imgproc: remove C-API usage from tests #25842
Final cleanup will be done in 5.x after regular merge.
Some tests have been reworked, some required only slight modifications.
Merge pull request #25861 from Abdurrahheem:ash/torch-attention-export-fix-4x
Support for Unflatten operation requred by Attention layer - 4.x #25861
### Pull Request Readiness Checklist
All test data and models for PR are located [#1190](https://github.com/opencv/opencv_extra/pull/1190)
This PR fixes issue reised when importing batched vanilla `Attention` layer from `PyTorch` via ONNX. Currently batched version of `Attention` layer in PyTorch [has unflatten operation inside](e3b3431c42/torch/nn/functional.py (L5500C17-L5500C31)). `unflatten` operation causes issue in `reshape` layer (see the Reshape_2 in the graph below) due to incorrect output of `slice` layer. This PR particularly fixes `slice` and `concat` layers to handle `unflatten` operation.
<img width="673" alt="image" src="https://github.com/opencv/opencv/assets/44877829/5b612b31-657a-47f1-83a4-0ac35a950abd">
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
Fixed kotlin requirement in Android build.gradle #25856
Now OpenCV Android SDK doesn't always require kotlin plugin. Kotlin code is compiled only if the application uses kotlin plugin.
Fixes#24663
### 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
python: attempts to fix 3d mat parsing problem for dnn #25810
Fixes https://github.com/opencv/opencv/issues/25762https://github.com/opencv/opencv/issues/23242
Relates https://github.com/opencv/opencv/issues/25763https://github.com/opencv/opencv/issues/19091
Although `cv.Mat` has already been introduced to workaround this problem, people do not know it and it kind of leads to confusion with `numpy.array`. This patch adds a "switch" to turn off the auto multichannel feature when the API is from cv::dnn::Net (more specifically, `setInput`) and the parameter is of type `Mat`. This patch only leads to changes of three places in `pyopencv_generated_types_content.h`:
```.diff
static PyObject* pyopencv_cv_dnn_dnn_Net_setInput(PyObject* self, PyObject* py_args, PyObject* kw)
{
...
- pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 0)) &&
+ pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 8)) &&
...
}
// I guess we also need to change this as one-channel blob is expected for param
static PyObject* pyopencv_cv_dnn_dnn_Net_setParam(PyObject* self, PyObject* py_args, PyObject* kw)
{
...
- pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 0)) )
+ pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 8)) )
...
- pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 0)) )
+ pyopencv_to_safe(pyobj_blob, blob, ArgInfo("blob", 8)) )
...
}
```
Others are unchanged, e.g. `dnn_SegmentationModel` and stuff like that.
### 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
Add support for v_log (Natural Logarithm) #25781
This PR aims to implement `v_log(v_float16 x)`, `v_log(v_float32 x)` and `v_log(v_float64 x)`.
Merged after https://github.com/opencv/opencv/pull/24941
TODO:
- [x] double and half float precision
- [x] tests for them
- [x] doc to explain the implementation
### 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
imgcodecs: Add rgb flag for imread and imdecode #25809
Try to `imread` images by RGB to save R-B swapping costs.
## How to use it?
```
img_rgb = cv2.imread("PATH", IMREAD_COLOR_RGB) # OpenCV decode the image by RGB format.
```
## TODO
- [x] Fix the broken code
- [x] Add imread rgb test
- [x] Speed test of rgb mode.
