mirror of
https://github.com/opencv/opencv.git
synced 2025-01-19 06:53:50 +08:00
55d7e3f8cc
[BugFix] dnn (ONNX): Foce dropping constant inputs in parseClip if they are shared #25319 Resolves https://github.com/opencv/opencv/issues/25278 Merge with https://github.com/opencv/opencv_extra/pull/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 https://github.com/opencv/opencv/issues/25278#issuecomment-2032199630. ### 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 |
||
---|---|---|
.. | ||
calib3d | ||
core | ||
dnn | ||
features2d | ||
flann | ||
gapi | ||
highgui | ||
imgcodecs | ||
imgproc | ||
java | ||
js | ||
ml | ||
objc | ||
objdetect | ||
photo | ||
python | ||
stitching | ||
ts | ||
video | ||
videoio | ||
world |