Merge pull request #25779 from fengyuentau:dnn/fix_onnx_depthtospace

dnn: add DepthToSpace and SpaceToDepth #25779

We are working on updating WeChat QRCode module. One of the new models is a fully convolutional model and hence it should be able to run with different input shapes. However,  it has an operator `DepthToSpace`, which is parsed as a subgraph of `Reshape -> Permute -> Reshape` with a fixed shape getting during parsing. The subgraph itself is not a problem, but the true problem is the subgraph with a fixed input and output shape regardless input changes. This does not allow the model to run with different input shapes.

Solution is to add a dedicated layer for DepthtoSpace and SpaceToDepth.

Backend support:

- [x] CPU
- [x] CUDA
- [x] OpenCL
- [x] OpenVINO
- [x] CANN
- [x] TIMVX
-  ~Vulkan~ (missing fundamental tools, like permutation and reshape)

### 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/src/init.cpp

@@ -164,6 +164,10 @@ void initializeLayerFactory()
     CV_DNN_REGISTER_LAYER_CLASS(InstanceNormalization, InstanceNormLayer);
     CV_DNN_REGISTER_LAYER_CLASS(Attention,      AttentionLayer);
     CV_DNN_REGISTER_LAYER_CLASS(GroupNormalization, GroupNormLayer);
+    CV_DNN_REGISTER_LAYER_CLASS(DepthToSpace,   DepthToSpaceLayer)
+    CV_DNN_REGISTER_LAYER_CLASS(SpaceToDepth,   SpaceToDepthLayer)
+    CV_DNN_REGISTER_LAYER_CLASS(DepthToSpaceInt8, DepthToSpaceLayer)
+    CV_DNN_REGISTER_LAYER_CLASS(SpaceToDepthInt8, SpaceToDepthLayer)
 
     CV_DNN_REGISTER_LAYER_CLASS(Crop,           CropLayer);
     CV_DNN_REGISTER_LAYER_CLASS(Eltwise,        EltwiseLayer);