files even more
for iters in range(100):
homes_changed = False
for (func, used_by) in inv_deps.items():
p0 = func_home[func]
n = len(used_by)
if n == 1:
p = list(used_by)[0]
p1 = func_home[p]
if p1 != p0:
func_home[func] = p1
homes_changed = True
continue
elif n > 1:
phomes = set([])
for p in used_by:
phomes.add(func_home[p])
if len(phomes) == 1:
p1 = list(phomes)[0]
if p1 != p0:
func_home[func] = p1
homes_changed = True
if not homes_changed:
break
res_files = {}
for (func, h) in func_home.items():
elems = res_files.get(h, set([]))
elems.add(func)
res_files[h] = elems
print ("total files after amalgamation: %d" % len(res_files))
#print_graph(res_files)
outdir = os.path.join(dst_path, "new_clapack")
outdir_src = os.path.join(outdir, "src")
outdir_inc = os.path.join(outdir, "include")
shutil.rmtree(outdir, ignore_errors=True)
try:
os.makedirs(outdir_src)
except os.error:
pass
try:
os.makedirs(outdir_inc)
except os.error:
pass
f2c_appname = os.getenv("F2C", default="f2c")
print ("f2c used: %s" % f2c_appname)
f2c_getver_cmd = f2c_appname + " -v"
verstr = subprocess.check_output(f2c_getver_cmd.split(' ')).decode("utf-8")
if "for_lapack" not in verstr:
error("invalid version of f2c\n" + appdoc)
f2c_flags = "-ctypes -localconst -no-proto"
f2c_cmd0 = f2c_appname + " " + f2c_flags
f2c_cmd1 = f2c_appname + " -hdr none " + f2c_flags
lapack_protos = {}
extract_fn_regexp = re.compile(r'.+?(\w+)\s*\(')
def extract_proto(func, csrc):
global lapack_protos
cname = func.lower() + "_"
cfname = func.lower() + ".c"
regexp_str = r'\n(?:/\* Subroutine \*/\s*)?\w+\s+\w+\s*\((?:.|\n)+?\)[\s\n]*\{'
proto_regexp = re.compile(regexp_str)
ps = proto_regexp.findall(csrc)
for p in ps:
n = p.find("*/")
if n < 0:
n = 0
else:
n += 2
p = p[n:-1].strip() + ";"
fns = extract_fn_regexp.findall(p)
if len(fns) != 1:
error("prototype of function (%s) when analyzing %s cannot be parsed" % (p, cfname))
fn = fns[0]
if fn not in lapack_protos:
p = re.sub(r'\bcomplex\b', 'lapack_complex', p)
p = re.sub(r'\bdoublecomplex\b', 'lapack_doublecomplex', p)
lapack_protos[fn] = p
for (filename, funcs) in sorted(res_files.items()):
out = ""
f2c_cmd = f2c_cmd0
for func in sorted(list(funcs)):
ffilename = fun2file(func)
print ("running " + f2c_cmd + " on " + ffilename + " ...")
ffile = open(ffilename, 'rt')
delta_out = subprocess.check_output(f2c_cmd.split(' '), stdin=ffile).decode("utf-8")
# remove trailing whitespaces
delta_out = '\n'.join([l.rstrip() for l in delta_out.split('\n')])
extract_proto(func, delta_out)
out += delta_out
ffile.close()
f2c_cmd = f2c_cmd1
outname = os.path.join(outdir_src, filename.lower() + ".c")
outfile = open(outname, 'wt')
outfile.write(out)
outfile.close()
proto_hdr = """// this is auto-generated header for Lapack subset
#ifndef __CLAPACK_H__
#define __CLAPACK_H__
#include "cblas.h"
#ifdef __cplusplus
extern "C" {
#endif
%s
#ifdef __cplusplus
}
#endif
#endif
""" % "\n\n".join([p for (n, p) in sorted(lapack_protos.items())])
proto_hdr_fname = os.path.join(outdir_inc, "lapack.h")
f = open(proto_hdr_fname, 'wt')
f.write(proto_hdr)
f.close()

289
3rdparty/clapack/runtime/cblas_wrap.c vendored Normal file
View File

@@ -0,0 +1,289 @@
#include "f2c.h"
#include <stdarg.h>
void cblas_cgemm(const CBLAS_LAYOUT layout, const CBLAS_TRANSPOSE TransA,
const CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const void *alpha, const void *A,
const int lda, const void *B, const int ldb,
const void *beta, void *C, const int ldc)
{
char TA, TB;
if( layout == CblasColMajor )
{
if(TransA == CblasTrans) TA='T';
else if ( TransA == CblasConjTrans ) TA='C';
else if ( TransA == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_cgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TB='T';
else if ( TransB == CblasConjTrans ) TB='C';
else if ( TransB == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 3, "cblas_cgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
cgemm_(&TA, &TB, (int*)&M, (int*)&N, (int*)&K, (complex*)alpha, (complex*)A, (int*)&lda,
(complex*)B, (int*)&ldb, (complex*)beta, (complex*)C, (int*)&ldc);
}
else if (layout == CblasRowMajor)
{
if(TransA == CblasTrans) TB='T';
else if ( TransA == CblasConjTrans ) TB='C';
else if ( TransA == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 2, "cblas_cgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TA='T';
else if ( TransB == CblasConjTrans ) TA='C';
else if ( TransB == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_cgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
cgemm_(&TA, &TB, (int*)&N, (int*)&M, (int*)&K, (complex*)alpha, (complex*)B, (int*)&ldb,
(complex*)A, (int*)&lda, (complex*)beta, (complex*)C, (int*)&ldc);
}
else cblas_xerbla(layout, 1, "cblas_cgemm", "Illegal layout setting, %d\n", layout);
}
void cblas_dgemm(const CBLAS_LAYOUT layout, const CBLAS_TRANSPOSE TransA,
const CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const double alpha, const double *A,
const int lda, const double *B, const int ldb,
const double beta, double *C, const int ldc)
{
char TA, TB;
if( layout == CblasColMajor )
{
if(TransA == CblasTrans) TA='T';
else if ( TransA == CblasConjTrans ) TA='C';
else if ( TransA == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_dgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TB='T';
else if ( TransB == CblasConjTrans ) TB='C';
else if ( TransB == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 3, "cblas_dgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
dgemm_(&TA, &TB, (int*)&M, (int*)&N, (int*)&K, (double*)&alpha, (double*)A, (int*)&lda,
(double*)B, (int*)&ldb, (double*)&beta, (double*)C, (int*)&ldc);
}
else if (layout == CblasRowMajor)
{
if(TransA == CblasTrans) TB='T';
else if ( TransA == CblasConjTrans ) TB='C';
else if ( TransA == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 2, "cblas_dgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TA='T';
else if ( TransB == CblasConjTrans ) TA='C';
else if ( TransB == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_dgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
dgemm_(&TA, &TB, (int*)&N, (int*)&M, (int*)&K, (double*)&alpha, (double*)B, (int*)&ldb,
(double*)A, (int*)&lda, (double*)&beta, (double*)C, (int*)&ldc);
}
else cblas_xerbla(layout, 1, "cblas_dgemm", "Illegal layout setting, %d\n", layout);
}
void cblas_sgemm(const CBLAS_LAYOUT layout, const CBLAS_TRANSPOSE TransA,
const CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const float alpha, const float *A,
const int lda, const float *B, const int ldb,
const float beta, float *C, const int ldc)
{
char TA, TB;
if( layout == CblasColMajor )
{
if(TransA == CblasTrans) TA='T';
else if ( TransA == CblasConjTrans ) TA='C';
else if ( TransA == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_sgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TB='T';
else if ( TransB == CblasConjTrans ) TB='C';
else if ( TransB == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 3, "cblas_sgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
sgemm_(&TA, &TB, (int*)&M, (int*)&N, (int*)&K, (float*)&alpha, (float*)A, (int*)&lda,
(float*)B, (int*)&ldb, (float*)&beta, (float*)C, (int*)&ldc);
}
else if (layout == CblasRowMajor)
{
if(TransA == CblasTrans) TB='T';
else if ( TransA == CblasConjTrans ) TB='C';
else if ( TransA == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 2, "cblas_sgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TA='T';
else if ( TransB == CblasConjTrans ) TA='C';
else if ( TransB == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_sgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
sgemm_(&TA, &TB, (int*)&N, (int*)&M, (int*)&K, (float*)&alpha, (float*)B, (int*)&ldb,
(float*)A, (int*)&lda, (float*)&beta, (float*)C, (int*)&ldc);
}
else cblas_xerbla(layout, 1, "cblas_sgemm", "Illegal layout setting, %d\n", layout);
}
void cblas_zgemm(const CBLAS_LAYOUT layout, const CBLAS_TRANSPOSE TransA,
const CBLAS_TRANSPOSE TransB, const int M, const int N,
const int K, const void *alpha, const void *A,
const int lda, const void *B, const int ldb,
const void *beta, void *C, const int ldc)
{
char TA, TB;
if( layout == CblasColMajor )
{
if(TransA == CblasTrans) TA='T';
else if ( TransA == CblasConjTrans ) TA='C';
else if ( TransA == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_zgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TB='T';
else if ( TransB == CblasConjTrans ) TB='C';
else if ( TransB == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 3, "cblas_zgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
zgemm_(&TA, &TB, (int*)&M, (int*)&N, (int*)&K, (doublecomplex*)alpha, (doublecomplex*)A, (int*)&lda,
(doublecomplex*)B, (int*)&ldb, (doublecomplex*)beta, (doublecomplex*)C, (int*)&ldc);
}
else if (layout == CblasRowMajor)
{
if(TransA == CblasTrans) TB='T';
else if ( TransA == CblasConjTrans ) TB='C';
else if ( TransA == CblasNoTrans ) TB='N';
else
{
cblas_xerbla(layout, 2, "cblas_zgemm", "Illegal TransA setting, %d\n", TransA);
return;
}
if(TransB == CblasTrans) TA='T';
else if ( TransB == CblasConjTrans ) TA='C';
else if ( TransB == CblasNoTrans ) TA='N';
else
{
cblas_xerbla(layout, 2, "cblas_zgemm", "Illegal TransB setting, %d\n", TransB);
return;
}
zgemm_(&TA, &TB, (int*)&N, (int*)&M, (int*)&K, (doublecomplex*)alpha, (doublecomplex*)B, (int*)&ldb,
(doublecomplex*)A, (int*)&lda, (doublecomplex*)beta, (doublecomplex*)C, (int*)&ldc);
}
else cblas_xerbla(layout, 1, "cblas_zgemm", "Illegal layout setting, %d\n", layout);
}
void cblas_xerbla(const CBLAS_LAYOUT layout, int info, const char *rout, const char *form, ...)
{
extern int RowMajorStrg;
char empty[1] = "";
va_list argptr;
va_start(argptr, form);
if (layout == CblasRowMajor)
{
if (strstr(rout,"gemm") != 0)
{
if (info == 5 ) info = 4;
else if (info == 4 ) info = 5;
else if (info == 11) info = 9;
else if (info == 9 ) info = 11;
}
else if (strstr(rout,"symm") != 0 || strstr(rout,"hemm") != 0)
{
if (info == 5 ) info = 4;
else if (info == 4 ) info = 5;
}
else if (strstr(rout,"trmm") != 0 || strstr(rout,"trsm") != 0)
{
if (info == 7 ) info = 6;
else if (info == 6 ) info = 7;
}
else if (strstr(rout,"gemv") != 0)
{
if (info == 4) info = 3;
else if (info == 3) info = 4;
}
else if (strstr(rout,"gbmv") != 0)
{
if (info == 4) info = 3;
else if (info == 3) info = 4;
else if (info == 6) info = 5;
else if (info == 5) info = 6;
}
else if (strstr(rout,"ger") != 0)
{
if (info == 3) info = 2;
else if (info == 2) info = 3;
else if (info == 8) info = 6;
else if (info == 6) info = 8;
}
else if ( (strstr(rout,"her2") != 0 || strstr(rout,"hpr2") != 0)
&& strstr(rout,"her2k") == 0 )
{
if (info == 8) info = 6;
else if (info == 6) info = 8;
}
}
if (info)
fprintf(stderr, "Parameter %d to routine %s was incorrect\n", info, rout);
vfprintf(stderr, form, argptr);
va_end(argptr);
if (info && !info)
xerbla_(empty, &info); /* Force link of our F77 error handler */
exit(-1);
}

View File

@@ -0,0 +1,72 @@
#include "f2c.h"
#include <float.h>
#include <stdio.h>
/* *********************************************************************** */
double dlamc3_(double *a, double *b)
{
/* -- LAPACK auxiliary routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* DLAMC3 is intended to force A and B to be stored prior to doing */
/* the addition of A and B , for use in situations where optimizers */
/* might hold one of these in a register. */
/* Arguments */
/* ========= */
/* A (input) DOUBLE PRECISION */
/* B (input) DOUBLE PRECISION */
/* The values A and B. */
/* ===================================================================== */
/* .. Executable Statements .. */
double ret_val = *a + *b;
return ret_val;
/* End of DLAMC3 */
} /* dlamc3_ */
/* simpler version of dlamch for the case of IEEE754-compliant FPU module by Piotr Luszczek S.
taken from http://www.mail-archive.com/numpy-discussion@lists.sourceforge.net/msg02448.html */
#ifndef DBL_DIGITS
#define DBL_DIGITS 53
#endif
static const unsigned char lapack_dlamch_tab0[] =
{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 3, 4, 5, 6, 7, 0, 8, 9, 0, 10, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 3, 4, 5, 6, 7, 0, 8, 9,
0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
};
const double lapack_dlamch_tab1[] =
{
0, FLT_RADIX, DBL_EPSILON, DBL_MAX_EXP, DBL_MIN_EXP, DBL_DIGITS, DBL_MAX,
DBL_EPSILON*FLT_RADIX, 1, DBL_MIN*(1 + DBL_EPSILON), DBL_MIN
};
double dlamch_(char* cmach)
{
return lapack_dlamch_tab1[lapack_dlamch_tab0[(unsigned char)cmach[0]]];
}

