Merge pull request #28053 from TonyCY24:docs/mask-rcnn-compatibility

samples: add compatibility note for Mask R-CNN in OpenCV 5.0 #28053

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- [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
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- [x] There is a reference to the original bug report and related work
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      Patch to opencv_extra has the same branch name.
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### Summary
Updates documentation in `samples/dnn/mask_rcnn.py` to clarify a compatibility issue with OpenCV 5.0.

### Details
As verified in issue #27240, OpenCV 5.0 introduces stricter graph optimization. The default `.pbtxt` used in this sample treats `detection_out_final` as an intermediate layer (it is not listed in `getUnconnectedOutLayersNames`).

While OpenCV 4.x implicitly allows retrieving this layer, OpenCV 5.0 throws an error when requesting it:
> "the number of requested and actual outputs must be the same"

This PR adds:
1. A warning note in the file header explaining the strict output requirement.
2. An inline comment near `net.forward()` to guide users debugging this error.

Relates to issue: #27240

samples/dnn/mask_rcnn.py

@@ -1,3 +1,15 @@
+'''
+Mask R-CNN
+This is an example of using Mask R-CNN for object detection and instance segmentation.
+
+NOTE regarding OpenCV 5.0+:
+The default model configuration (.pbtxt) used in this sample relies on retrieving
+intermediate layers (e.g., 'detection_out_final'). OpenCV 5.0 introduces stricter
+graph optimization which may prune intermediate layers not explicitly registered as outputs.
+If you encounter an error such as "the number of requested and actual outputs must be the same",
+please note that the provided .pbtxt may need to be updated to explicitly declare
+'detection_out_final' as an output node.
+'''
 import cv2 as cv
 import argparse
 import numpy as np
@@ -91,6 +103,8 @@ while cv.waitKey(1) < 0:
     # Run a model
     net.setInput(blob)
 
+    # NOTE: In OpenCV 5.0, requesting 'detection_out_final' will fail if the .pbtxt
+    # does not register it as an output. See file header for details.
     boxes, masks = net.forward(['detection_out_final', 'detection_masks'])
 
     numClasses = masks.shape[1]