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dnn: add models and data converted from onnx conformance for TopK #1200
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10 tasks
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please rebase and fix the conflict |
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Fixed. |
asmorkalov
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Aug 21, 2024
dnn: add ONNX TopK #23279 Merge with opencv/opencv_extra#1200 Partially fixes #22890 and #20258 To-do: - [x] TopK forward impl - [x] add tests - [x] support Opset 1 & 10 if possible - [ ] ~Support other backends~ (TopK has two outputs, which is not supported by other backends, such as openvino) Perf: M1 (time in millisecond) | input shape | axis | dnn | ort | | --------------- | ---- | ---- | ---- | | (1000, 100) | 0 | 1.68 | 4.07 | | (1000, 100) K5 | 0 | 1.13 | 0.12 | | (1000, 100) | 1 | 0.96 | 0.77 | | (100, 100, 100) | 0 | 10.00 | 31.13 | | (100, 100, 100) | 1 | 7.33 | 9.17 | | (100, 100, 100) | 2 | 7.52 | 9.48 | M2 (time in milisecond) | input shape | axis | dnn | ort | | --------------- | ---- | ---- | ---- | | (1000, 100) | 0 | 0.76 | 2.44 | | (1000, 100) K5 | 0 | 0.68 | 0.07 | | (1000, 100) | 1 | 0.41 | 0.50 | | (100, 100, 100) | 0 | 4.83 | 17.52| | (100, 100, 100) | 1 | 3.60 | 5.08 | | (100, 100, 100) | 2 | 3.73 | 5.10 | ONNXRuntime performance testing script: https://gist.github.com/fengyuentau/a119f94fd16721ec9974b8c7b0a45d4c ### 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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thewoz
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Feb 13, 2025
dnn: add ONNX TopK opencv#23279 Merge with opencv/opencv_extra#1200 Partially fixes opencv#22890 and opencv#20258 To-do: - [x] TopK forward impl - [x] add tests - [x] support Opset 1 & 10 if possible - [ ] ~Support other backends~ (TopK has two outputs, which is not supported by other backends, such as openvino) Perf: M1 (time in millisecond) | input shape | axis | dnn | ort | | --------------- | ---- | ---- | ---- | | (1000, 100) | 0 | 1.68 | 4.07 | | (1000, 100) K5 | 0 | 1.13 | 0.12 | | (1000, 100) | 1 | 0.96 | 0.77 | | (100, 100, 100) | 0 | 10.00 | 31.13 | | (100, 100, 100) | 1 | 7.33 | 9.17 | | (100, 100, 100) | 2 | 7.52 | 9.48 | M2 (time in milisecond) | input shape | axis | dnn | ort | | --------------- | ---- | ---- | ---- | | (1000, 100) | 0 | 0.76 | 2.44 | | (1000, 100) K5 | 0 | 0.68 | 0.07 | | (1000, 100) | 1 | 0.41 | 0.50 | | (100, 100, 100) | 0 | 4.83 | 17.52| | (100, 100, 100) | 1 | 3.60 | 5.08 | | (100, 100, 100) | 2 | 3.73 | 5.10 | ONNXRuntime performance testing script: https://gist.github.com/fengyuentau/a119f94fd16721ec9974b8c7b0a45d4c ### 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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Merge wtih opencv/opencv#23279
Models are created according to the original ones from ONNX conformance. Also the input tensors are the same with the original ones.
TopK conformance has input
K, which determines the output shape, being a varaible instead of constant. However, since dnn does not support dynamic shape, this recreating conformance with inputKbeing constant is needed.