Commit Graph

23 Commits

Author SHA1 Message Date
Abhishek Gola
34074075b2 Merge pull request #29369 from abhishek-gola:fp8_support
FP8 support in core module #29369

Core part of https://github.com/opencv/opencv/issues/29313

### 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
2026-07-15 15:45:01 +03:00
Abhishek Gola
81621ced10 Merge pull request #29323 from abhishek-gola:split_layer_extension
Extended support for Resize and Split layers #29323

Merge with: https://github.com/opencv/opencv_extra/pull/1379

Key changes: 

Resize layer: 
_antialias_ (linear & cubic) :- PIL-style separable resampling with stretched filter support and edge-clamped, renormalized weights.
_axes_ (incl. reversed [3,2]) :- getOutShape, the scale override, and runtime _tf_crop_and_resize_ ROI parsing now map 2-element sizes/scales/roi by the axes order instead of assuming [2,3].
_keep_aspect_ratio_policy_ (not_larger/not_smaller) :- output size from min/max per-axis scale.
_half_pixel_symmetric_ :- new coordinate-transform mode + importer mapping.
_align_corners_ downsampling :- coordinate scale uses the unfloored scaled length (in−1)/(in·x_scale−1).

Split Layer:
_convertTo empty 1-D Mat:_ the empty-Mat branch collapsed a 1-D [0] to 2-D [1,0] via cv::Size(); now uses allowTransposed like the non-empty path.
### 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
2026-06-23 09:23:19 +03:00
Abhishek Gola
31cab2a055 Merge pull request #28574 from abhishek-gola:reduce_layer_empty_set
* added empty set support

* accept unnamed dynamic dims

* Fix for LSTM test failure

* removed converToND

* openvino failing test fix

* ARM CI issue fix

* ARM issue fix
2026-03-01 15:19:44 +03:00
Alexander Smorkalov
1b6fb61b89 Merge branch 4.x 2025-11-18 08:51:08 +03:00
Alexander Smorkalov
64bbaa9f41 Merge pull request #27972 from asmorkalov:as/dst_mat_type
Force empty output type where it's defined in API #27972

The PR replaces:
- https://github.com/opencv/opencv/pull/27936
- https://github.com/opencv/opencv/pull/21059

Empty matrix has undefined type, so user code should not relay on the output type, if it's empty. The PR introduces some exceptions:
- copyTo documentation defines, that the method re-create output buffer and set it's type.
- convertTo has output type as parameter and output type is defined and expected.
2025-11-10 08:00:17 +03:00
Vadim Pisarevsky
bdab54f79e Merge pull request #27757 from vpisarev:matshape_inside_mat
Use MatShape instead of MatSize inside cv::Mat/cv::UMat #27757

**Merge together with https://github.com/opencv/opencv_contrib/pull/3996**
---

This PR continues cv::Mat/cv::UMat refactoring. See #26056, where `MatShape` was introduced. Now it's put inside cv::Mat/cv::UMat instead of a weird `MatSize`. MatSize is now an alias for MatShape:

**before:**

```
struct MatShape { ... };
struct MatSize { ... };

struct Mat {
    ...
    int dims;
    int rows;
    int cols;

    ...

    MatShape shape() const { ... /* constructs MatShape out of MatSize and returns it;
                                    layout is always 'unknown', because we don't store it */ }

    MatSize size; // size is not valid without the parent cv::Mat,
                  // because size.p may point to Mat::rows or to Mat::cols,
                  // depending on the dimensionality, and dims() returns Mat::dims.
    MatStep step; // may allocate memory, depending on the dimensionality.
    ...
};
```

**after:**

```
struct MatShape { ... };
typedef MatShape MatSize; // they are now synonyms

struct Mat {
    ...
    int dims;
    int rows;
    int cols;

    ...

    MatShape shape() const { return size; } // just return the embedded shape (including the proper layout information)

    MatSize size; // size is self-contained data structure that can be used without the parent cv::Mat.
                  // size.dims is now a copy of dims; size.p[*] contains copies of Mat::rows and Mat::cols when dims <= 2.
    MatStep step; // does not allocate extra memory buffers.
    ...
};
```

There are several reasons to do that:

1. the main reason is to be able to store data layout (MatShape::layout) inside each cv::Mat/cv::UMat. This is necessary for the proper shape inference in DNN module. In particular, it's necessary for the next step of DNN inference optimization where we introduce block-layout-optimized convolution and other operations. Later on, we can use layout information to support non-interleaved images (e.g. RRR...GGG...BBB...) or even batches of such images in core/imgproc modules.
2. the other reason is to represent 3D/4D/5D etc. tensors as cv::Mat/cv::UMat instances more conveniently, without extra dynamic memory allocation. Before this patch we allocated some memory buffers dynamically to store shape & steps for more than 2D arrays. Now the whole cv::Mat/cv::UMat header can be stored completely on stack/in a container. Creating another copy of Mat/UMat header is now done more efficiently.
3. the third reason is to introduce the new coding pattern: `dst.create(src.size, <dst_type>);`. The pattern is suitable for most of element-wise (including cloning) and filtering operations. This pattern does not only look crisp and self-documenting, it will also automatically copy shape (including layout) from the source tensor into the destination matrix/tensor.
4. in the future we might add `colorspace` member to MatShape that will allow to distinguish RGB from BGR or NV12. `dst.create(src.size, <dst_type>);` will then copy the colorspace information as 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
2025-09-15 15:03:34 +03:00
Alexander Smorkalov
1483504702 Merge branch 4.x 2025-02-20 13:58:04 +03:00
天音あめ
2e909c38dc Merge pull request #26804 from amane-ame:norm_hal_rvv
Add RISC-V HAL implementation for cv::norm and cv::normalize #26804

This patch implements `cv::norm` with norm types `NORM_INF/NORM_L1/NORM_L2/NORM_L2SQR` and `Mat::convertTo` function in RVV_HAL using native intrinsic, optimizing the performance for `cv::norm(src)`, `cv::norm(src1, src2)`, and `cv::normalize(src)` with data types `8UC1/8UC4/32FC1`.

