added call to IPP's ippiDistanceTransform_5x5_8u32f_C1R (by Alexander Kapustin)#1165
added call to IPP's ippiDistanceTransform_5x5_8u32f_C1R (by Alexander Kapustin)#1165opencv-pushbot merged 1 commit intoopencv:2.4from
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Andrey, please, review |
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This breaks the build here (Linux, tried IPP 7.1 and 8.0). [ 7%] Building CXX object modules/imgproc/CMakeFiles/opencv_imgproc.dir/src/distransform.cpp.o |
…pencv#1165). Note: this may break binary compatibility, but since the class is not wrapped in Java and not exposed in Windows API, for example (it's considered internal-use class for flann), the effect should be minimal
[BugFix] dnn (ONNX): Foce dropping constant inputs in parseClip if they are shared #25319 Resolves #25278 Merge with opencv/opencv_extra#1165 In Gold-YOLO ,`Div` has a constant input `B=6` which is then parsed into a `Const` layer in the ONNX importer, but `Clip` also has the shared constant input `max=6` which is already a `Const` layer and then connected to `Elementwise` layer. This should not happen because in the `forward()` of `Elementwise` layer, the legacy code goes through and apply activation to each input. More details on #25278 (comment). ### 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
[BugFix] dnn (ONNX): Foce dropping constant inputs in parseClip if they are shared opencv#25319 Resolves opencv#25278 Merge with opencv/opencv_extra#1165 In Gold-YOLO ,`Div` has a constant input `B=6` which is then parsed into a `Const` layer in the ONNX importer, but `Clip` also has the shared constant input `max=6` which is already a `Const` layer and then connected to `Elementwise` layer. This should not happen because in the `forward()` of `Elementwise` layer, the legacy code goes through and apply activation to each input. More details on opencv#25278 (comment). ### 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
this should speedup distance transform 5x5