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Merge pull request #29107 from varun-jaiswal17:yunet-dynamic-input

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Update default YuNet model to new dynamic inputs #29107

Update the default model in `face_detect.py` and `face_detect.cpp` to
`face_detection_yunet_2026may.onnx`, which has symbolic `height`/`width` input dims.

## Changes
- `samples/dnn/face_detect.py`: update default `--face_detection_model` to `face_detection_yunet_2026may.onnx`
- `samples/dnn/face_detect.cpp`: update default `fd_model` to `face_detection_yunet_2026may.onnx`

Companion PR : 
- https://github.com/opencv/opencv_zoo/pull/310
- https://github.com/opencv/opencv_extra/pull/1373

 Closes : https://github.com/opencv/opencv/issues/28769
 
### 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 commit is contained in:
Varun Jaiswal
2026-05-29 23:07:05 +05:30
committed by GitHub
parent a3ced1a94b
commit 75bb662258
5 changed files with 20 additions and 9 deletions
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modules/dnn/perf/perf_net.cpp
+10 -2
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@@ -332,8 +332,16 @@ PERF_TEST_P_(DNNTestNetwork, EfficientNet)
processNet("dnn/efficientnet-lite4.onnx", "", inp);
}
PERF_TEST_P_(DNNTestNetwork, YuNet) {
processNet("dnn/onnx/models/yunet-202303.onnx", "", cv::Size(640, 640));
PERF_TEST_P_(DNNTestNetwork, YuNet_320) {
processNet("dnn/onnx/models/yunet-202605.onnx", "", cv::Size(320, 320));
}
PERF_TEST_P_(DNNTestNetwork, YuNet_640) {
processNet("dnn/onnx/models/yunet-202605.onnx", "", cv::Size(640, 640));
}
PERF_TEST_P_(DNNTestNetwork, YuNet_1280) {
processNet("dnn/onnx/models/yunet-202605.onnx", "", cv::Size(1280, 736));
}
PERF_TEST_P_(DNNTestNetwork, SFace) {