96
3rdparty/clapack/runtime/lapack_stubs.c vendored Normal file
View File

@@ -0,0 +1,96 @@
#include "f2c.h"
static const int CLAPACK_NOT_IMPLEMENTED = -1024;
int sgesdd_(char *jobz, int *m, int *n, float *a, int *lda,
float *s, float *u, int *ldu, float *vt, int *ldvt, float *work,
int *lwork, int *iwork, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int dgels_(char *trans, int *m, int *n, int *nrhs, double *a,
int *lda, double *b, int *ldb, double *work, int *lwork, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int dgesv_(int *n, int *nrhs, double *a, int *lda, int *ipiv,
double *b, int *ldb, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int dgetrf_(int *m, int *n, double *a, int *lda, int *ipiv,
int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int dposv_(char *uplo, int *n, int *nrhs, double *a, int *
lda, double *b, int *ldb, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int dpotrf_(char *uplo, int *n, double *a, int *lda, int *
info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int sgels_(char *trans, int *m, int *n, int *nrhs, float *a,
int *lda, float *b, int *ldb, float *work, int *lwork, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int sgeev_(char *jobvl, char *jobvr, int *n, float *a, int *
lda, float *wr, float *wi, float *vl, int *ldvl, float *vr, int *
ldvr, float *work, int *lwork, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int sgeqrf_(int *m, int *n, float *a, int *lda, float *tau,
float *work, int *lwork, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int sgesv_(int *n, int *nrhs, float *a, int *lda, int *ipiv,
float *b, int *ldb, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int sgetrf_(int *m, int *n, float *a, int *lda, int *ipiv,
int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int sposv_(char *uplo, int *n, int *nrhs, float *a, int *
lda, float *b, int *ldb, int *info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}
int spotrf_(char *uplo, int *n, float *a, int *lda, int *
info)
{
*info = CLAPACK_NOT_IMPLEMENTED;
return 0;
}

25
3rdparty/clapack/runtime/lsame_custom.c vendored Normal file
View File

@@ -0,0 +1,25 @@
#include "f2c.h"
static const unsigned char lapack_toupper_tab[] =
{
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,
46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 96, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 123, 124, 125, 126, 127, 128, 129, 130, 131,
132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149,
150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167,
168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185,
186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203,
204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221,
222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239,
240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255
};
#define lapack_toupper(c) ((char)lapack_toupper_tab[(unsigned char)(c)])
int lsame_(char *ca, char *cb)
{
return lapack_toupper(ca[0]) == lapack_toupper(cb[0]);
}

27
3rdparty/clapack/runtime/pow_di.c vendored Normal file
View File

@@ -0,0 +1,27 @@
#include "f2c.h"
double pow_di(double *ap, int *bp)
{
double p = 1;
double x = *ap;
int n = *bp;
if(n != 0)
{
if(n < 0)
{
n = -n;
x = 1/x;
}
unsigned u = (unsigned)n;
for(;;)
{
if((u & 1) != 0)
p *= x;
if((u >>= 1) == 0)
break;
x *= x;
}
}
return p;
}

25
3rdparty/clapack/runtime/pow_ii.c vendored Normal file
View File

@@ -0,0 +1,25 @@
#include "f2c.h"
int pow_ii(int *ap, int *bp)
{
int p;
int x = *ap;
int n = *bp;
if (n <= 0) {
if (n == 0 || x == 1)
return 1;
return x != -1 ? 0 : (n & 1) ? -1 : 1;
}
unsigned u = (unsigned)n;
for(p = 1; ; )
{
if(u & 01)
p *= x;
if(u >>= 1)
x *= x;
else
break;
}
return p;
}

22
3rdparty/clapack/runtime/s_cat.c vendored Normal file
View File

@@ -0,0 +1,22 @@
/* Unless compiled with -DNO_OVERWRITE, this variant of s_cat allows the
* target of a concatenation to appear on its right-hand side (contrary
* to the Fortran 77 Standard, but in accordance with Fortran 90).
*/
#include "f2c.h"
int s_cat(char *lp, char **rpp, int* rnp, int *np)
{
int i, L = 0;
int n = *np;
for(i = 0; i < n; i++) {
int ni = rnp[i];
if(ni > 0) {
memcpy(lp + L, rpp[i], ni);
L += ni;
}
}
lp[L] = '\0';
return 0;
}

40
3rdparty/clapack/runtime/s_cmp.c vendored Normal file
View File

@@ -0,0 +1,40 @@
#include "f2c.h"
/* compare two strings */
int s_cmp(char *a0, char *b0)
{
int la = (int)strlen(a0);
int lb = (int)strlen(b0);
unsigned char *a, *aend, *b, *bend;
a = (unsigned char *)a0;
b = (unsigned char *)b0;
aend = a + la;
bend = b + lb;
if(la <= lb)
{
while(a < aend)
if(*a != *b)
return( *a - *b );
else
{ ++a; ++b; }
while(b < bend)
if(*b != ' ')
return( ' ' - *b );
else ++b;
}
else
{
while(b < bend)
if(*a == *b)
{ ++a; ++b; }
else
return( *a - *b );
while(a < aend)
if(*a != ' ')
return(*a - ' ');
else ++a;
}
return(0);
}

View File

@@ -0,0 +1,71 @@
#include "f2c.h"
#include <float.h>
#include <stdio.h>
/* *********************************************************************** */
double slamc3_(float *a, float *b)
{
/* -- LAPACK auxiliary routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SLAMC3 is intended to force A and B to be stored prior to doing */
/* the addition of A and B , for use in situations where optimizers */
/* might hold one of these in a register. */
/* Arguments */
/* ========= */
/* A (input) REAL */
/* B (input) REAL */
/* The values A and B. */
/* ===================================================================== */
/* .. Executable Statements .. */
float ret_val = *a + *b;
return ret_val;
/* End of SLAMC3 */
} /* slamc3_ */
/* simpler version of slamch for the case of IEEE754-compliant FPU module by Piotr Luszczek S.
taken from http://www.mail-archive.com/numpy-discussion@lists.sourceforge.net/msg02448.html */
#ifndef FLT_DIGITS
#define FLT_DIGITS 24
#endif
static const unsigned char lapack_slamch_tab0[] =
{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 3, 4, 5, 6, 7, 0, 8, 9, 0, 10, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 3, 4, 5, 6, 7, 0, 8, 9,
0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
};
const double lapack_slamch_tab1[] =
{
0, FLT_RADIX, FLT_EPSILON, FLT_MAX_EXP, FLT_MIN_EXP, FLT_DIGITS, FLT_MAX,
FLT_EPSILON*FLT_RADIX, 1, FLT_MIN*(1 + FLT_EPSILON), FLT_MIN
};
double slamch_(char* cmach)
{
return lapack_slamch_tab1[lapack_slamch_tab0[(unsigned char)cmach[0]]];
}

View File

@@ -0,0 +1,19 @@
/* xerbla.f -- translated by f2c (version 20061008).
You must link the resulting object file with libf2c:
on Microsoft Windows system, link with libf2c.lib;
on Linux or Unix systems, link with .../path/to/libf2c.a -lm
or, if you install libf2c.a in a standard place, with -lf2c -lm
-- in that order, at the end of the command line, as in
cc *.o -lf2c -lm
Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
http://www.netlib.org/f2c/libf2c.zip
*/
#include "f2c.h"
/* Subroutine */ int xerbla_(char *srname, int *info)
{
printf("** On entry to %s, parameter number %2i had an illegal value\n", srname, *info);
return 0;
} /* xerbla_ */