## Performance test
| file name | IMREAD_COLOR | IMREAD_COLOR_RGB |
| --------- | ------ | --------- |
| jpg01 | 284 ms | 277 ms |
| jpg02 | 376 ms | 366 ms |
| png01 | 62 ms | 60 ms |
| Png02 | 97 ms | 94 ms |
Test with [image_test.zip](https://github.com/user-attachments/files/15982949/image_test.zip)
```.cpp
string img_path = "/Users/mzh/work/data/image_test/png02.png";
int loop = 20;
TickMeter t;
double t0 = 10000;
for (int i = 0; i < loop; i++)
{
t.reset();
t.start();
img_bgr = imread(img_path, IMREAD_COLOR);
t.stop();
if (t.getTimeMilli() < t0) t0 = t.getTimeMilli();
}
std::cout<<"bgr time = "<<t0<<std::endl;
t0 = 10000;
for (int i = 0; i < loop; i++)
{
t.reset();
t.start();
img_rgb = imread(img_path, IMREAD_COLOR_RGB);
t.stop();
if (t.getTimeMilli() < t0) t0 = t.getTimeMilli();
}
std::cout<<"rgb time = "<<t0<<std::endl;
```
### 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
dnn: parallelize nary elementwise forward implementation & enable related conformance tests #25630
This PR introduces the following changes:
- [x] Parallelize binary forward impl
- [x] Parallelize ternary forward impl (Where)
- [x] Parallelize nary (Operator that can take >=1 operands)
- [x] Enable conformance tests if workable
## Performance
### i7-12700K, RAM 64GB, Ubuntu 22.04
```
Geometric mean (ms)
Name of Test opencv opencv opencv
perf perf perf
core.x64.0606 core.x64.0606 core.x64.0606
vs
opencv
perf
core.x64.0606
(x-factor)
NCHW_C_sum::Layer_NaryEltwise::OCV/CPU 16.116 11.161 1.44
NCHW_NCHW_add::Layer_NaryEltwise::OCV/CPU 17.469 11.446 1.53
NCHW_NCHW_div::Layer_NaryEltwise::OCV/CPU 17.531 11.469 1.53
NCHW_NCHW_equal::Layer_NaryEltwise::OCV/CPU 28.653 13.682 2.09
NCHW_NCHW_greater::Layer_NaryEltwise::OCV/CPU 21.899 13.422 1.63
NCHW_NCHW_less::Layer_NaryEltwise::OCV/CPU 21.738 13.185 1.65
NCHW_NCHW_max::Layer_NaryEltwise::OCV/CPU 16.172 11.473 1.41
NCHW_NCHW_mean::Layer_NaryEltwise::OCV/CPU 16.309 11.565 1.41
NCHW_NCHW_min::Layer_NaryEltwise::OCV/CPU 16.166 11.454 1.41
NCHW_NCHW_mul::Layer_NaryEltwise::OCV/CPU 16.157 11.443 1.41
NCHW_NCHW_pow::Layer_NaryEltwise::OCV/CPU 163.459 15.234 10.73
NCHW_NCHW_ref_div::Layer_NaryEltwise::OCV/CPU 10.880 10.868 1.00
NCHW_NCHW_ref_max::Layer_NaryEltwise::OCV/CPU 10.947 11.058 0.99
NCHW_NCHW_ref_min::Layer_NaryEltwise::OCV/CPU 10.948 10.910 1.00
NCHW_NCHW_ref_mul::Layer_NaryEltwise::OCV/CPU 10.874 10.871 1.00
NCHW_NCHW_ref_sum::Layer_NaryEltwise::OCV/CPU 10.971 10.920 1.00
NCHW_NCHW_sub::Layer_NaryEltwise::OCV/CPU 17.546 11.462 1.53
NCHW_NCHW_sum::Layer_NaryEltwise::OCV/CPU 16.175 11.475 1.41
NHWC_C::Layer_NaryEltwise::OCV/CPU 11.339 11.333 1.00
NHWC_H::Layer_NaryEltwise::OCV/CPU 16.154 11.102 1.46
```
### Apple M1, RAM 16GB, macOS 14.4.1
```
Geometric mean (ms)
Name of Test opencv opencv opencv
perf perf perf
core.m1.0606 core.m1.0606.patch core.m1.0606.patch
vs
opencv
perf
core.m1.0606
(x-factor)
NCHW_C_sum::Layer_NaryEltwise::OCV/CPU 28.418 3.768 7.54
NCHW_NCHW_add::Layer_NaryEltwise::OCV/CPU 6.942 5.679 1.22
NCHW_NCHW_div::Layer_NaryEltwise::OCV/CPU 5.822 5.653 1.03
NCHW_NCHW_equal::Layer_NaryEltwise::OCV/CPU 5.751 5.628 1.02
NCHW_NCHW_greater::Layer_NaryEltwise::OCV/CPU 5.797 5.599 1.04
NCHW_NCHW_less::Layer_NaryEltwise::OCV/CPU 7.272 5.578 1.30
NCHW_NCHW_max::Layer_NaryEltwise::OCV/CPU 5.777 5.562 1.04
NCHW_NCHW_mean::Layer_NaryEltwise::OCV/CPU 5.819 5.559 1.05
NCHW_NCHW_min::Layer_NaryEltwise::OCV/CPU 5.830 5.574 1.05
NCHW_NCHW_mul::Layer_NaryEltwise::OCV/CPU 5.759 5.567 1.03
NCHW_NCHW_pow::Layer_NaryEltwise::OCV/CPU 342.260 74.655 4.58