`cv::normalize` also calls `minMaxIdx`, #26789 implements RVV_HAL for this.

Tested on MUSE-PI for both gcc 14.2 and clang 20.0.

```
$ opencv_test_core --gtest_filter="*Norm*"
$ opencv_perf_core --gtest_filter="*norm*" --perf_min_samples=300 --perf_force_samples=300
```

The head of the perf table is shown below since the table is too long.

View the full perf table here: [hal_rvv_norm.pdf](https://github.com/user-attachments/files/18468255/hal_rvv_norm.pdf)

<img width="1304" alt="Untitled" src="https://github.com/user-attachments/assets/3550b671-6d96-4db3-8b5b-d4cb241da650" />

### 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
2025-02-06 19:34:54 +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
Alexander Smorkalov
cb6d295f15 Merge branch 4.x 2024-04-02 16:39:54 +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
Yuantao Feng
3afe8ddaf8 core: Rename cv::float16_t to cv::hfloat (#25217)
* rename cv::float16_t to cv::fp16_t

* add typedef fp16_t float16_t

* remove zero(), bits() from fp16_t class

* fp16_t -> hfloat

* remove cv::float16_t::fromBits; add hfloatFromBits

* undo changes in conv_winograd_f63.simd.hpp and conv_block.simd.hpp

* undo some changes in dnn
2024-03-21 23:44:19 +03:00
Alexander Smorkalov
3a55f50133 Merge branch 4.x 2024-02-12 14:20:35 +03:00
Alexander Alekhin
40533dbf69 Merge pull request #24918 from opencv-pushbot:gitee/alalek/core_convertfp16_replacement
core(OpenCL): optimize convertTo() with CV_16F (convertFp16() replacement) #24918

relates #24909
relates #24917
relates #24892

Performance changes:

- [x] 12700K (1 thread) + Intel iGPU

|Name of Test|noOCL|convertFp16|convertTo BASE|convertTo PATCH|
|---|:-:|:-:|:-:|:-:|
|ConvertFP16FP32MatMat::OCL_Core|3.130|3.152|3.127|3.136|
|ConvertFP16FP32MatUMat::OCL_Core|3.030|3.996|3.007|2.671|
|ConvertFP16FP32UMatMat::OCL_Core|3.010|3.101|3.056|2.854|
|ConvertFP16FP32UMatUMat::OCL_Core|3.016|3.298|2.072|2.061|
|ConvertFP32FP16MatMat::OCL_Core|2.697|2.652|2.723|2.721|
|ConvertFP32FP16MatUMat::OCL_Core|2.752|4.268|2.662|2.947|
|ConvertFP32FP16UMatMat::OCL_Core|2.706|2.601|2.603|2.528|
|ConvertFP32FP16UMatUMat::OCL_Core|2.704|3.215|1.999|1.988|

Patched version is not worse than convertFp16 and convertTo baseline (except MatUMat 32->16, baseline uses CPU code+dst buffer map).
There are still gaps against noOpenCL(CPU only) mode due to T-API implementation issues (unnecessary synchronization).


- [x] 12700K + AMD dGPU

|Name of Test|noOCL|convertFp16 dGPU|convertTo BASE dGPU|convertTo PATCH dGPU|
|---|:-:|:-:|:-:|:-:|
|ConvertFP16FP32MatMat::OCL_Core|3.130|3.133|3.172|3.087|
|ConvertFP16FP32MatUMat::OCL_Core|3.030|1.713|9.559|1.729|
|ConvertFP16FP32UMatMat::OCL_Core|3.010|6.515|6.309|4.452|
|ConvertFP16FP32UMatUMat::OCL_Core|3.016|0.242|23.597|0.170|
|ConvertFP32FP16MatMat::OCL_Core|2.697|2.641|2.713|2.689|
|ConvertFP32FP16MatUMat::OCL_Core|2.752|4.076|6.483|4.191|
|ConvertFP32FP16UMatMat::OCL_Core|2.706|9.042|16.481|1.834|
|ConvertFP32FP16UMatUMat::OCL_Core|2.704|0.229|15.730|0.176|

convertTo-baseline can't compile OpenCL kernel for FP16 properly - FIXED.
dGPU has much more power, so results are x16-17 better than single cpu core. 
Patched version is not worse than convertFp16 and convertTo baseline.
There are still gaps against noOpenCL(CPU only) mode due to T-API implementation issues (unnecessary synchronization) and required memory transfers.

Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
2024-01-26 12:56:52 +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
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 Alekhin
624d532000 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-12-17 21:05:34 +00:00
Alexander Alekhin
c240355cc6 dnn(ocl): avoid mess FP16/FP32 in convolution layer 2020-12-15 08:51:24 +00:00
Alexander Alekhin
f8791f072d core: avoid function type cast, make happy UBSAN
backporting of commit: d3d13c41c4
2019-06-11 19:36:47 +00:00
Alexander Alekhin
d3d13c41c4 core: avoid function type cast, make happy UBSAN
oss-fuzz: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=14115
2019-06-11 07:06:29 +00:00
Alexander Alekhin
dfef04b325 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-02-12 17:54:40 +03:00
Alexander Alekhin
39b90ae9fb core: dispatch convert 2019-02-08 18:32:10 +03:00
Alexander Alekhin
5527c41468 core: clone convert.dispatch.cpp 2019-02-08 16:29:16 +03:00