752
3rdparty/clapack/src/cgemm.c vendored Normal file
View File

@@ -0,0 +1,752 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b CGEMM
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
// Definition:
// ===========
//
// SUBROUTINE CGEMM(TRANSA,TRANSB,M,N,K,ALPHA,A,LDA,B,LDB,BETA,C,LDC)
//
// .. Scalar Arguments ..
// COMPLEX ALPHA,BETA
// INTEGER K,LDA,LDB,LDC,M,N
// CHARACTER TRANSA,TRANSB
// ..
// .. Array Arguments ..
// COMPLEX A(LDA,*),B(LDB,*),C(LDC,*)
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> CGEMM performs one of the matrix-matrix operations
//>
//> C := alpha*op( A )*op( B ) + beta*C,
//>
//> where op( X ) is one of
//>
//> op( X ) = X or op( X ) = X**T or op( X ) = X**H,
//>
//> alpha and beta are scalars, and A, B and C are matrices, with op( A )
//> an m by k matrix, op( B ) a k by n matrix and C an m by n matrix.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] TRANSA
//> \verbatim
//> TRANSA is CHARACTER*1
//> On entry, TRANSA specifies the form of op( A ) to be used in
//> the matrix multiplication as follows:
//>
//> TRANSA = 'N' or 'n', op( A ) = A.
//>
//> TRANSA = 'T' or 't', op( A ) = A**T.
//>
//> TRANSA = 'C' or 'c', op( A ) = A**H.
//> \endverbatim
//>
//> \param[in] TRANSB
//> \verbatim
//> TRANSB is CHARACTER*1
//> On entry, TRANSB specifies the form of op( B ) to be used in
//> the matrix multiplication as follows:
//>
//> TRANSB = 'N' or 'n', op( B ) = B.
//>
//> TRANSB = 'T' or 't', op( B ) = B**T.
//>
//> TRANSB = 'C' or 'c', op( B ) = B**H.
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> On entry, M specifies the number of rows of the matrix
//> op( A ) and of the matrix C. M must be at least zero.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> On entry, N specifies the number of columns of the matrix
//> op( B ) and the number of columns of the matrix C. N must be
//> at least zero.
//> \endverbatim
//>
//> \param[in] K
//> \verbatim
//> K is INTEGER
//> On entry, K specifies the number of columns of the matrix
//> op( A ) and the number of rows of the matrix op( B ). K must
//> be at least zero.
//> \endverbatim
//>
//> \param[in] ALPHA
//> \verbatim
//> ALPHA is COMPLEX
//> On entry, ALPHA specifies the scalar alpha.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is COMPLEX array, dimension ( LDA, ka ), where ka is
//> k when TRANSA = 'N' or 'n', and is m otherwise.
//> Before entry with TRANSA = 'N' or 'n', the leading m by k
//> part of the array A must contain the matrix A, otherwise
//> the leading k by m part of the array A must contain the
//> matrix A.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> On entry, LDA specifies the first dimension of A as declared
//> in the calling (sub) program. When TRANSA = 'N' or 'n' then
//> LDA must be at least max( 1, m ), otherwise LDA must be at
//> least max( 1, k ).
//> \endverbatim
//>
//> \param[in] B
//> \verbatim
//> B is COMPLEX array, dimension ( LDB, kb ), where kb is
//> n when TRANSB = 'N' or 'n', and is k otherwise.
//> Before entry with TRANSB = 'N' or 'n', the leading k by n
//> part of the array B must contain the matrix B, otherwise
//> the leading n by k part of the array B must contain the
//> matrix B.
//> \endverbatim
//>
//> \param[in] LDB
//> \verbatim
//> LDB is INTEGER
//> On entry, LDB specifies the first dimension of B as declared
//> in the calling (sub) program. When TRANSB = 'N' or 'n' then
//> LDB must be at least max( 1, k ), otherwise LDB must be at
//> least max( 1, n ).
//> \endverbatim
//>
//> \param[in] BETA
//> \verbatim
//> BETA is COMPLEX
//> On entry, BETA specifies the scalar beta. When BETA is
//> supplied as zero then C need not be set on input.
//> \endverbatim
//>
//> \param[in,out] C
//> \verbatim
//> C is COMPLEX array, dimension ( LDC, N )
//> Before entry, the leading m by n part of the array C must
//> contain the matrix C, except when beta is zero, in which
//> case C need not be set on entry.
//> On exit, the array C is overwritten by the m by n matrix
//> ( alpha*op( A )*op( B ) + beta*C ).
//> \endverbatim
//>
//> \param[in] LDC
//> \verbatim
//> LDC is INTEGER
//> On entry, LDC specifies the first dimension of C as declared
//> in the calling (sub) program. LDC must be at least
//> max( 1, m ).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup complex_blas_level3
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> Level 3 Blas routine.
//>
//> -- Written on 8-February-1989.
//> Jack Dongarra, Argonne National Laboratory.
//> Iain Duff, AERE Harwell.
//> Jeremy Du Croz, Numerical Algorithms Group Ltd.
//> Sven Hammarling, Numerical Algorithms Group Ltd.
//> \endverbatim
//>
// =====================================================================
/* Subroutine */ int cgemm_(char *transa, char *transb, int *m, int *n, int *
k, complex *alpha, complex *a, int *lda, complex *b, int *ldb,
complex *beta, complex *c__, int *ldc)
{
// Table of constant values
complex c_b1 = {1.f,0.f};
complex c_b2 = {0.f,0.f};
// System generated locals
int a_dim1, a_offset, b_dim1, b_offset, c_dim1, c_offset, i__1, i__2,
i__3, i__4, i__5, i__6;
complex q__1, q__2, q__3, q__4;
// Local variables
int i__, j, l, info;
int nota, notb;
complex temp;
int conja, conjb;
int ncola;
extern int lsame_(char *, char *);
int nrowa, nrowb;
extern /* Subroutine */ int xerbla_(char *, int *);
//
// -- Reference BLAS level3 routine (version 3.7.0) --
// -- Reference BLAS is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. External Functions ..
// ..
// .. External Subroutines ..
// ..
// .. Intrinsic Functions ..
// ..
// .. Local Scalars ..
// ..
// .. Parameters ..
// ..
//
// Set NOTA and NOTB as true if A and B respectively are not
// conjugated or transposed, set CONJA and CONJB as true if A and
// B respectively are to be transposed but not conjugated and set
// NROWA, NCOLA and NROWB as the number of rows and columns of A
// and the number of rows of B respectively.
//
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
// Function Body
nota = lsame_(transa, "N");
notb = lsame_(transb, "N");
conja = lsame_(transa, "C");
conjb = lsame_(transb, "C");
if (nota) {
nrowa = *m;
ncola = *k;
} else {
nrowa = *k;
ncola = *m;
}
if (notb) {
nrowb = *k;
} else {
nrowb = *n;
}
//
// Test the input parameters.
//
info = 0;
if (! nota && ! conja && ! lsame_(transa, "T")) {
info = 1;
} else if (! notb && ! conjb && ! lsame_(transb, "T")) {
info = 2;
} else if (*m < 0) {
info = 3;
} else if (*n < 0) {
info = 4;
} else if (*k < 0) {
info = 5;
} else if (*lda < max(1,nrowa)) {
info = 8;
} else if (*ldb < max(1,nrowb)) {
info = 10;
} else if (*ldc < max(1,*m)) {
info = 13;
}
if (info != 0) {
xerbla_("CGEMM ", &info);
return 0;
}
//
// Quick return if possible.
//
if (*m == 0 || *n == 0 || (alpha->r == 0.f && alpha->i == 0.f || *k == 0)
&& (beta->r == 1.f && beta->i == 0.f)) {
return 0;
}
//
// And when alpha.eq.zero.
//
if (alpha->r == 0.f && alpha->i == 0.f) {
if (beta->r == 0.f && beta->i == 0.f) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
c__[i__3].r = 0.f, c__[i__3].i = 0.f;
// L10:
}
// L20:
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
i__4 = i__ + j * c_dim1;
q__1.r = beta->r * c__[i__4].r - beta->i * c__[i__4].i,
q__1.i = beta->r * c__[i__4].i + beta->i * c__[
i__4].r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
// L30:
}
// L40:
}
}
return 0;
}
//
// Start the operations.
//
if (notb) {
if (nota) {
//
// Form C := alpha*A*B + beta*C.
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (beta->r == 0.f && beta->i == 0.f) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
c__[i__3].r = 0.f, c__[i__3].i = 0.f;
// L50:
}
} else if (beta->r != 1.f || beta->i != 0.f) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
i__4 = i__ + j * c_dim1;
q__1.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__1.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
// L60:
}
}
i__2 = *k;
for (l = 1; l <= i__2; ++l) {
i__3 = l + j * b_dim1;
q__1.r = alpha->r * b[i__3].r - alpha->i * b[i__3].i,
q__1.i = alpha->r * b[i__3].i + alpha->i * b[i__3]
.r;
temp.r = q__1.r, temp.i = q__1.i;
i__3 = *m;
for (i__ = 1; i__ <= i__3; ++i__) {
i__4 = i__ + j * c_dim1;
i__5 = i__ + j * c_dim1;
i__6 = i__ + l * a_dim1;
q__2.r = temp.r * a[i__6].r - temp.i * a[i__6].i,
q__2.i = temp.r * a[i__6].i + temp.i * a[i__6]
.r;
q__1.r = c__[i__5].r + q__2.r, q__1.i = c__[i__5].i +
q__2.i;
c__[i__4].r = q__1.r, c__[i__4].i = q__1.i;
// L70:
}
// L80:
}
// L90:
}
} else if (conja) {
//
// Form C := alpha*A**H*B + beta*C.
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp.r = 0.f, temp.i = 0.f;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
r_cnjg(&q__3, &a[l + i__ * a_dim1]);
i__4 = l + j * b_dim1;
q__2.r = q__3.r * b[i__4].r - q__3.i * b[i__4].i,
q__2.i = q__3.r * b[i__4].i + q__3.i * b[i__4]
.r;
q__1.r = temp.r + q__2.r, q__1.i = temp.i + q__2.i;
temp.r = q__1.r, temp.i = q__1.i;
// L100:
}
if (beta->r == 0.f && beta->i == 0.f) {
i__3 = i__ + j * c_dim1;
q__1.r = alpha->r * temp.r - alpha->i * temp.i,
q__1.i = alpha->r * temp.i + alpha->i *
temp.r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
} else {
i__3 = i__ + j * c_dim1;
q__2.r = alpha->r * temp.r - alpha->i * temp.i,
q__2.i = alpha->r * temp.i + alpha->i *
temp.r;
i__4 = i__ + j * c_dim1;
q__3.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__3.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
q__1.r = q__2.r + q__3.r, q__1.i = q__2.i + q__3.i;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
}
// L110:
}
// L120:
}
} else {
//
// Form C := alpha*A**T*B + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp.r = 0.f, temp.i = 0.f;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
i__4 = l + i__ * a_dim1;
i__5 = l + j * b_dim1;
q__2.r = a[i__4].r * b[i__5].r - a[i__4].i * b[i__5]
.i, q__2.i = a[i__4].r * b[i__5].i + a[i__4]
.i * b[i__5].r;
q__1.r = temp.r + q__2.r, q__1.i = temp.i + q__2.i;
temp.r = q__1.r, temp.i = q__1.i;
// L130:
}
if (beta->r == 0.f && beta->i == 0.f) {
i__3 = i__ + j * c_dim1;
q__1.r = alpha->r * temp.r - alpha->i * temp.i,
q__1.i = alpha->r * temp.i + alpha->i *
temp.r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
} else {
i__3 = i__ + j * c_dim1;
q__2.r = alpha->r * temp.r - alpha->i * temp.i,
q__2.i = alpha->r * temp.i + alpha->i *
temp.r;
i__4 = i__ + j * c_dim1;
q__3.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__3.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
q__1.r = q__2.r + q__3.r, q__1.i = q__2.i + q__3.i;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
}
// L140:
}
// L150:
}
}
} else if (nota) {
if (conjb) {
//
// Form C := alpha*A*B**H + beta*C.
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (beta->r == 0.f && beta->i == 0.f) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
c__[i__3].r = 0.f, c__[i__3].i = 0.f;
// L160:
}
} else if (beta->r != 1.f || beta->i != 0.f) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
i__4 = i__ + j * c_dim1;
q__1.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__1.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
// L170:
}
}
i__2 = *k;
for (l = 1; l <= i__2; ++l) {
r_cnjg(&q__2, &b[j + l * b_dim1]);
q__1.r = alpha->r * q__2.r - alpha->i * q__2.i, q__1.i =
alpha->r * q__2.i + alpha->i * q__2.r;
temp.r = q__1.r, temp.i = q__1.i;
i__3 = *m;
for (i__ = 1; i__ <= i__3; ++i__) {
i__4 = i__ + j * c_dim1;
i__5 = i__ + j * c_dim1;
i__6 = i__ + l * a_dim1;
q__2.r = temp.r * a[i__6].r - temp.i * a[i__6].i,
q__2.i = temp.r * a[i__6].i + temp.i * a[i__6]
.r;
q__1.r = c__[i__5].r + q__2.r, q__1.i = c__[i__5].i +
q__2.i;
c__[i__4].r = q__1.r, c__[i__4].i = q__1.i;
// L180:
}
// L190:
}
// L200:
}
} else {
//
// Form C := alpha*A*B**T + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (beta->r == 0.f && beta->i == 0.f) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
c__[i__3].r = 0.f, c__[i__3].i = 0.f;
// L210:
}
} else if (beta->r != 1.f || beta->i != 0.f) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
i__3 = i__ + j * c_dim1;
i__4 = i__ + j * c_dim1;
q__1.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__1.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
// L220:
}
}
i__2 = *k;
for (l = 1; l <= i__2; ++l) {
i__3 = j + l * b_dim1;
q__1.r = alpha->r * b[i__3].r - alpha->i * b[i__3].i,
q__1.i = alpha->r * b[i__3].i + alpha->i * b[i__3]
.r;
temp.r = q__1.r, temp.i = q__1.i;
i__3 = *m;
for (i__ = 1; i__ <= i__3; ++i__) {
i__4 = i__ + j * c_dim1;
i__5 = i__ + j * c_dim1;
i__6 = i__ + l * a_dim1;
q__2.r = temp.r * a[i__6].r - temp.i * a[i__6].i,
q__2.i = temp.r * a[i__6].i + temp.i * a[i__6]
.r;
q__1.r = c__[i__5].r + q__2.r, q__1.i = c__[i__5].i +
q__2.i;
c__[i__4].r = q__1.r, c__[i__4].i = q__1.i;
// L230:
}
// L240:
}
// L250:
}
}
} else if (conja) {
if (conjb) {
//
// Form C := alpha*A**H*B**H + beta*C.
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp.r = 0.f, temp.i = 0.f;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
r_cnjg(&q__3, &a[l + i__ * a_dim1]);
r_cnjg(&q__4, &b[j + l * b_dim1]);
q__2.r = q__3.r * q__4.r - q__3.i * q__4.i, q__2.i =
q__3.r * q__4.i + q__3.i * q__4.r;
q__1.r = temp.r + q__2.r, q__1.i = temp.i + q__2.i;
temp.r = q__1.r, temp.i = q__1.i;
// L260:
}
if (beta->r == 0.f && beta->i == 0.f) {
i__3 = i__ + j * c_dim1;
q__1.r = alpha->r * temp.r - alpha->i * temp.i,
q__1.i = alpha->r * temp.i + alpha->i *
temp.r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
} else {
i__3 = i__ + j * c_dim1;
q__2.r = alpha->r * temp.r - alpha->i * temp.i,
q__2.i = alpha->r * temp.i + alpha->i *
temp.r;
i__4 = i__ + j * c_dim1;
q__3.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__3.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
q__1.r = q__2.r + q__3.r, q__1.i = q__2.i + q__3.i;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
}
// L270:
}
// L280:
}
} else {
//
// Form C := alpha*A**H*B**T + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp.r = 0.f, temp.i = 0.f;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
r_cnjg(&q__3, &a[l + i__ * a_dim1]);
i__4 = j + l * b_dim1;
q__2.r = q__3.r * b[i__4].r - q__3.i * b[i__4].i,
q__2.i = q__3.r * b[i__4].i + q__3.i * b[i__4]
.r;
q__1.r = temp.r + q__2.r, q__1.i = temp.i + q__2.i;
temp.r = q__1.r, temp.i = q__1.i;
// L290:
}
if (beta->r == 0.f && beta->i == 0.f) {
i__3 = i__ + j * c_dim1;
q__1.r = alpha->r * temp.r - alpha->i * temp.i,
q__1.i = alpha->r * temp.i + alpha->i *
temp.r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
} else {
i__3 = i__ + j * c_dim1;
q__2.r = alpha->r * temp.r - alpha->i * temp.i,
q__2.i = alpha->r * temp.i + alpha->i *
temp.r;
i__4 = i__ + j * c_dim1;
q__3.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__3.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
q__1.r = q__2.r + q__3.r, q__1.i = q__2.i + q__3.i;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
}
// L300:
}
// L310:
}
}
} else {
if (conjb) {
//
// Form C := alpha*A**T*B**H + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp.r = 0.f, temp.i = 0.f;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
i__4 = l + i__ * a_dim1;
r_cnjg(&q__3, &b[j + l * b_dim1]);
q__2.r = a[i__4].r * q__3.r - a[i__4].i * q__3.i,
q__2.i = a[i__4].r * q__3.i + a[i__4].i *
q__3.r;
q__1.r = temp.r + q__2.r, q__1.i = temp.i + q__2.i;
temp.r = q__1.r, temp.i = q__1.i;
// L320:
}
if (beta->r == 0.f && beta->i == 0.f) {
i__3 = i__ + j * c_dim1;
q__1.r = alpha->r * temp.r - alpha->i * temp.i,
q__1.i = alpha->r * temp.i + alpha->i *
temp.r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
} else {
i__3 = i__ + j * c_dim1;
q__2.r = alpha->r * temp.r - alpha->i * temp.i,
q__2.i = alpha->r * temp.i + alpha->i *
temp.r;
i__4 = i__ + j * c_dim1;
q__3.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__3.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
q__1.r = q__2.r + q__3.r, q__1.i = q__2.i + q__3.i;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
}
// L330:
}
// L340:
}
} else {
//
// Form C := alpha*A**T*B**T + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp.r = 0.f, temp.i = 0.f;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
i__4 = l + i__ * a_dim1;
i__5 = j + l * b_dim1;
q__2.r = a[i__4].r * b[i__5].r - a[i__4].i * b[i__5]
.i, q__2.i = a[i__4].r * b[i__5].i + a[i__4]
.i * b[i__5].r;
q__1.r = temp.r + q__2.r, q__1.i = temp.i + q__2.i;
temp.r = q__1.r, temp.i = q__1.i;
// L350:
}
if (beta->r == 0.f && beta->i == 0.f) {
i__3 = i__ + j * c_dim1;
q__1.r = alpha->r * temp.r - alpha->i * temp.i,
q__1.i = alpha->r * temp.i + alpha->i *
temp.r;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
} else {
i__3 = i__ + j * c_dim1;
q__2.r = alpha->r * temp.r - alpha->i * temp.i,
q__2.i = alpha->r * temp.i + alpha->i *
temp.r;
i__4 = i__ + j * c_dim1;
q__3.r = beta->r * c__[i__4].r - beta->i * c__[i__4]
.i, q__3.i = beta->r * c__[i__4].i + beta->i *
c__[i__4].r;
q__1.r = q__2.r + q__3.r, q__1.i = q__2.i + q__3.i;
c__[i__3].r = q__1.r, c__[i__3].i = q__1.i;
}
// L360:
}
// L370:
}
}
}
return 0;
//
// End of CGEMM .
//
} // cgemm_

171
3rdparty/clapack/src/dcopy.c vendored Normal file
View File

@@ -0,0 +1,171 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DCOPY
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
// Definition:
// ===========
//
// SUBROUTINE DCOPY(N,DX,INCX,DY,INCY)
//
// .. Scalar Arguments ..
// INTEGER INCX,INCY,N
// ..
// .. Array Arguments ..
// DOUBLE PRECISION DX(*),DY(*)
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DCOPY copies a vector, x, to a vector, y.
//> uses unrolled loops for increments equal to 1.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> number of elements in input vector(s)
//> \endverbatim
//>
//> \param[in] DX
//> \verbatim
//> DX is DOUBLE PRECISION array, dimension ( 1 + ( N - 1 )*abs( INCX ) )
//> \endverbatim
//>
//> \param[in] INCX
//> \verbatim
//> INCX is INTEGER
//> storage spacing between elements of DX
//> \endverbatim
//>
//> \param[out] DY
//> \verbatim
//> DY is DOUBLE PRECISION array, dimension ( 1 + ( N - 1 )*abs( INCY ) )
//> \endverbatim
//>
//> \param[in] INCY
//> \verbatim
//> INCY is INTEGER
//> storage spacing between elements of DY
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date November 2017
//
//> \ingroup double_blas_level1
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> jack dongarra, linpack, 3/11/78.
//> modified 12/3/93, array(1) declarations changed to array(*)
//> \endverbatim
//>
// =====================================================================
/* Subroutine */ int dcopy_(int *n, double *dx, int *incx, double *dy, int *
incy)
{
// System generated locals
int i__1;
// Local variables
int i__, m, ix, iy, mp1;
//
// -- Reference BLAS level1 routine (version 3.8.0) --
// -- Reference BLAS is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// November 2017
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Local Scalars ..
// ..
// .. Intrinsic Functions ..
// ..
// Parameter adjustments
--dy;
--dx;
// Function Body
if (*n <= 0) {
return 0;
}
if (*incx == 1 && *incy == 1) {
//
// code for both increments equal to 1
//
//
// clean-up loop
//
m = *n % 7;
if (m != 0) {
i__1 = m;
for (i__ = 1; i__ <= i__1; ++i__) {
dy[i__] = dx[i__];
}
if (*n < 7) {
return 0;
}
}
mp1 = m + 1;
i__1 = *n;
for (i__ = mp1; i__ <= i__1; i__ += 7) {
dy[i__] = dx[i__];
dy[i__ + 1] = dx[i__ + 1];
dy[i__ + 2] = dx[i__ + 2];
dy[i__ + 3] = dx[i__ + 3];
dy[i__ + 4] = dx[i__ + 4];
dy[i__ + 5] = dx[i__ + 5];
dy[i__ + 6] = dx[i__ + 6];
}
} else {
//
// code for unequal increments or equal increments
// not equal to 1
//
ix = 1;
iy = 1;
if (*incx < 0) {
ix = (-(*n) + 1) * *incx + 1;
}
if (*incy < 0) {
iy = (-(*n) + 1) * *incy + 1;
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
dy[iy] = dx[ix];
ix += *incx;
iy += *incy;
}
}
return 0;
} // dcopy_