NCHW_NCHW_ref_div::Layer_NaryEltwise::OCV/CPU 8.338 8.280 1.01
NCHW_NCHW_ref_max::Layer_NaryEltwise::OCV/CPU 8.359 8.309 1.01
NCHW_NCHW_ref_min::Layer_NaryEltwise::OCV/CPU 8.412 8.295 1.01
NCHW_NCHW_ref_mul::Layer_NaryEltwise::OCV/CPU 8.380 8.297 1.01
NCHW_NCHW_ref_sum::Layer_NaryEltwise::OCV/CPU 8.356 8.323 1.00
NCHW_NCHW_sub::Layer_NaryEltwise::OCV/CPU 6.818 5.561 1.23
NCHW_NCHW_sum::Layer_NaryEltwise::OCV/CPU 5.805 5.570 1.04
NHWC_C::Layer_NaryEltwise::OCV/CPU 3.834 4.817 0.80
NHWC_H::Layer_NaryEltwise::OCV/CPU 28.402 3.771 7.53
```
### 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
Add sample support of YOLOv9 and YOLOv10 in OpenCV #25794
This PR adds sample support of [`YOLOv9`](https://github.com/WongKinYiu/yolov9) and [`YOLOv10`](https://github.com/THU-MIG/yolov10/tree/main)) in OpenCV. Models for this test are located in this [PR](https://github.com/opencv/opencv_extra/pull/1186).
**Running YOLOv10 using OpenCV.**
1. In oder to run `YOLOv10` one needs to cut off postporcessing with dynamic shapes from torch and then convert it to ONNX. If someone is looking for ready solution, there is [this forked branch](https://github.com/Abdurrahheem/yolov10/tree/ash/opencv-export) from official YOLOv10. Particularty follow this proceduce.
```bash
git clone git@github.com:Abdurrahheem/yolov10.git
conda create -n yolov10 python=3.9
conda activate yolov10
pip install -r requirements.txt
python export_opencv.py --model=<model-name> --imgsz=<input-img-size>
```
By default `model="yolov10s"` and `imgsz=(480,640)`. This will generate file `yolov10s.onnx`, which can be use for inference in OpenCV
2. For inference part on OpenCV. one can use `yolo_detector.cpp` [sample](https://github.com/opencv/opencv/blob/4.x/samples/dnn/yolo_detector.cpp). If you have followed above exporting procedure, then you can use following command to run the model.
``` bash
build opencv from source
cd build
./bin/example_dnn_yolo_detector --model=<path-to-yolov10s.onnx-file> --yolo=yolov10 --width=640 --height=480 --input=<path-to-image> --scale=0.003921568627 --padvalue=114
```
If you do not specify `--input` argument, OpenCV will grab first camera that is avaliable on your platform.
For more deatils on how to run the `yolo_detector.cpp` file see this [guide](https://docs.opencv.org/4.x/da/d9d/tutorial_dnn_yolo.html#autotoc_md443)
**Running YOLOv9 using OpenCV**
1. Export model following [official guide](https://github.com/WongKinYiu/yolov9)of the YOLOv9 repository. Particularly you can do following for converting.
```bash
git clone https://github.com/WongKinYiu/yolov9.git
cd yolov9
conda create -n yolov9 python=3.9
conda activate yolov9
pip install -r requirements.txt
wget https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-t-converted.pt
python export.py --weights=./yolov9-t-converted.pt --include=onnx --img-size=(480,640)
```
This will generate <yolov9-t-converted.onnx> file.
2. Inference on OpenCV.
```bash
build opencv from source
cd build
./bin/example_dnn_yolo_detector --model=<path-to-yolov9-t-converted.onnx> --yolo=yolov9 --width=640 --height=480 --scale=0.003921568627 --padvalue=114 --path=<path-to-image>
```
### 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
Add support for v_exp (exponential) #24941
This PR aims to implement `v_exp(v_float16 x)`, `v_exp(v_float32 x)` and `v_exp(v_float64 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
- [ ] 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
Fill mean and stdDev tails with zeros for HAL branch in meanStdDev #25789
as it's done for other branches.
