Fixing python wrapper around ECCParameters to include itersPerLevel #29148
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core: add YAML 1.2 support for FileStorage #28482Fixes: #26363
CI Update: https://github.com/opencv/ci-gha-workflow/pull/306
Summary:
- Bool true/false literals support
- Header-less YAMLs support for Python YAML module compatibility. Header-less files are parsed as YAMLs by default
- Added FORMAT_YAML_1_0 flag to FileStorage for fallback.
- New YAML1.2 header
Testing:
- Added Core_InputOutput.YAML_1_2_Compatibility test case in test_io.cpp.
- Added YAML interop test in Python
Fixes the issue for Identity functions for 0D #28968
Closes https://github.com/opencv/opencv/issues/25763
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GSoC 2025: Add Tokenizer Support to DNN Module #27534
merge with https://github.com/opencv/opencv_extra/pull/1276
### Summary
This pull request introduces initial support for a tokenizer module under `modules/dnn/src/tokenizer` as part of Google Summer of Code 2025 (Project: Tokenization for OpenCV DNN).
### Status
- [x] Project structure in place
- [x] Initial BPE tokenizer loading
- [x] Regex splitting (in progress)
- [x] Encoding logic for GPT-2 tokenizer (in progress)
- [ ] Documentation (to be improved)
### Goals
The goal is to support Hugging Face-compatible tokenization (e.g., GPT-2) natively in C++ to be integrated with DNN inference pipelines.
The core pipeline lives in `dnn/src/tokenizer/core_bpe.hpp` and `dnn/src/tokenizer/encoding.hpp`. For Unicode handling I’m using `dnn/src/tokenizer/unicode.hpp`, which is adapted from llama.cpp.
### Feedback
Please share early feedback on:
- General design structure
- Integration strategy with `dnn`
- Code organization or naming conventions
### Reference
Project: https://summerofcode.withgoogle.com/programs/2025/projects/79SW6eNK
python: fix segfault on 0-channel numpy array input #28747
### Pull Request Readiness Checklist
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N/A: a Python unit test is added in `modules/python/test/test_mat.py`. No external test data required.
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N/A: this is a bug fix, not a new feature. No documentation update needed.
### Problem
Passing a numpy array with shape `(H, W, 0)` (0 channels) to any OpenCV function that accepts a `Mat` argument (e.g. `cv2.resize`, `cv2.warpAffine`, `cv2.blur`) causes a **segfault**.
**Reproducer:**
```python
import cv2
import numpy as np
arr = np.zeros((100, 100, 0), np.uint8)
cv2.resize(arr, (200, 200)) # segfault
```
### Root Cause
In `modules/python/src2/cv2_convert.cpp`, the numpy→Mat conversion checks channel validity only against `CV_CN_MAX` (upper bound):
```cpp
if (channels > CV_CN_MAX) // channels=0 passes this check
```
With `channels=0`, `CV_MAKETYPE(0, 0)` produces `type=-8`, which corrupts the Mat's internal type field and causes undefined behavior downstream.
### Fix
Extend the check to also reject `channels < 1`:
```cpp
if (channels < 1 || channels > CV_CN_MAX)
```
**After fix:**
```
cv2.error: src unable to wrap channels, invalid count (0, must be in [1, 512])
```
### Notes
- This affects all functions that accept a `Mat` input, not just `cv2.resize`
- The same bug exists in the `5.x` branch
- A 0-channel array has no valid OpenCV Mat representation; rejecting it with a clear error is the correct behavior and poses no backward-compatibility risk (the previous behavior was a crash)
Chromatic aberration correction #27491
Merge with https://github.com/opencv/opencv_extra/pull/1266
### Pull Request Readiness Checklist
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Parent issue: https://github.com/opencv/opencv/issues/27206
Related PR: [#27490](https://github.com/opencv/opencv/pull/27490)
This PR adds chromatic aberration correction in C++ based on calibration data from the python app.
This code adds a function for chromatic aberration correction based on the calibration file (Mat correctChromaticAberration(InputArray image, const String& calibration_file)), and a class ChromaticAberrationCorrector which can be used to correct images of the same camera under the same settings (so for the same calibration data that is initialized in the beginning).
