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

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

modules/dnn/test/test_backends.cpp

@@ -394,10 +394,13 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
 
 TEST_P(DNNTestNetwork, YuNet)
 {
-    Mat img = imread(findDataFile("gpu/lbpcascade/er.png"));
-    resize(img, img, Size(320, 320));
-    Mat inp = blobFromImage(img);
-    processNet("dnn/onnx/models/yunet-202303.onnx", "", inp);
+    double l1 = 0.0, lInf = 0.0;
+    if (target == DNN_TARGET_CUDA_FP16 || target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_CPU_FP16)
+    {
+        l1 = 0.01;
+        lInf = 0.05;
+    }
+    processNet("dnn/onnx/models/yunet-202605.onnx", "", Size(320, 320), "", l1, lInf);
     expectNoFallbacksFromIE(net);
 }