172
3rdparty/clapack/src/ddot.c vendored Normal file
View File

@@ -0,0 +1,172 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DDOT
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
// Definition:
// ===========
//
// DOUBLE PRECISION FUNCTION DDOT(N,DX,INCX,DY,INCY)
//
// .. Scalar Arguments ..
// INTEGER INCX,INCY,N
// ..
// .. Array Arguments ..
// DOUBLE PRECISION DX(*),DY(*)
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DDOT forms the dot product of two vectors.
//> uses unrolled loops for increments equal to one.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> number of elements in input vector(s)
//> \endverbatim
//>
//> \param[in] DX
//> \verbatim
//> DX is DOUBLE PRECISION array, dimension ( 1 + ( N - 1 )*abs( INCX ) )
//> \endverbatim
//>
//> \param[in] INCX
//> \verbatim
//> INCX is INTEGER
//> storage spacing between elements of DX
//> \endverbatim
//>
//> \param[in] DY
//> \verbatim
//> DY is DOUBLE PRECISION array, dimension ( 1 + ( N - 1 )*abs( INCY ) )
//> \endverbatim
//>
//> \param[in] INCY
//> \verbatim
//> INCY is INTEGER
//> storage spacing between elements of DY
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date November 2017
//
//> \ingroup double_blas_level1
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> jack dongarra, linpack, 3/11/78.
//> modified 12/3/93, array(1) declarations changed to array(*)
//> \endverbatim
//>
// =====================================================================
double ddot_(int *n, double *dx, int *incx, double *dy, int *incy)
{
// System generated locals
int i__1;
double ret_val;
// Local variables
int i__, m, ix, iy, mp1;
double dtemp;
//
// -- Reference BLAS level1 routine (version 3.8.0) --
// -- Reference BLAS is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// November 2017
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Local Scalars ..
// ..
// .. Intrinsic Functions ..
// ..
// Parameter adjustments
--dy;
--dx;
// Function Body
ret_val = 0.;
dtemp = 0.;
if (*n <= 0) {
return ret_val;
}
if (*incx == 1 && *incy == 1) {
//
// code for both increments equal to 1
//
//
// clean-up loop
//
m = *n % 5;
if (m != 0) {
i__1 = m;
for (i__ = 1; i__ <= i__1; ++i__) {
dtemp += dx[i__] * dy[i__];
}
if (*n < 5) {
ret_val = dtemp;
return ret_val;
}
}
mp1 = m + 1;
i__1 = *n;
for (i__ = mp1; i__ <= i__1; i__ += 5) {
dtemp = dtemp + dx[i__] * dy[i__] + dx[i__ + 1] * dy[i__ + 1] +
dx[i__ + 2] * dy[i__ + 2] + dx[i__ + 3] * dy[i__ + 3] +
dx[i__ + 4] * dy[i__ + 4];
}
} else {
//
// code for unequal increments or equal increments
// not equal to 1
//
ix = 1;
iy = 1;
if (*incx < 0) {
ix = (-(*n) + 1) * *incx + 1;
}
if (*incy < 0) {
iy = (-(*n) + 1) * *incy + 1;
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
dtemp += dx[ix] * dy[iy];
ix += *incx;
iy += *incy;
}
}
ret_val = dtemp;
return ret_val;
} // ddot_

14369
3rdparty/clapack/src/dgeev.c vendored Normal file

File diff suppressed because it is too large Load Diff

444
3rdparty/clapack/src/dgemm.c vendored Normal file
View File

@@ -0,0 +1,444 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DGEMM
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
// Definition:
// ===========
//
// SUBROUTINE DGEMM(TRANSA,TRANSB,M,N,K,ALPHA,A,LDA,B,LDB,BETA,C,LDC)
//
// .. Scalar Arguments ..
// DOUBLE PRECISION ALPHA,BETA
// INTEGER K,LDA,LDB,LDC,M,N
// CHARACTER TRANSA,TRANSB
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A(LDA,*),B(LDB,*),C(LDC,*)
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DGEMM performs one of the matrix-matrix operations
//>
//> C := alpha*op( A )*op( B ) + beta*C,
//>
//> where op( X ) is one of
//>
//> op( X ) = X or op( X ) = X**T,
//>
//> alpha and beta are scalars, and A, B and C are matrices, with op( A )
//> an m by k matrix, op( B ) a k by n matrix and C an m by n matrix.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] TRANSA
//> \verbatim
//> TRANSA is CHARACTER*1
//> On entry, TRANSA specifies the form of op( A ) to be used in
//> the matrix multiplication as follows:
//>
//> TRANSA = 'N' or 'n', op( A ) = A.
//>
//> TRANSA = 'T' or 't', op( A ) = A**T.
//>
//> TRANSA = 'C' or 'c', op( A ) = A**T.
//> \endverbatim
//>
//> \param[in] TRANSB
//> \verbatim
//> TRANSB is CHARACTER*1
//> On entry, TRANSB specifies the form of op( B ) to be used in
//> the matrix multiplication as follows:
//>
//> TRANSB = 'N' or 'n', op( B ) = B.
//>
//> TRANSB = 'T' or 't', op( B ) = B**T.
//>
//> TRANSB = 'C' or 'c', op( B ) = B**T.
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> On entry, M specifies the number of rows of the matrix
//> op( A ) and of the matrix C. M must be at least zero.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> On entry, N specifies the number of columns of the matrix
//> op( B ) and the number of columns of the matrix C. N must be
//> at least zero.
//> \endverbatim
//>
//> \param[in] K
//> \verbatim
//> K is INTEGER
//> On entry, K specifies the number of columns of the matrix
//> op( A ) and the number of rows of the matrix op( B ). K must
//> be at least zero.
//> \endverbatim
//>
//> \param[in] ALPHA
//> \verbatim
//> ALPHA is DOUBLE PRECISION.
//> On entry, ALPHA specifies the scalar alpha.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension ( LDA, ka ), where ka is
//> k when TRANSA = 'N' or 'n', and is m otherwise.
//> Before entry with TRANSA = 'N' or 'n', the leading m by k
//> part of the array A must contain the matrix A, otherwise
//> the leading k by m part of the array A must contain the
//> matrix A.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> On entry, LDA specifies the first dimension of A as declared
//> in the calling (sub) program. When TRANSA = 'N' or 'n' then
//> LDA must be at least max( 1, m ), otherwise LDA must be at
//> least max( 1, k ).
//> \endverbatim
//>
//> \param[in] B
//> \verbatim
//> B is DOUBLE PRECISION array, dimension ( LDB, kb ), where kb is
//> n when TRANSB = 'N' or 'n', and is k otherwise.
//> Before entry with TRANSB = 'N' or 'n', the leading k by n
//> part of the array B must contain the matrix B, otherwise
//> the leading n by k part of the array B must contain the
//> matrix B.
//> \endverbatim
//>
//> \param[in] LDB
//> \verbatim
//> LDB is INTEGER
//> On entry, LDB specifies the first dimension of B as declared
//> in the calling (sub) program. When TRANSB = 'N' or 'n' then
//> LDB must be at least max( 1, k ), otherwise LDB must be at
//> least max( 1, n ).
//> \endverbatim
//>
//> \param[in] BETA
//> \verbatim
//> BETA is DOUBLE PRECISION.
//> On entry, BETA specifies the scalar beta. When BETA is
//> supplied as zero then C need not be set on input.
//> \endverbatim
//>
//> \param[in,out] C
//> \verbatim
//> C is DOUBLE PRECISION array, dimension ( LDC, N )
//> Before entry, the leading m by n part of the array C must
//> contain the matrix C, except when beta is zero, in which
//> case C need not be set on entry.
//> On exit, the array C is overwritten by the m by n matrix
//> ( alpha*op( A )*op( B ) + beta*C ).
//> \endverbatim
//>
//> \param[in] LDC
//> \verbatim
//> LDC is INTEGER
//> On entry, LDC specifies the first dimension of C as declared
//> in the calling (sub) program. LDC must be at least
//> max( 1, m ).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup double_blas_level3
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> Level 3 Blas routine.
//>
//> -- Written on 8-February-1989.
//> Jack Dongarra, Argonne National Laboratory.
//> Iain Duff, AERE Harwell.
//> Jeremy Du Croz, Numerical Algorithms Group Ltd.
//> Sven Hammarling, Numerical Algorithms Group Ltd.
//> \endverbatim
//>
// =====================================================================
/* Subroutine */ int dgemm_(char *transa, char *transb, int *m, int *n, int *
k, double *alpha, double *a, int *lda, double *b, int *ldb, double *
beta, double *c__, int *ldc)
{
// System generated locals
int a_dim1, a_offset, b_dim1, b_offset, c_dim1, c_offset, i__1, i__2,
i__3;
// Local variables
int i__, j, l, info;
int nota, notb;
double temp;
int ncola;
extern int lsame_(char *, char *);
int nrowa, nrowb;
extern /* Subroutine */ int xerbla_(char *, int *);
//
// -- Reference BLAS level3 routine (version 3.7.0) --
// -- Reference BLAS is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. External Functions ..
// ..
// .. External Subroutines ..
// ..
// .. Intrinsic Functions ..
// ..
// .. Local Scalars ..
// ..
// .. Parameters ..
// ..
//
// Set NOTA and NOTB as true if A and B respectively are not
// transposed and set NROWA, NCOLA and NROWB as the number of rows
// and columns of A and the number of rows of B respectively.
//
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
// Function Body
nota = lsame_(transa, "N");
notb = lsame_(transb, "N");
if (nota) {
nrowa = *m;
ncola = *k;
} else {
nrowa = *k;
ncola = *m;
}
if (notb) {
nrowb = *k;
} else {
nrowb = *n;
}
//
// Test the input parameters.
//
info = 0;
if (! nota && ! lsame_(transa, "C") && ! lsame_(transa, "T")) {
info = 1;
} else if (! notb && ! lsame_(transb, "C") && ! lsame_(transb, "T")) {
info = 2;
} else if (*m < 0) {
info = 3;
} else if (*n < 0) {
info = 4;
} else if (*k < 0) {
info = 5;
} else if (*lda < max(1,nrowa)) {
info = 8;
} else if (*ldb < max(1,nrowb)) {
info = 10;
} else if (*ldc < max(1,*m)) {
info = 13;
}
if (info != 0) {
xerbla_("DGEMM ", &info);
return 0;
}
//
// Quick return if possible.
//
if (*m == 0 || *n == 0 || (*alpha == 0. || *k == 0) && *beta == 1.) {
return 0;
}
//
// And if alpha.eq.zero.
//
if (*alpha == 0.) {
if (*beta == 0.) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] = 0.;
// L10:
}
// L20:
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1];
// L30:
}
// L40:
}
}
return 0;
}
//
// Start the operations.
//
if (notb) {
if (nota) {
//
// Form C := alpha*A*B + beta*C.
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (*beta == 0.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] = 0.;
// L50:
}
} else if (*beta != 1.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1];
// L60:
}
}
i__2 = *k;
for (l = 1; l <= i__2; ++l) {
temp = *alpha * b[l + j * b_dim1];
i__3 = *m;
for (i__ = 1; i__ <= i__3; ++i__) {
c__[i__ + j * c_dim1] += temp * a[i__ + l * a_dim1];
// L70:
}
// L80:
}
// L90:
}
} else {
//
// Form C := alpha*A**T*B + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = 0.;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
temp += a[l + i__ * a_dim1] * b[l + j * b_dim1];
// L100:
}
if (*beta == 0.) {
c__[i__ + j * c_dim1] = *alpha * temp;
} else {
c__[i__ + j * c_dim1] = *alpha * temp + *beta * c__[
i__ + j * c_dim1];
}
// L110:
}
// L120:
}
}
} else {
if (nota) {
//
// Form C := alpha*A*B**T + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (*beta == 0.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] = 0.;
// L130:
}
} else if (*beta != 1.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] = *beta * c__[i__ + j * c_dim1];
// L140:
}
}
i__2 = *k;
for (l = 1; l <= i__2; ++l) {
temp = *alpha * b[j + l * b_dim1];
i__3 = *m;
for (i__ = 1; i__ <= i__3; ++i__) {
c__[i__ + j * c_dim1] += temp * a[i__ + l * a_dim1];
// L150:
}
// L160:
}
// L170:
}
} else {
//
// Form C := alpha*A**T*B**T + beta*C
//
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = 0.;
i__3 = *k;
for (l = 1; l <= i__3; ++l) {
temp += a[l + i__ * a_dim1] * b[j + l * b_dim1];
// L180:
}
if (*beta == 0.) {
c__[i__ + j * c_dim1] = *alpha * temp;
} else {
c__[i__ + j * c_dim1] = *alpha * temp + *beta * c__[
i__ + j * c_dim1];
}
// L190:
}
// L200:
}
}
}
return 0;
//
// End of DGEMM .
//
} // dgemm_