Also, basic functionality and performance tests are added.
Correct minAreaRect angle to be in range [-90, 0) #28051
### Pull Request Readiness Checklist
Box angle range over all imgproc tests is in interval `[-90, -0.0581199]`
resolves https://github.com/opencv/opencv/issues/27667
resolves https://github.com/opencv/opencv/issues/19472
resolves https://github.com/opencv/opencv/issues/24436
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Add 5.x types for DLPack. Keep uint32/int64/uint64 data type for conversion to Numpy. More types support for GpuMat::convertTo #27779
### Pull Request Readiness Checklist
**Merge with contrib**: https://github.com/opencv/opencv_contrib/pull/4000
related: https://github.com/opencv/opencv/pull/27581
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.
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- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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### Pull Request Readiness Checklist
resolves#16295
```
docker run --gpus 0 -v ~/opencv:/opencv -v ~/opencv_contrib:/opencv_contrib -it nvidia/cuda:12.8.1-cudnn-devel-ubuntu22.04
apt-get update && apt-get install -y cmake python3-dev python3-pip python3-venv &&
python3 -m venv .venv &&
source .venv/bin/activate &&
pip install -U pip &&
pip install -U numpy &&
pip install torch --index-url https://download.pytorch.org/whl/cu128 &&
cmake \
-DWITH_OPENCL=OFF \
-DCMAKE_BUILD_TYPE=Release \
-DBUILD_DOCS=OFF \
-DWITH_CUDA=ON \
-DOPENCV_DNN_CUDA=ON \
-DOPENCV_EXTRA_MODULES_PATH=/opencv_contrib/modules \
-DBUILD_LIST=ts,cudev,python3 \
-S /opencv -B /opencv_build &&
cmake --build /opencv_build -j16
export PYTHONPATH=/opencv_build/lib/python3/:$PYTHONPATH
```
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.
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Extend image I/O API with metadata support #27499
Covered with the PR:
* AVIF encoder can write exif, xmp, icc
* AVIF decoder can read exif
* JPEG encoder can write exif
* JPEG decoder can read exif
* PNG encoder can write exif
* PNG decoder can read exif
This PR is a sort of preamble for #27488. I suggest to merge this one first to OpenCV 4.x, then promote this change to OpenCV 5.x and then provide extra API to read and write metadata in 5.x (or maybe 4.x) in a style similar to #27488. Maybe in that PR exif packing/unpacking should be done using a separate external API. That is, metadata reading and writing can/should be done in 2 steps:
* [1] pack and then [2] embed exif into image at the encoding stage.
* [1] extract and then [2] unpack exif at the decoding stage.
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Adding color correction module to photo module from opencv_contrib #27051
This PR moved color correction module from opencv_contrib to main repo inside photo module.
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Add HoughCirclesWithAccumulator binding #27389
### Pull Request Readiness Checklist
Fix#27377
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Support bool type for FileStorage Base64 #26937
### Pull Request Readiness Checklist
OpenCV extra: https://github.com/opencv/opencv_extra/pull/1238
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Added trackers factory with pre-loaded dnn models #26875
Replaces https://github.com/opencv/opencv/pull/26295
Allows to substitute custom models or initialize tracker from in-memory model.
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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
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)
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Added flag to GaussianBlur for faster but not bit-exact implementation #25792
Rationale:
Current implementation of GaussianBlur is almost always bit-exact. It helps to get predictable results according platforms, but prohibits most of approximations and optimization tricks.
The patch converts `borderType` parameter to more generic `flags` and introduces `GAUSS_ALLOW_APPROXIMATIONS` flag to allow not bit-exact implementation. With the flag IPP and generic HAL implementation are called first. The flag naming and location is a subject for discussion.
Replaces https://github.com/opencv/opencv/pull/22073
Possibly related issue: https://github.com/opencv/opencv/issues/24135
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Add imread #24415
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Hello everyone,
I created this new version of the imread function and I think it can be very useful in several cases.
It is actually passed to it object on which you want to upload the image.
The advantages can be different like in case one needs to open several large images all the same in sequence.
one can use the same pointer and the system would not allocate memory each time.