### 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
Highgui backend on top of Framebuffer #25661
### 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
Environment variables used:
OPENCV_UI_BACKEND - you need to add the value “FB”
OPENCV_UI_PRIORITY_FB - requires priority indication
OPENCV_HIGHGUI_FB_MODE={FB|XVFB|EMU} - mode of using Framebuffer (default "FB")
- FB - Linux Framebuffer
- XVFB - virtual Framebuffer
- EMU - emulation (images are not displayed)
OPENCV_HIGHGUI_FB_DEVICE (FRAMEBUFFER) - path to the Framebuffer file (default "/dev/fb0").
Examples of using:
sudo OPENCV_UI_BACKEND=FB ./opencv_test_highgui
sudo OPENCV_UI_PRIORITY_FB=1111 ./opencv_test_highgui
OPENCV_UI_BACKEND=FB OPENCV_HIGHGUI_FB_MODE=EMU ./opencv_test_highgui
sudo OPENCV_UI_BACKEND=FB OPENCV_HIGHGUI_FB_MODE=FB ./opencv_test_highgui
export DISPLAY=:99
Xvfb $DISPLAY -screen 0 1024x768x24 -fbdir /tmp/ -f /tmp/user.xvfb.auth&
sudo -u sipeed XAUTHORITY=/tmp/user.xvfb.auth x11vnc -display $DISPLAY -listen localhost&
DISPLAY=:0 gvncviewer localhost&
FRAMEBUFFER=/tmp/Xvfb_screen0 OPENCV_UI_BACKEND=FB OPENCV_HIGHGUI_FB_MODE=XVFB ./opencv_test_highgui
dnn: add DepthToSpace and SpaceToDepth #25779
We are working on updating WeChat QRCode module. One of the new models is a fully convolutional model and hence it should be able to run with different input shapes. However, it has an operator `DepthToSpace`, which is parsed as a subgraph of `Reshape -> Permute -> Reshape` with a fixed shape getting during parsing. The subgraph itself is not a problem, but the true problem is the subgraph with a fixed input and output shape regardless input changes. This does not allow the model to run with different input shapes.
Solution is to add a dedicated layer for DepthtoSpace and SpaceToDepth.
Backend support:
- [x] CPU
- [x] CUDA
- [x] OpenCL
- [x] OpenVINO
- [x] CANN
- [x] TIMVX
- ~Vulkan~ (missing fundamental tools, like permutation and reshape)
### 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
Extending G-API onnx::Params to pass arbitrary session options #25791
### 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
Add missing cv2eigen overload #25751Fixes#16606
Add overloads to cv2eigen to handle eigen matrices of type
Eigen::Matrix<Tp_, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
### 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
video: fix vittrack in the case where crop size grows until out-of-memory when the input is black #25771
Fixes https://github.com/opencv/opencv/issues/25760
### 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
Use onRuntimeInitialized with OpenCV.js Node tests #25757
### Pull Request Readiness Checklist
tests: https://github.com/opencv/ci-gha-workflow/pull/174
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
Accuracy tests for equalizeHist() added #25759
### 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
Fix OpenCV.js tests #25732
### Pull Request Readiness Checklist
* Firefox tests passed
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
Relates to #24603
### 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
Tests added for mixed type arithmetic operations #25671
### Changes
* added accuracy tests for mixed type arithmetic operations
_Note: div-by-zero values are removed from checking since the result is implementation-defined in common case_
* added perf tests for the same cases
* fixed a typo in `getMulExtTab()` function that lead to dead code
### 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
Suppress build warnings for GCC14 #25686Close#25674
### 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
Fix Homography computation. #25665
The bug was introduced in https://github.com/opencv/opencv/pull/25308
I am sorry I do not have a proper 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
- [ ] 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
Maksim Shabunin
Abduragim Shtanchaev
alexlyulkov
Yuantao Feng
Alexander Smorkalov
Wanli
zihaomu
kaingwade
Mikhail Khachayants
Dan Mašek
Alexander Smorkalov
kozinove
Letu Ren
Yuantao Feng
xndcn
Ujjayant Kadian
Simon Kämpe
Dmitry Kurtaev
Rostislav Vasilikhin
Robert Lexmann
Pierre Chatelier
Maxim Smolskiy
Alexander Panov
Vadim Levin
Alexander Lyulkov
cudawarped
Patrick Keane
Kumataro
Vincent Rabaud