370
3rdparty/clapack/src/dgemv.c vendored Normal file
View File

@@ -0,0 +1,370 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DGEMV
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
// Definition:
// ===========
//
// SUBROUTINE DGEMV(TRANS,M,N,ALPHA,A,LDA,X,INCX,BETA,Y,INCY)
//
// .. Scalar Arguments ..
// DOUBLE PRECISION ALPHA,BETA
// INTEGER INCX,INCY,LDA,M,N
// CHARACTER TRANS
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A(LDA,*),X(*),Y(*)
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DGEMV performs one of the matrix-vector operations
//>
//> y := alpha*A*x + beta*y, or y := alpha*A**T*x + beta*y,
//>
//> where alpha and beta are scalars, x and y are vectors and A is an
//> m by n matrix.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] TRANS
//> \verbatim
//> TRANS is CHARACTER*1
//> On entry, TRANS specifies the operation to be performed as
//> follows:
//>
//> TRANS = 'N' or 'n' y := alpha*A*x + beta*y.
//>
//> TRANS = 'T' or 't' y := alpha*A**T*x + beta*y.
//>
//> TRANS = 'C' or 'c' y := alpha*A**T*x + beta*y.
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> On entry, M specifies the number of rows of the matrix A.
//> M must be at least zero.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> On entry, N specifies the number of columns of the matrix A.
//> N must be at least zero.
//> \endverbatim
//>
//> \param[in] ALPHA
//> \verbatim
//> ALPHA is DOUBLE PRECISION.
//> On entry, ALPHA specifies the scalar alpha.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension ( LDA, N )
//> Before entry, the leading m by n part of the array A must
//> contain the matrix of coefficients.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> On entry, LDA specifies the first dimension of A as declared
//> in the calling (sub) program. LDA must be at least
//> max( 1, m ).
//> \endverbatim
//>
//> \param[in] X
//> \verbatim
//> X is DOUBLE PRECISION array, dimension at least
//> ( 1 + ( n - 1 )*abs( INCX ) ) when TRANS = 'N' or 'n'
//> and at least
//> ( 1 + ( m - 1 )*abs( INCX ) ) otherwise.
//> Before entry, the incremented array X must contain the
//> vector x.
//> \endverbatim
//>
//> \param[in] INCX
//> \verbatim
//> INCX is INTEGER
//> On entry, INCX specifies the increment for the elements of
//> X. INCX must not be zero.
//> \endverbatim
//>
//> \param[in] BETA
//> \verbatim
//> BETA is DOUBLE PRECISION.
//> On entry, BETA specifies the scalar beta. When BETA is
//> supplied as zero then Y need not be set on input.
//> \endverbatim
//>
//> \param[in,out] Y
//> \verbatim
//> Y is DOUBLE PRECISION array, dimension at least
//> ( 1 + ( m - 1 )*abs( INCY ) ) when TRANS = 'N' or 'n'
//> and at least
//> ( 1 + ( n - 1 )*abs( INCY ) ) otherwise.
//> Before entry with BETA non-zero, the incremented array Y
//> must contain the vector y. On exit, Y is overwritten by the
//> updated vector y.
//> \endverbatim
//>
//> \param[in] INCY
//> \verbatim
//> INCY is INTEGER
//> On entry, INCY specifies the increment for the elements of
//> Y. INCY must not be zero.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup double_blas_level2
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> Level 2 Blas routine.
//> The vector and matrix arguments are not referenced when N = 0, or M = 0
//>
//> -- Written on 22-October-1986.
//> Jack Dongarra, Argonne National Lab.
//> Jeremy Du Croz, Nag Central Office.
//> Sven Hammarling, Nag Central Office.
//> Richard Hanson, Sandia National Labs.
//> \endverbatim
//>
// =====================================================================
/* Subroutine */ int dgemv_(char *trans, int *m, int *n, double *alpha,
double *a, int *lda, double *x, int *incx, double *beta, double *y,
int *incy)
{
// System generated locals
int a_dim1, a_offset, i__1, i__2;
// Local variables
int i__, j, ix, iy, jx, jy, kx, ky, info;
double temp;
int lenx, leny;
extern int lsame_(char *, char *);
extern /* Subroutine */ int xerbla_(char *, int *);
//
// -- Reference BLAS level2 routine (version 3.7.0) --
// -- Reference BLAS is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. External Functions ..
// ..
// .. External Subroutines ..
// ..
// .. Intrinsic Functions ..
// ..
//
// Test the input parameters.
//
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--x;
--y;
// Function Body
info = 0;
if (! lsame_(trans, "N") && ! lsame_(trans, "T") && ! lsame_(trans, "C"))
{
info = 1;
} else if (*m < 0) {
info = 2;
} else if (*n < 0) {
info = 3;
} else if (*lda < max(1,*m)) {
info = 6;
} else if (*incx == 0) {
info = 8;
} else if (*incy == 0) {
info = 11;
}
if (info != 0) {
xerbla_("DGEMV ", &info);
return 0;
}
//
// Quick return if possible.
//
if (*m == 0 || *n == 0 || *alpha == 0. && *beta == 1.) {
return 0;
}
//
// Set LENX and LENY, the lengths of the vectors x and y, and set
// up the start points in X and Y.
//
if (lsame_(trans, "N")) {
lenx = *n;
leny = *m;
} else {
lenx = *m;
leny = *n;
}
if (*incx > 0) {
kx = 1;
} else {
kx = 1 - (lenx - 1) * *incx;
}
if (*incy > 0) {
ky = 1;
} else {
ky = 1 - (leny - 1) * *incy;
}
//
// Start the operations. In this version the elements of A are
// accessed sequentially with one pass through A.
//
// First form y := beta*y.
//
if (*beta != 1.) {
if (*incy == 1) {
if (*beta == 0.) {
i__1 = leny;
for (i__ = 1; i__ <= i__1; ++i__) {
y[i__] = 0.;
// L10:
}
} else {
i__1 = leny;
for (i__ = 1; i__ <= i__1; ++i__) {
y[i__] = *beta * y[i__];
// L20:
}
}
} else {
iy = ky;
if (*beta == 0.) {
i__1 = leny;
for (i__ = 1; i__ <= i__1; ++i__) {
y[iy] = 0.;
iy += *incy;
// L30:
}
} else {
i__1 = leny;
for (i__ = 1; i__ <= i__1; ++i__) {
y[iy] = *beta * y[iy];
iy += *incy;
// L40:
}
}
}
}
if (*alpha == 0.) {
return 0;
}
if (lsame_(trans, "N")) {
//
// Form y := alpha*A*x + y.
//
jx = kx;
if (*incy == 1) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
temp = *alpha * x[jx];
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
y[i__] += temp * a[i__ + j * a_dim1];
// L50:
}
jx += *incx;
// L60:
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
temp = *alpha * x[jx];
iy = ky;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
y[iy] += temp * a[i__ + j * a_dim1];
iy += *incy;
// L70:
}
jx += *incx;
// L80:
}
}
} else {
//
// Form y := alpha*A**T*x + y.
//
jy = ky;
if (*incx == 1) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
temp = 0.;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp += a[i__ + j * a_dim1] * x[i__];
// L90:
}
y[jy] += *alpha * temp;
jy += *incy;
// L100:
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
temp = 0.;
ix = kx;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp += a[i__ + j * a_dim1] * x[ix];
ix += *incx;
// L110:
}
y[jy] += *alpha * temp;
jy += *incy;
// L120:
}
}
}
return 0;
//
// End of DGEMV .
//
} // dgemv_

18599
3rdparty/clapack/src/dgesdd.c vendored Normal file

File diff suppressed because it is too large Load Diff

186
3rdparty/clapack/src/disnan.c vendored Normal file
View File

@@ -0,0 +1,186 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DISNAN tests input for NaN.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DISNAN + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/disnan.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/disnan.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/disnan.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// LOGICAL FUNCTION DISNAN( DIN )
//
// .. Scalar Arguments ..
// DOUBLE PRECISION, INTENT(IN) :: DIN
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DISNAN returns .TRUE. if its argument is NaN, and .FALSE.
//> otherwise. To be replaced by the Fortran 2003 intrinsic in the
//> future.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] DIN
//> \verbatim
//> DIN is DOUBLE PRECISION
//> Input to test for NaN.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date June 2017
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
int disnan_(double *din)
{
// System generated locals
int ret_val;
// Local variables
extern int dlaisnan_(double *, double *);
//
// -- LAPACK auxiliary routine (version 3.7.1) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// June 2017
//
// .. Scalar Arguments ..
// ..
//
// =====================================================================
//
// .. External Functions ..
// ..
// .. Executable Statements ..
ret_val = dlaisnan_(din, din);
return ret_val;
} // disnan_
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
//> \brief \b DLAISNAN tests input for NaN by comparing two arguments for inequality.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLAISNAN + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlaisnan.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlaisnan.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlaisnan.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// LOGICAL FUNCTION DLAISNAN( DIN1, DIN2 )
//
// .. Scalar Arguments ..
// DOUBLE PRECISION, INTENT(IN) :: DIN1, DIN2
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> This routine is not for general use. It exists solely to avoid
//> over-optimization in DISNAN.
//>
//> DLAISNAN checks for NaNs by comparing its two arguments for
//> inequality. NaN is the only floating-point value where NaN != NaN
//> returns .TRUE. To check for NaNs, pass the same variable as both
//> arguments.
//>
//> A compiler must assume that the two arguments are
//> not the same variable, and the test will not be optimized away.
//> Interprocedural or whole-program optimization may delete this
//> test. The ISNAN functions will be replaced by the correct
//> Fortran 03 intrinsic once the intrinsic is widely available.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] DIN1
//> \verbatim
//> DIN1 is DOUBLE PRECISION
//> \endverbatim
//>
//> \param[in] DIN2
//> \verbatim
//> DIN2 is DOUBLE PRECISION
//> Two numbers to compare for inequality.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date June 2017
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
int dlaisnan_(double *din1, double *din2)
{
// System generated locals
int ret_val;
//
// -- LAPACK auxiliary routine (version 3.7.1) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// June 2017
//
// .. Scalar Arguments ..
// ..
//
// =====================================================================
//
// .. Executable Statements ..
ret_val = *din1 != *din2;
return ret_val;
} // dlaisnan_

184
3rdparty/clapack/src/dlacpy.c vendored Normal file
View File

@@ -0,0 +1,184 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DLACPY copies all or part of one two-dimensional array to another.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLACPY + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlacpy.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlacpy.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlacpy.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// SUBROUTINE DLACPY( UPLO, M, N, A, LDA, B, LDB )
//
// .. Scalar Arguments ..
// CHARACTER UPLO
// INTEGER LDA, LDB, M, N
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A( LDA, * ), B( LDB, * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DLACPY copies all or part of a two-dimensional matrix A to another
//> matrix B.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] UPLO
//> \verbatim
//> UPLO is CHARACTER*1
//> Specifies the part of the matrix A to be copied to B.
//> = 'U': Upper triangular part
//> = 'L': Lower triangular part
//> Otherwise: All of the matrix A
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> The number of rows of the matrix A. M >= 0.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The number of columns of the matrix A. N >= 0.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension (LDA,N)
//> The m by n matrix A. If UPLO = 'U', only the upper triangle
//> or trapezoid is accessed; if UPLO = 'L', only the lower
//> triangle or trapezoid is accessed.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> The leading dimension of the array A. LDA >= max(1,M).
//> \endverbatim
//>
//> \param[out] B
//> \verbatim
//> B is DOUBLE PRECISION array, dimension (LDB,N)
//> On exit, B = A in the locations specified by UPLO.
//> \endverbatim
//>
//> \param[in] LDB
//> \verbatim
//> LDB is INTEGER
//> The leading dimension of the array B. LDB >= max(1,M).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
/* Subroutine */ int dlacpy_(char *uplo, int *m, int *n, double *a, int *lda,
double *b, int *ldb)
{
// System generated locals
int a_dim1, a_offset, b_dim1, b_offset, i__1, i__2;
// Local variables
int i__, j;
extern int lsame_(char *, char *);
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Local Scalars ..
// ..
// .. External Functions ..
// ..
// .. Intrinsic Functions ..
// ..
// .. Executable Statements ..
//
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
// Function Body
if (lsame_(uplo, "U")) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = min(j,*m);
for (i__ = 1; i__ <= i__2; ++i__) {
b[i__ + j * b_dim1] = a[i__ + j * a_dim1];
// L10:
}
// L20:
}
} else if (lsame_(uplo, "L")) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = j; i__ <= i__2; ++i__) {
b[i__ + j * b_dim1] = a[i__ + j * a_dim1];
// L30:
}
// L40:
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
b[i__ + j * b_dim1] = a[i__ + j * a_dim1];
// L50:
}
// L60:
}
}
return 0;
//
// End of DLACPY
//
} // dlacpy_

367
3rdparty/clapack/src/dlange.c vendored Normal file
View File

@@ -0,0 +1,367 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DCOMBSSQ adds two scaled sum of squares quantities.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//
// Definition:
// ===========
//
// SUBROUTINE DCOMBSSQ( V1, V2 )
//
// .. Array Arguments ..
// DOUBLE PRECISION V1( 2 ), V2( 2 )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DCOMBSSQ adds two scaled sum of squares quantities, V1 := V1 + V2.
//> That is,
//>
//> V1_scale**2 * V1_sumsq := V1_scale**2 * V1_sumsq
//> + V2_scale**2 * V2_sumsq
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in,out] V1
//> \verbatim
//> V1 is DOUBLE PRECISION array, dimension (2).
//> The first scaled sum.
//> V1(1) = V1_scale, V1(2) = V1_sumsq.
//> \endverbatim
//>
//> \param[in] V2
//> \verbatim
//> V2 is DOUBLE PRECISION array, dimension (2).
//> The second scaled sum.
//> V2(1) = V2_scale, V2(2) = V2_sumsq.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date November 2018
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
/* Subroutine */ int dcombssq_(double *v1, double *v2)
{
// System generated locals
double d__1;
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// November 2018
//
// .. Array Arguments ..
// ..
//
//=====================================================================
//
// .. Parameters ..
// ..
// .. Executable Statements ..
//
// Parameter adjustments
--v2;
--v1;
// Function Body
if (v1[1] >= v2[1]) {
if (v1[1] != 0.) {
// Computing 2nd power
d__1 = v2[1] / v1[1];
v1[2] += d__1 * d__1 * v2[2];
}
} else {
// Computing 2nd power
d__1 = v1[1] / v2[1];
v1[2] = v2[2] + d__1 * d__1 * v1[2];
v1[1] = v2[1];
}
return 0;
//
// End of DCOMBSSQ
//
} // dcombssq_
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
//> \brief \b DLANGE returns the value of the 1-norm, Frobenius norm, infinity-norm, or the largest absolute value of any element of a general rectangular matrix.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLANGE + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlange.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlange.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlange.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// DOUBLE PRECISION FUNCTION DLANGE( NORM, M, N, A, LDA, WORK )
//
// .. Scalar Arguments ..
// CHARACTER NORM
// INTEGER LDA, M, N
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A( LDA, * ), WORK( * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DLANGE returns the value of the one norm, or the Frobenius norm, or
//> the infinity norm, or the element of largest absolute value of a
//> real matrix A.
//> \endverbatim
//>
//> \return DLANGE
//> \verbatim
//>
//> DLANGE = ( max(abs(A(i,j))), NORM = 'M' or 'm'
//> (
//> ( norm1(A), NORM = '1', 'O' or 'o'
//> (
//> ( normI(A), NORM = 'I' or 'i'
//> (
//> ( normF(A), NORM = 'F', 'f', 'E' or 'e'
//>
//> where norm1 denotes the one norm of a matrix (maximum column sum),
//> normI denotes the infinity norm of a matrix (maximum row sum) and
//> normF denotes the Frobenius norm of a matrix (square root of sum of
//> squares). Note that max(abs(A(i,j))) is not a consistent matrix norm.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] NORM
//> \verbatim
//> NORM is CHARACTER*1
//> Specifies the value to be returned in DLANGE as described
//> above.
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> The number of rows of the matrix A. M >= 0. When M = 0,
//> DLANGE is set to zero.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The number of columns of the matrix A. N >= 0. When N = 0,
//> DLANGE is set to zero.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension (LDA,N)
//> The m by n matrix A.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> The leading dimension of the array A. LDA >= max(M,1).
//> \endverbatim
//>
//> \param[out] WORK
//> \verbatim
//> WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)),
//> where LWORK >= M when NORM = 'I'; otherwise, WORK is not
//> referenced.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup doubleGEauxiliary
//
// =====================================================================
double dlange_(char *norm, int *m, int *n, double *a, int *lda, double *work)
{
// Table of constant values
int c__1 = 1;
// System generated locals
int a_dim1, a_offset, i__1, i__2;
double ret_val, d__1;
// Local variables
extern /* Subroutine */ int dcombssq_(double *, double *);
int i__, j;
double sum, ssq[2], temp;
extern int lsame_(char *, char *);
double value;
extern int disnan_(double *);
extern /* Subroutine */ int dlassq_(int *, double *, int *, double *,
double *);
double colssq[2];
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
//=====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. Local Arrays ..
// ..
// .. External Subroutines ..
// ..
// .. External Functions ..
// ..
// .. Intrinsic Functions ..
// ..
// .. Executable Statements ..
//
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--work;
// Function Body
if (min(*m,*n) == 0) {
value = 0.;
} else if (lsame_(norm, "M")) {
//
// Find max(abs(A(i,j))).
//
value = 0.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = (d__1 = a[i__ + j * a_dim1], abs(d__1));
if (value < temp || disnan_(&temp)) {
value = temp;
}
// L10:
}
// L20:
}
} else if (lsame_(norm, "O") || *(unsigned char *)norm == '1') {
//
// Find norm1(A).
//
value = 0.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = 0.;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
sum += (d__1 = a[i__ + j * a_dim1], abs(d__1));
// L30:
}
if (value < sum || disnan_(&sum)) {
value = sum;
}
// L40:
}
} else if (lsame_(norm, "I")) {
//
// Find normI(A).
//
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
work[i__] = 0.;
// L50:
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
work[i__] += (d__1 = a[i__ + j * a_dim1], abs(d__1));
// L60:
}
// L70:
}
value = 0.;
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = work[i__];
if (value < temp || disnan_(&temp)) {
value = temp;
}
// L80:
}
} else if (lsame_(norm, "F") || lsame_(norm, "E")) {
//
// Find normF(A).
// SSQ(1) is scale
// SSQ(2) is sum-of-squares
// For better accuracy, sum each column separately.
//
ssq[0] = 0.;
ssq[1] = 1.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
colssq[0] = 0.;
colssq[1] = 1.;
dlassq_(m, &a[j * a_dim1 + 1], &c__1, colssq, &colssq[1]);
dcombssq_(ssq, colssq);
// L90:
}
value = ssq[0] * sqrt(ssq[1]);
}
ret_val = value;
return ret_val;
//
// End of DLANGE
//
} // dlange_

