Merge pull request #25515 from gursimarsingh:improved_edge_detection_sample

#25006 #25314 
This pull request removes hed_pretrained caffe model to the SOTA dexined onnx model for edge detection. Usage of conventional methods like canny has also been added

The obsolete cpp and python sample has been removed

TODO:
- [  ]  Remove temporary hack for quantized models. Refer issue https://github.com/opencv/opencv_zoo/issues/273

### 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
- [ ] 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

doc/tutorials/dnn/dnn_custom_layers/dnn_custom_layers.md

@@ -218,13 +218,13 @@ a centric one.
 
 - Create a class with `getMemoryShapes` and `forward` methods
 
-@snippet dnn/edge_detection.py CropLayer
+@snippet dnn/custom_layer.py CropLayer
 
 @note Both methods should return lists.
 
 - Register a new layer.
 
-@snippet dnn/edge_detection.py Register
+@snippet dnn/custom_layer.py Register
 
 That's it! We have replaced an implemented OpenCV's layer to a custom one.
 You may find a full script in the [source code](https://github.com/opencv/opencv/tree/5.x/samples/dnn/edge_detection.py).