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Abhishek Gola
3d77645a3a
Extended fusion for activation functions in new DNN engine #28750 After this fusion, we see following improvements in YOLO models: | Model | Before (`ENGINE_NEW`) | After (`ENGINE_NEW`) | `ENGINE_ORT` | % Improvement (Before v/s After) | | :--- | :--- | :--- | :--- | :--- | | **YOLOv8n** | 18.89 ms| 12.06 ms| 12.15 ms| 36.16% | | **YOLOv5n** | 17.12 ms| 9.29 ms| 9.23 ms| 45.73% | | **YOLOX-S** | 38.78 ms| 25.56 ms| 25.16 ms| 34.09% | Device details: - Model name: Intel(R) Core(TM) i9-14900KS, x86, 32 Cores, ubuntu 24.04, ### 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
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