125
3rdparty/clapack/src/dlapy2.c vendored Normal file
View File

@@ -0,0 +1,125 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DLAPY2 returns sqrt(x2+y2).
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLAPY2 + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlapy2.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlapy2.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlapy2.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// DOUBLE PRECISION FUNCTION DLAPY2( X, Y )
//
// .. Scalar Arguments ..
// DOUBLE PRECISION X, Y
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DLAPY2 returns sqrt(x**2+y**2), taking care not to cause unnecessary
//> overflow.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] X
//> \verbatim
//> X is DOUBLE PRECISION
//> \endverbatim
//>
//> \param[in] Y
//> \verbatim
//> Y is DOUBLE PRECISION
//> X and Y specify the values x and y.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date June 2017
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
double dlapy2_(double *x, double *y)
{
// System generated locals
double ret_val, d__1;
// Local variables
int x_is_nan__, y_is_nan__;
double w, z__, xabs, yabs;
extern int disnan_(double *);
//
// -- LAPACK auxiliary routine (version 3.7.1) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// June 2017
//
// .. Scalar Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. External Functions ..
// ..
// .. Intrinsic Functions ..
// ..
// .. Executable Statements ..
//
x_is_nan__ = disnan_(x);
y_is_nan__ = disnan_(y);
if (x_is_nan__) {
ret_val = *x;
}
if (y_is_nan__) {
ret_val = *y;
}
if (! (x_is_nan__ || y_is_nan__)) {
xabs = abs(*x);
yabs = abs(*y);
w = max(xabs,yabs);
z__ = min(xabs,yabs);
if (z__ == 0.) {
ret_val = w;
} else {
// Computing 2nd power
d__1 = z__ / w;
ret_val = w * sqrt(d__1 * d__1 + 1.);
}
}
return ret_val;
//
// End of DLAPY2
//
} // dlapy2_

768
3rdparty/clapack/src/dlarf.c vendored Normal file
View File

@@ -0,0 +1,768 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DGER
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
// Definition:
// ===========
//
// SUBROUTINE DGER(M,N,ALPHA,X,INCX,Y,INCY,A,LDA)
//
// .. Scalar Arguments ..
// DOUBLE PRECISION ALPHA
// INTEGER INCX,INCY,LDA,M,N
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A(LDA,*),X(*),Y(*)
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DGER performs the rank 1 operation
//>
//> A := alpha*x*y**T + A,
//>
//> where alpha is a scalar, x is an m element vector, y is an n element
//> vector and A is an m by n matrix.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> On entry, M specifies the number of rows of the matrix A.
//> M must be at least zero.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> On entry, N specifies the number of columns of the matrix A.
//> N must be at least zero.
//> \endverbatim
//>
//> \param[in] ALPHA
//> \verbatim
//> ALPHA is DOUBLE PRECISION.
//> On entry, ALPHA specifies the scalar alpha.
//> \endverbatim
//>
//> \param[in] X
//> \verbatim
//> X is DOUBLE PRECISION array, dimension at least
//> ( 1 + ( m - 1 )*abs( INCX ) ).
//> Before entry, the incremented array X must contain the m
//> element vector x.
//> \endverbatim
//>
//> \param[in] INCX
//> \verbatim
//> INCX is INTEGER
//> On entry, INCX specifies the increment for the elements of
//> X. INCX must not be zero.
//> \endverbatim
//>
//> \param[in] Y
//> \verbatim
//> Y is DOUBLE PRECISION array, dimension at least
//> ( 1 + ( n - 1 )*abs( INCY ) ).
//> Before entry, the incremented array Y must contain the n
//> element vector y.
//> \endverbatim
//>
//> \param[in] INCY
//> \verbatim
//> INCY is INTEGER
//> On entry, INCY specifies the increment for the elements of
//> Y. INCY must not be zero.
//> \endverbatim
//>
//> \param[in,out] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension ( LDA, N )
//> Before entry, the leading m by n part of the array A must
//> contain the matrix of coefficients. On exit, A is
//> overwritten by the updated matrix.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> On entry, LDA specifies the first dimension of A as declared
//> in the calling (sub) program. LDA must be at least
//> max( 1, m ).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup double_blas_level2
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> Level 2 Blas routine.
//>
//> -- Written on 22-October-1986.
//> Jack Dongarra, Argonne National Lab.
//> Jeremy Du Croz, Nag Central Office.
//> Sven Hammarling, Nag Central Office.
//> Richard Hanson, Sandia National Labs.
//> \endverbatim
//>
// =====================================================================
/* Subroutine */ int dger_(int *m, int *n, double *alpha, double *x, int *
incx, double *y, int *incy, double *a, int *lda)
{
// System generated locals
int a_dim1, a_offset, i__1, i__2;
// Local variables
int i__, j, ix, jy, kx, info;
double temp;
extern /* Subroutine */ int xerbla_(char *, int *);
//
// -- Reference BLAS level2 routine (version 3.7.0) --
// -- Reference BLAS is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. External Subroutines ..
// ..
// .. Intrinsic Functions ..
// ..
//
// Test the input parameters.
//
// Parameter adjustments
--x;
--y;
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
// Function Body
info = 0;
if (*m < 0) {
info = 1;
} else if (*n < 0) {
info = 2;
} else if (*incx == 0) {
info = 5;
} else if (*incy == 0) {
info = 7;
} else if (*lda < max(1,*m)) {
info = 9;
}
if (info != 0) {
xerbla_("DGER ", &info);
return 0;
}
//
// Quick return if possible.
//
if (*m == 0 || *n == 0 || *alpha == 0.) {
return 0;
}
//
// Start the operations. In this version the elements of A are
// accessed sequentially with one pass through A.
//
if (*incy > 0) {
jy = 1;
} else {
jy = 1 - (*n - 1) * *incy;
}
if (*incx == 1) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (y[jy] != 0.) {
temp = *alpha * y[jy];
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] += x[i__] * temp;
// L10:
}
}
jy += *incy;
// L20:
}
} else {
if (*incx > 0) {
kx = 1;
} else {
kx = 1 - (*m - 1) * *incx;
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (y[jy] != 0.) {
temp = *alpha * y[jy];
ix = kx;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] += x[ix] * temp;
ix += *incx;
// L30:
}
}
jy += *incy;
// L40:
}
}
return 0;
//
// End of DGER .
//
} // dger_
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
//> \brief \b DLARF applies an elementary reflector to a general rectangular matrix.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLARF + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlarf.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlarf.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlarf.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// SUBROUTINE DLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
//
// .. Scalar Arguments ..
// CHARACTER SIDE
// INTEGER INCV, LDC, M, N
// DOUBLE PRECISION TAU
// ..
// .. Array Arguments ..
// DOUBLE PRECISION C( LDC, * ), V( * ), WORK( * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DLARF applies a real elementary reflector H to a real m by n matrix
//> C, from either the left or the right. H is represented in the form
//>
//> H = I - tau * v * v**T
//>
//> where tau is a real scalar and v is a real vector.
//>
//> If tau = 0, then H is taken to be the unit matrix.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] SIDE
//> \verbatim
//> SIDE is CHARACTER*1
//> = 'L': form H * C
//> = 'R': form C * H
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> The number of rows of the matrix C.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The number of columns of the matrix C.
//> \endverbatim
//>
//> \param[in] V
//> \verbatim
//> V is DOUBLE PRECISION array, dimension
//> (1 + (M-1)*abs(INCV)) if SIDE = 'L'
//> or (1 + (N-1)*abs(INCV)) if SIDE = 'R'
//> The vector v in the representation of H. V is not used if
//> TAU = 0.
//> \endverbatim
//>
//> \param[in] INCV
//> \verbatim
//> INCV is INTEGER
//> The increment between elements of v. INCV <> 0.
//> \endverbatim
//>
//> \param[in] TAU
//> \verbatim
//> TAU is DOUBLE PRECISION
//> The value tau in the representation of H.
//> \endverbatim
//>
//> \param[in,out] C
//> \verbatim
//> C is DOUBLE PRECISION array, dimension (LDC,N)
//> On entry, the m by n matrix C.
//> On exit, C is overwritten by the matrix H * C if SIDE = 'L',
//> or C * H if SIDE = 'R'.
//> \endverbatim
//>
//> \param[in] LDC
//> \verbatim
//> LDC is INTEGER
//> The leading dimension of the array C. LDC >= max(1,M).
//> \endverbatim
//>
//> \param[out] WORK
//> \verbatim
//> WORK is DOUBLE PRECISION array, dimension
//> (N) if SIDE = 'L'
//> or (M) if SIDE = 'R'
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup doubleOTHERauxiliary
//
// =====================================================================
/* Subroutine */ int dlarf_(char *side, int *m, int *n, double *v, int *incv,
double *tau, double *c__, int *ldc, double *work)
{
// Table of constant values
double c_b4 = 1.;
double c_b5 = 0.;
int c__1 = 1;
// System generated locals
int c_dim1, c_offset;
double d__1;
// Local variables
int i__;
int applyleft;
extern /* Subroutine */ int dger_(int *, int *, double *, double *, int *,
double *, int *, double *, int *);
extern int lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, int *, int *, double *, double
*, int *, double *, int *, double *, double *, int *);
int lastc, lastv;
extern int iladlc_(int *, int *, double *, int *), iladlr_(int *, int *,
double *, int *);
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. External Subroutines ..
// ..
// .. External Functions ..
// ..
// .. Executable Statements ..
//
// Parameter adjustments
--v;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
// Function Body
applyleft = lsame_(side, "L");
lastv = 0;
lastc = 0;
if (*tau != 0.) {
// Set up variables for scanning V. LASTV begins pointing to the end
// of V.
if (applyleft) {
lastv = *m;
} else {
lastv = *n;
}
if (*incv > 0) {
i__ = (lastv - 1) * *incv + 1;
} else {
i__ = 1;
}
// Look for the last non-zero row in V.
while(lastv > 0 && v[i__] == 0.) {
--lastv;
i__ -= *incv;
}
if (applyleft) {
// Scan for the last non-zero column in C(1:lastv,:).
lastc = iladlc_(&lastv, n, &c__[c_offset], ldc);
} else {
// Scan for the last non-zero row in C(:,1:lastv).
lastc = iladlr_(m, &lastv, &c__[c_offset], ldc);
}
}
// Note that lastc.eq.0 renders the BLAS operations null; no special
// case is needed at this level.
if (applyleft) {
//
// Form H * C
//
if (lastv > 0) {
//
// w(1:lastc,1) := C(1:lastv,1:lastc)**T * v(1:lastv,1)
//
dgemv_("Transpose", &lastv, &lastc, &c_b4, &c__[c_offset], ldc, &
v[1], incv, &c_b5, &work[1], &c__1);
//
// C(1:lastv,1:lastc) := C(...) - v(1:lastv,1) * w(1:lastc,1)**T
//
d__1 = -(*tau);
dger_(&lastv, &lastc, &d__1, &v[1], incv, &work[1], &c__1, &c__[
c_offset], ldc);
}
} else {
//
// Form C * H
//
if (lastv > 0) {
//
// w(1:lastc,1) := C(1:lastc,1:lastv) * v(1:lastv,1)
//
dgemv_("No transpose", &lastc, &lastv, &c_b4, &c__[c_offset], ldc,
&v[1], incv, &c_b5, &work[1], &c__1);
//
// C(1:lastc,1:lastv) := C(...) - w(1:lastc,1) * v(1:lastv,1)**T
//
d__1 = -(*tau);
dger_(&lastc, &lastv, &d__1, &work[1], &c__1, &v[1], incv, &c__[
c_offset], ldc);
}
}
return 0;
//
// End of DLARF
//
} // dlarf_
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
//> \brief \b ILADLC scans a matrix for its last non-zero column.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download ILADLC + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/iladlc.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/iladlc.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/iladlc.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// INTEGER FUNCTION ILADLC( M, N, A, LDA )
//
// .. Scalar Arguments ..
// INTEGER M, N, LDA
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A( LDA, * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> ILADLC scans A for its last non-zero column.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> The number of rows of the matrix A.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The number of columns of the matrix A.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension (LDA,N)
//> The m by n matrix A.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> The leading dimension of the array A. LDA >= max(1,M).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
int iladlc_(int *m, int *n, double *a, int *lda)
{
// System generated locals
int a_dim1, a_offset, ret_val, i__1;
// Local variables
int i__;
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. Executable Statements ..
//
// Quick test for the common case where one corner is non-zero.
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
// Function Body
if (*n == 0) {
ret_val = *n;
} else if (a[*n * a_dim1 + 1] != 0. || a[*m + *n * a_dim1] != 0.) {
ret_val = *n;
} else {
// Now scan each column from the end, returning with the first non-zero.
for (ret_val = *n; ret_val >= 1; --ret_val) {
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
if (a[i__ + ret_val * a_dim1] != 0.) {
return ret_val;
}
}
}
}
return ret_val;
} // iladlc_
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
//> \brief \b ILADLR scans a matrix for its last non-zero row.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download ILADLR + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/iladlr.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/iladlr.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/iladlr.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// INTEGER FUNCTION ILADLR( M, N, A, LDA )
//
// .. Scalar Arguments ..
// INTEGER M, N, LDA
// ..
// .. Array Arguments ..
// DOUBLE PRECISION A( LDA, * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> ILADLR scans A for its last non-zero row.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> The number of rows of the matrix A.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The number of columns of the matrix A.
//> \endverbatim
//>
//> \param[in] A
//> \verbatim
//> A is DOUBLE PRECISION array, dimension (LDA,N)
//> The m by n matrix A.
//> \endverbatim
//>
//> \param[in] LDA
//> \verbatim
//> LDA is INTEGER
//> The leading dimension of the array A. LDA >= max(1,M).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date December 2016
//
//> \ingroup OTHERauxiliary
//
// =====================================================================
int iladlr_(int *m, int *n, double *a, int *lda)
{
// System generated locals
int a_dim1, a_offset, ret_val, i__1;
// Local variables
int i__, j;
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// December 2016
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. Executable Statements ..
//
// Quick test for the common case where one corner is non-zero.
// Parameter adjustments
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
// Function Body
if (*m == 0) {
ret_val = *m;
} else if (a[*m + a_dim1] != 0. || a[*m + *n * a_dim1] != 0.) {
ret_val = *m;
} else {
// Scan up each column tracking the last zero row seen.
ret_val = 0;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__ = *m;
while(a[max(i__,1) + j * a_dim1] == 0. && i__ >= 1) {
--i__;
}
ret_val = max(ret_val,i__);
}
}
return ret_val;
} // iladlr_

