Merge pull request #28588 from abhishek-gola:ORT_GPU_wrapper

Added OnnxRuntime GPU wrapper #28588

### 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

samples/dnn/classification.py

@@ -135,7 +135,9 @@ def main(func_args=None):
 
         # Run a model
         net.setInput(blob)
+        t0 = cv.getTickCount()
         out = net.forward()
+        t = (cv.getTickCount() - t0) / cv.getTickFrequency()
 
         (h, w, _) = frame.shape
         roi_rows = min(300, h)
@@ -143,8 +145,7 @@ def main(func_args=None):
         frame[:roi_rows,:roi_cols,:] >>= 1
 
         # Put efficiency information.
-        t, _ = net.getPerfProfile()
-        label = 'Inference time: %.1f ms' % (t * 1000.0 / cv.getTickFrequency())
+        label = 'Inference time: %.1f ms' % (t * 1000.0)
         cv.putText(frame, label, (15, 30), cv.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0))
 
         # Print predicted classes.