824
3rdparty/clapack/src/dlarfb.c vendored Normal file
View File

@@ -0,0 +1,824 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DLARFB applies a block reflector or its transpose to a general rectangular matrix.
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLARFB + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlarfb.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlarfb.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlarfb.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// SUBROUTINE DLARFB( SIDE, TRANS, DIRECT, STOREV, M, N, K, V, LDV,
// T, LDT, C, LDC, WORK, LDWORK )
//
// .. Scalar Arguments ..
// CHARACTER DIRECT, SIDE, STOREV, TRANS
// INTEGER K, LDC, LDT, LDV, LDWORK, M, N
// ..
// .. Array Arguments ..
// DOUBLE PRECISION C( LDC, * ), T( LDT, * ), V( LDV, * ),
// $ WORK( LDWORK, * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DLARFB applies a real block reflector H or its transpose H**T to a
//> real m by n matrix C, from either the left or the right.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] SIDE
//> \verbatim
//> SIDE is CHARACTER*1
//> = 'L': apply H or H**T from the Left
//> = 'R': apply H or H**T from the Right
//> \endverbatim
//>
//> \param[in] TRANS
//> \verbatim
//> TRANS is CHARACTER*1
//> = 'N': apply H (No transpose)
//> = 'T': apply H**T (Transpose)
//> \endverbatim
//>
//> \param[in] DIRECT
//> \verbatim
//> DIRECT is CHARACTER*1
//> Indicates how H is formed from a product of elementary
//> reflectors
//> = 'F': H = H(1) H(2) . . . H(k) (Forward)
//> = 'B': H = H(k) . . . H(2) H(1) (Backward)
//> \endverbatim
//>
//> \param[in] STOREV
//> \verbatim
//> STOREV is CHARACTER*1
//> Indicates how the vectors which define the elementary
//> reflectors are stored:
//> = 'C': Columnwise
//> = 'R': Rowwise
//> \endverbatim
//>
//> \param[in] M
//> \verbatim
//> M is INTEGER
//> The number of rows of the matrix C.
//> \endverbatim
//>
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The number of columns of the matrix C.
//> \endverbatim
//>
//> \param[in] K
//> \verbatim
//> K is INTEGER
//> The order of the matrix T (= the number of elementary
//> reflectors whose product defines the block reflector).
//> If SIDE = 'L', M >= K >= 0;
//> if SIDE = 'R', N >= K >= 0.
//> \endverbatim
//>
//> \param[in] V
//> \verbatim
//> V is DOUBLE PRECISION array, dimension
//> (LDV,K) if STOREV = 'C'
//> (LDV,M) if STOREV = 'R' and SIDE = 'L'
//> (LDV,N) if STOREV = 'R' and SIDE = 'R'
//> The matrix V. See Further Details.
//> \endverbatim
//>
//> \param[in] LDV
//> \verbatim
//> LDV is INTEGER
//> The leading dimension of the array V.
//> If STOREV = 'C' and SIDE = 'L', LDV >= max(1,M);
//> if STOREV = 'C' and SIDE = 'R', LDV >= max(1,N);
//> if STOREV = 'R', LDV >= K.
//> \endverbatim
//>
//> \param[in] T
//> \verbatim
//> T is DOUBLE PRECISION array, dimension (LDT,K)
//> The triangular k by k matrix T in the representation of the
//> block reflector.
//> \endverbatim
//>
//> \param[in] LDT
//> \verbatim
//> LDT is INTEGER
//> The leading dimension of the array T. LDT >= K.
//> \endverbatim
//>
//> \param[in,out] C
//> \verbatim
//> C is DOUBLE PRECISION array, dimension (LDC,N)
//> On entry, the m by n matrix C.
//> On exit, C is overwritten by H*C or H**T*C or C*H or C*H**T.
//> \endverbatim
//>
//> \param[in] LDC
//> \verbatim
//> LDC is INTEGER
//> The leading dimension of the array C. LDC >= max(1,M).
//> \endverbatim
//>
//> \param[out] WORK
//> \verbatim
//> WORK is DOUBLE PRECISION array, dimension (LDWORK,K)
//> \endverbatim
//>
//> \param[in] LDWORK
//> \verbatim
//> LDWORK is INTEGER
//> The leading dimension of the array WORK.
//> If SIDE = 'L', LDWORK >= max(1,N);
//> if SIDE = 'R', LDWORK >= max(1,M).
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date June 2013
//
//> \ingroup doubleOTHERauxiliary
//
//> \par Further Details:
// =====================
//>
//> \verbatim
//>
//> The shape of the matrix V and the storage of the vectors which define
//> the H(i) is best illustrated by the following example with n = 5 and
//> k = 3. The elements equal to 1 are not stored; the corresponding
//> array elements are modified but restored on exit. The rest of the
//> array is not used.
//>
//> DIRECT = 'F' and STOREV = 'C': DIRECT = 'F' and STOREV = 'R':
//>
//> V = ( 1 ) V = ( 1 v1 v1 v1 v1 )
//> ( v1 1 ) ( 1 v2 v2 v2 )
//> ( v1 v2 1 ) ( 1 v3 v3 )
//> ( v1 v2 v3 )
//> ( v1 v2 v3 )
//>
//> DIRECT = 'B' and STOREV = 'C': DIRECT = 'B' and STOREV = 'R':
//>
//> V = ( v1 v2 v3 ) V = ( v1 v1 1 )
//> ( v1 v2 v3 ) ( v2 v2 v2 1 )
//> ( 1 v2 v3 ) ( v3 v3 v3 v3 1 )
//> ( 1 v3 )
//> ( 1 )
//> \endverbatim
//>
// =====================================================================
/* Subroutine */ int dlarfb_(char *side, char *trans, char *direct, char *
storev, int *m, int *n, int *k, double *v, int *ldv, double *t, int *
ldt, double *c__, int *ldc, double *work, int *ldwork)
{
// Table of constant values
int c__1 = 1;
double c_b14 = 1.;
double c_b25 = -1.;
// System generated locals
int c_dim1, c_offset, t_dim1, t_offset, v_dim1, v_offset, work_dim1,
work_offset, i__1, i__2;
// Local variables
int i__, j;
extern /* Subroutine */ int dgemm_(char *, char *, int *, int *, int *,
double *, double *, int *, double *, int *, double *, double *,
int *);
extern int lsame_(char *, char *);
extern /* Subroutine */ int dcopy_(int *, double *, int *, double *, int *
), dtrmm_(char *, char *, char *, char *, int *, int *, double *,
double *, int *, double *, int *);
char transt[1+1]={'\0'};
//
// -- LAPACK auxiliary routine (version 3.7.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// June 2013
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. External Functions ..
// ..
// .. External Subroutines ..
// ..
// .. Executable Statements ..
//
// Quick return if possible
//
// Parameter adjustments
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
work_dim1 = *ldwork;
work_offset = 1 + work_dim1;
work -= work_offset;
// Function Body
if (*m <= 0 || *n <= 0) {
return 0;
}
if (lsame_(trans, "N")) {
*(unsigned char *)transt = 'T';
} else {
*(unsigned char *)transt = 'N';
}
if (lsame_(storev, "C")) {
if (lsame_(direct, "F")) {
//
// Let V = ( V1 ) (first K rows)
// ( V2 )
// where V1 is unit lower triangular.
//
if (lsame_(side, "L")) {
//
// Form H * C or H**T * C where C = ( C1 )
// ( C2 )
//
// W := C**T * V = (C1**T * V1 + C2**T * V2) (stored in WORK)
//
// W := C1**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(n, &c__[j + c_dim1], ldc, &work[j * work_dim1 + 1],
&c__1);
// L10:
}
//
// W := W * V1
//
dtrmm_("Right", "Lower", "No transpose", "Unit", n, k, &c_b14,
&v[v_offset], ldv, &work[work_offset], ldwork);
if (*m > *k) {
//
// W := W + C2**T * V2
//
i__1 = *m - *k;
dgemm_("Transpose", "No transpose", n, k, &i__1, &c_b14, &
c__[*k + 1 + c_dim1], ldc, &v[*k + 1 + v_dim1],
ldv, &c_b14, &work[work_offset], ldwork);
}
//
// W := W * T**T or W * T
//
dtrmm_("Right", "Upper", transt, "Non-unit", n, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - V * W**T
//
if (*m > *k) {
//
// C2 := C2 - V2 * W**T
//
i__1 = *m - *k;
dgemm_("No transpose", "Transpose", &i__1, n, k, &c_b25, &
v[*k + 1 + v_dim1], ldv, &work[work_offset],
ldwork, &c_b14, &c__[*k + 1 + c_dim1], ldc);
}
//
// W := W * V1**T
//
dtrmm_("Right", "Lower", "Transpose", "Unit", n, k, &c_b14, &
v[v_offset], ldv, &work[work_offset], ldwork);
//
// C1 := C1 - W**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[j + i__ * c_dim1] -= work[i__ + j * work_dim1];
// L20:
}
// L30:
}
} else if (lsame_(side, "R")) {
//
// Form C * H or C * H**T where C = ( C1 C2 )
//
// W := C * V = (C1*V1 + C2*V2) (stored in WORK)
//
// W := C1
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(m, &c__[j * c_dim1 + 1], &c__1, &work[j *
work_dim1 + 1], &c__1);
// L40:
}
//
// W := W * V1
//
dtrmm_("Right", "Lower", "No transpose", "Unit", m, k, &c_b14,
&v[v_offset], ldv, &work[work_offset], ldwork);
if (*n > *k) {
//
// W := W + C2 * V2
//
i__1 = *n - *k;
dgemm_("No transpose", "No transpose", m, k, &i__1, &
c_b14, &c__[(*k + 1) * c_dim1 + 1], ldc, &v[*k +
1 + v_dim1], ldv, &c_b14, &work[work_offset],
ldwork);
}
//
// W := W * T or W * T**T
//
dtrmm_("Right", "Upper", trans, "Non-unit", m, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - W * V**T
//
if (*n > *k) {
//
// C2 := C2 - W * V2**T
//
i__1 = *n - *k;
dgemm_("No transpose", "Transpose", m, &i__1, k, &c_b25, &
work[work_offset], ldwork, &v[*k + 1 + v_dim1],
ldv, &c_b14, &c__[(*k + 1) * c_dim1 + 1], ldc);
}
//
// W := W * V1**T
//
dtrmm_("Right", "Lower", "Transpose", "Unit", m, k, &c_b14, &
v[v_offset], ldv, &work[work_offset], ldwork);
//
// C1 := C1 - W
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] -= work[i__ + j * work_dim1];
// L50:
}
// L60:
}
}
} else {
//
// Let V = ( V1 )
// ( V2 ) (last K rows)
// where V2 is unit upper triangular.
//
if (lsame_(side, "L")) {
//
// Form H * C or H**T * C where C = ( C1 )
// ( C2 )
//
// W := C**T * V = (C1**T * V1 + C2**T * V2) (stored in WORK)
//
// W := C2**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(n, &c__[*m - *k + j + c_dim1], ldc, &work[j *
work_dim1 + 1], &c__1);
// L70:
}
//
// W := W * V2
//
dtrmm_("Right", "Upper", "No transpose", "Unit", n, k, &c_b14,
&v[*m - *k + 1 + v_dim1], ldv, &work[work_offset],
ldwork);
if (*m > *k) {
//
// W := W + C1**T * V1
//
i__1 = *m - *k;
dgemm_("Transpose", "No transpose", n, k, &i__1, &c_b14, &
c__[c_offset], ldc, &v[v_offset], ldv, &c_b14, &
work[work_offset], ldwork);
}
//
// W := W * T**T or W * T
//
dtrmm_("Right", "Lower", transt, "Non-unit", n, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - V * W**T
//
if (*m > *k) {
//
// C1 := C1 - V1 * W**T
//
i__1 = *m - *k;
dgemm_("No transpose", "Transpose", &i__1, n, k, &c_b25, &
v[v_offset], ldv, &work[work_offset], ldwork, &
c_b14, &c__[c_offset], ldc);
}
//
// W := W * V2**T
//
dtrmm_("Right", "Upper", "Transpose", "Unit", n, k, &c_b14, &
v[*m - *k + 1 + v_dim1], ldv, &work[work_offset],
ldwork);
//
// C2 := C2 - W**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[*m - *k + j + i__ * c_dim1] -= work[i__ + j *
work_dim1];
// L80:
}
// L90:
}
} else if (lsame_(side, "R")) {
//
// Form C * H or C * H**T where C = ( C1 C2 )
//
// W := C * V = (C1*V1 + C2*V2) (stored in WORK)
//
// W := C2
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(m, &c__[(*n - *k + j) * c_dim1 + 1], &c__1, &work[
j * work_dim1 + 1], &c__1);
// L100:
}
//
// W := W * V2
//
dtrmm_("Right", "Upper", "No transpose", "Unit", m, k, &c_b14,
&v[*n - *k + 1 + v_dim1], ldv, &work[work_offset],
ldwork);
if (*n > *k) {
//
// W := W + C1 * V1
//
i__1 = *n - *k;
dgemm_("No transpose", "No transpose", m, k, &i__1, &
c_b14, &c__[c_offset], ldc, &v[v_offset], ldv, &
c_b14, &work[work_offset], ldwork);
}
//
// W := W * T or W * T**T
//
dtrmm_("Right", "Lower", trans, "Non-unit", m, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - W * V**T
//
if (*n > *k) {
//
// C1 := C1 - W * V1**T
//
i__1 = *n - *k;
dgemm_("No transpose", "Transpose", m, &i__1, k, &c_b25, &
work[work_offset], ldwork, &v[v_offset], ldv, &
c_b14, &c__[c_offset], ldc);
}
//
// W := W * V2**T
//
dtrmm_("Right", "Upper", "Transpose", "Unit", m, k, &c_b14, &
v[*n - *k + 1 + v_dim1], ldv, &work[work_offset],
ldwork);
//
// C2 := C2 - W
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + (*n - *k + j) * c_dim1] -= work[i__ + j *
work_dim1];
// L110:
}
// L120:
}
}
}
} else if (lsame_(storev, "R")) {
if (lsame_(direct, "F")) {
//
// Let V = ( V1 V2 ) (V1: first K columns)
// where V1 is unit upper triangular.
//
if (lsame_(side, "L")) {
//
// Form H * C or H**T * C where C = ( C1 )
// ( C2 )
//
// W := C**T * V**T = (C1**T * V1**T + C2**T * V2**T) (stored in WORK)
//
// W := C1**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(n, &c__[j + c_dim1], ldc, &work[j * work_dim1 + 1],
&c__1);
// L130:
}
//
// W := W * V1**T
//
dtrmm_("Right", "Upper", "Transpose", "Unit", n, k, &c_b14, &
v[v_offset], ldv, &work[work_offset], ldwork);
if (*m > *k) {
//
// W := W + C2**T * V2**T
//
i__1 = *m - *k;
dgemm_("Transpose", "Transpose", n, k, &i__1, &c_b14, &
c__[*k + 1 + c_dim1], ldc, &v[(*k + 1) * v_dim1 +
1], ldv, &c_b14, &work[work_offset], ldwork);
}
//
// W := W * T**T or W * T
//
dtrmm_("Right", "Upper", transt, "Non-unit", n, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - V**T * W**T
//
if (*m > *k) {
//
// C2 := C2 - V2**T * W**T
//
i__1 = *m - *k;
dgemm_("Transpose", "Transpose", &i__1, n, k, &c_b25, &v[(
*k + 1) * v_dim1 + 1], ldv, &work[work_offset],
ldwork, &c_b14, &c__[*k + 1 + c_dim1], ldc);
}
//
// W := W * V1
//
dtrmm_("Right", "Upper", "No transpose", "Unit", n, k, &c_b14,
&v[v_offset], ldv, &work[work_offset], ldwork);
//
// C1 := C1 - W**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[j + i__ * c_dim1] -= work[i__ + j * work_dim1];
// L140:
}
// L150:
}
} else if (lsame_(side, "R")) {
//
// Form C * H or C * H**T where C = ( C1 C2 )
//
// W := C * V**T = (C1*V1**T + C2*V2**T) (stored in WORK)
//
// W := C1
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(m, &c__[j * c_dim1 + 1], &c__1, &work[j *
work_dim1 + 1], &c__1);
// L160:
}
//
// W := W * V1**T
//
dtrmm_("Right", "Upper", "Transpose", "Unit", m, k, &c_b14, &
v[v_offset], ldv, &work[work_offset], ldwork);
if (*n > *k) {
//
// W := W + C2 * V2**T
//
i__1 = *n - *k;
dgemm_("No transpose", "Transpose", m, k, &i__1, &c_b14, &
c__[(*k + 1) * c_dim1 + 1], ldc, &v[(*k + 1) *
v_dim1 + 1], ldv, &c_b14, &work[work_offset],
ldwork);
}
//
// W := W * T or W * T**T
//
dtrmm_("Right", "Upper", trans, "Non-unit", m, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - W * V
//
if (*n > *k) {
//
// C2 := C2 - W * V2
//
i__1 = *n - *k;
dgemm_("No transpose", "No transpose", m, &i__1, k, &
c_b25, &work[work_offset], ldwork, &v[(*k + 1) *
v_dim1 + 1], ldv, &c_b14, &c__[(*k + 1) * c_dim1
+ 1], ldc);
}
//
// W := W * V1
//
dtrmm_("Right", "Upper", "No transpose", "Unit", m, k, &c_b14,
&v[v_offset], ldv, &work[work_offset], ldwork);
//
// C1 := C1 - W
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] -= work[i__ + j * work_dim1];
// L170:
}
// L180:
}
}
} else {
//
// Let V = ( V1 V2 ) (V2: last K columns)
// where V2 is unit lower triangular.
//
if (lsame_(side, "L")) {
//
// Form H * C or H**T * C where C = ( C1 )
// ( C2 )
//
// W := C**T * V**T = (C1**T * V1**T + C2**T * V2**T) (stored in WORK)
//
// W := C2**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(n, &c__[*m - *k + j + c_dim1], ldc, &work[j *
work_dim1 + 1], &c__1);
// L190:
}
//
// W := W * V2**T
//
dtrmm_("Right", "Lower", "Transpose", "Unit", n, k, &c_b14, &
v[(*m - *k + 1) * v_dim1 + 1], ldv, &work[work_offset]
, ldwork);
if (*m > *k) {
//
// W := W + C1**T * V1**T
//
i__1 = *m - *k;
dgemm_("Transpose", "Transpose", n, k, &i__1, &c_b14, &
c__[c_offset], ldc, &v[v_offset], ldv, &c_b14, &
work[work_offset], ldwork);
}
//
// W := W * T**T or W * T
//
dtrmm_("Right", "Lower", transt, "Non-unit", n, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - V**T * W**T
//
if (*m > *k) {
//
// C1 := C1 - V1**T * W**T
//
i__1 = *m - *k;
dgemm_("Transpose", "Transpose", &i__1, n, k, &c_b25, &v[
v_offset], ldv, &work[work_offset], ldwork, &
c_b14, &c__[c_offset], ldc);
}
//
// W := W * V2
//
dtrmm_("Right", "Lower", "No transpose", "Unit", n, k, &c_b14,
&v[(*m - *k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork);
//
// C2 := C2 - W**T
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[*m - *k + j + i__ * c_dim1] -= work[i__ + j *
work_dim1];
// L200:
}
// L210:
}
} else if (lsame_(side, "R")) {
//
// Form C * H or C * H' where C = ( C1 C2 )
//
// W := C * V**T = (C1*V1**T + C2*V2**T) (stored in WORK)
//
// W := C2
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(m, &c__[(*n - *k + j) * c_dim1 + 1], &c__1, &work[
j * work_dim1 + 1], &c__1);
// L220:
}
//
// W := W * V2**T
//
dtrmm_("Right", "Lower", "Transpose", "Unit", m, k, &c_b14, &
v[(*n - *k + 1) * v_dim1 + 1], ldv, &work[work_offset]
, ldwork);
if (*n > *k) {
//
// W := W + C1 * V1**T
//
i__1 = *n - *k;
dgemm_("No transpose", "Transpose", m, k, &i__1, &c_b14, &
c__[c_offset], ldc, &v[v_offset], ldv, &c_b14, &
work[work_offset], ldwork);
}
//
// W := W * T or W * T**T
//
dtrmm_("Right", "Lower", trans, "Non-unit", m, k, &c_b14, &t[
t_offset], ldt, &work[work_offset], ldwork);
//
// C := C - W * V
//
if (*n > *k) {
//
// C1 := C1 - W * V1
//
i__1 = *n - *k;
dgemm_("No transpose", "No transpose", m, &i__1, k, &
c_b25, &work[work_offset], ldwork, &v[v_offset],
ldv, &c_b14, &c__[c_offset], ldc);
}
//
// W := W * V2
//
dtrmm_("Right", "Lower", "No transpose", "Unit", m, k, &c_b14,
&v[(*n - *k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork);
//
// C1 := C1 - W
//
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + (*n - *k + j) * c_dim1] -= work[i__ + j *
work_dim1];
// L230:
}
// L240:
}
}
}
}
return 0;
//
// End of DLARFB
//
} // dlarfb_

216
3rdparty/clapack/src/dlarfg.c vendored Normal file
View File

@@ -0,0 +1,216 @@
/* -- translated by f2c (version 20201020 (for_lapack)). -- */
#include "f2c.h"
//> \brief \b DLARFG generates an elementary reflector (Householder matrix).
//
// =========== DOCUMENTATION ===========
//
// Online html documentation available at
// http://www.netlib.org/lapack/explore-html/
//
//> \htmlonly
//> Download DLARFG + dependencies
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dlarfg.f">
//> [TGZ]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dlarfg.f">
//> [ZIP]</a>
//> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlarfg.f">
//> [TXT]</a>
//> \endhtmlonly
//
// Definition:
// ===========
//
// SUBROUTINE DLARFG( N, ALPHA, X, INCX, TAU )
//
// .. Scalar Arguments ..
// INTEGER INCX, N
// DOUBLE PRECISION ALPHA, TAU
// ..
// .. Array Arguments ..
// DOUBLE PRECISION X( * )
// ..
//
//
//> \par Purpose:
// =============
//>
//> \verbatim
//>
//> DLARFG generates a real elementary reflector H of order n, such
//> that
//>
//> H * ( alpha ) = ( beta ), H**T * H = I.
//> ( x ) ( 0 )
//>
//> where alpha and beta are scalars, and x is an (n-1)-element real
//> vector. H is represented in the form
//>
//> H = I - tau * ( 1 ) * ( 1 v**T ) ,
//> ( v )
//>
//> where tau is a real scalar and v is a real (n-1)-element
//> vector.
//>
//> If the elements of x are all zero, then tau = 0 and H is taken to be
//> the unit matrix.
//>
//> Otherwise 1 <= tau <= 2.
//> \endverbatim
//
// Arguments:
// ==========
//
//> \param[in] N
//> \verbatim
//> N is INTEGER
//> The order of the elementary reflector.
//> \endverbatim
//>
//> \param[in,out] ALPHA
//> \verbatim
//> ALPHA is DOUBLE PRECISION
//> On entry, the value alpha.
//> On exit, it is overwritten with the value beta.
//> \endverbatim
//>
//> \param[in,out] X
//> \verbatim
//> X is DOUBLE PRECISION array, dimension
//> (1+(N-2)*abs(INCX))
//> On entry, the vector x.
//> On exit, it is overwritten with the vector v.
//> \endverbatim
//>
//> \param[in] INCX
//> \verbatim
//> INCX is INTEGER
//> The increment between elements of X. INCX > 0.
//> \endverbatim
//>
//> \param[out] TAU
//> \verbatim
//> TAU is DOUBLE PRECISION
//> The value tau.
//> \endverbatim
//
// Authors:
// ========
//
//> \author Univ. of Tennessee
//> \author Univ. of California Berkeley
//> \author Univ. of Colorado Denver
//> \author NAG Ltd.
//
//> \date November 2017
//
//> \ingroup doubleOTHERauxiliary
//
// =====================================================================
/* Subroutine */ int dlarfg_(int *n, double *alpha, double *x, int *incx,
double *tau)
{
// System generated locals
int i__1;
double d__1;
// Local variables
int j, knt;
double beta;
extern double dnrm2_(int *, double *, int *);
extern /* Subroutine */ int dscal_(int *, double *, double *, int *);
double xnorm;
extern double dlapy2_(double *, double *), dlamch_(char *);
double safmin, rsafmn;
//
// -- LAPACK auxiliary routine (version 3.8.0) --
// -- LAPACK is a software package provided by Univ. of Tennessee, --
// -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
// November 2017
//
// .. Scalar Arguments ..
// ..
// .. Array Arguments ..
// ..
//
// =====================================================================
//
// .. Parameters ..
// ..
// .. Local Scalars ..
// ..
// .. External Functions ..
// ..
// .. Intrinsic Functions ..
// ..
// .. External Subroutines ..
// ..
// .. Executable Statements ..
//
// Parameter adjustments
--x;
// Function Body
if (*n <= 1) {
*tau = 0.;
return 0;
}
i__1 = *n - 1;
xnorm = dnrm2_(&i__1, &x[1], incx);
if (xnorm == 0.) {
//
// H = I
//
*tau = 0.;
} else {
//
// general case
//
d__1 = dlapy2_(alpha, &xnorm);
beta = -d_sign(&d__1, alpha);
safmin = dlamch_("S") / dlamch_("E");
knt = 0;
if (abs(beta) < safmin) {
//
// XNORM, BETA may be inaccurate; scale X and recompute them
//
rsafmn = 1. / safmin;
L10:
++knt;
i__1 = *n - 1;
dscal_(&i__1, &rsafmn, &x[1], incx);
beta *= rsafmn;
*alpha *= rsafmn;
if (abs(beta) < safmin && knt < 20) {
goto L10;
}
//
// New BETA is at most 1, at least SAFMIN
//
i__1 = *n - 1;
xnorm = dnrm2_(&i__1, &x[1], incx);
d__1 = dlapy2_(alpha, &xnorm);
beta = -d_sign(&d__1, alpha);
}
*tau = (beta - *alpha) / beta;
i__1 = *n - 1;
d__1 = 1. / (*alpha - beta);
dscal_(&i__1, &d__1, &x[1], incx);
//
// If ALPHA is subnormal, it may lose relative accuracy
//
i__1 = knt;
for (j = 1; j <= i__1; ++j) {
beta *= safmin;
// L20:
}
*alpha = beta;
}
return 0;
//
// End of DLARFG
//
} // dlarfg_

Some files were not shown because too many files have changed in this diff Show More