fix 4.x links

modules/core/doc/cuda.markdown

@@ -82,4 +82,4 @@ Block Matching algorithm has been successfully parallelized using the following
 3.  Merge the results into a single disparity map.
 
 With this algorithm, a dual GPU gave a 180% performance increase comparing to the single Fermi GPU.
-For a source code example, see <https://github.com/opencv/opencv/tree/master/samples/gpu/>.
+For a source code example, see <https://github.com/opencv/opencv/tree/4.x/samples/gpu/>.

modules/core/include/opencv2/core/simd_intrinsics.hpp

@@ -7,7 +7,7 @@
 
 /**
 Helper header to support SIMD intrinsics (universal intrinsics) in user code.
-Intrinsics documentation: https://docs.opencv.org/master/df/d91/group__core__hal__intrin.html
+Intrinsics documentation: https://docs.opencv.org/4.x/df/d91/group__core__hal__intrin.html
 
 
 Checks of target CPU instruction set based on compiler definitions don't work well enough.

modules/dnn/misc/quantize_face_detector.py

@@ -18,7 +18,7 @@ parser = argparse.ArgumentParser(description="Use this script to create TensorFl
                                              "with weights from OpenCV's face detection network. "
                                              "Only backbone part of SSD model is converted this way. "
                                              "Look for .pbtxt configuration file at "
-                                             "https://github.com/opencv/opencv_extra/tree/master/testdata/dnn/opencv_face_detector.pbtxt")
+                                             "https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn/opencv_face_detector.pbtxt")
 parser.add_argument('--model', help='Path to .caffemodel weights', required=True)
 parser.add_argument('--proto', help='Path to .prototxt Caffe model definition', required=True)
 parser.add_argument('--pb', help='Path to output .pb TensorFlow model', required=True)

modules/dnn/test/imagenet_cls_test_inception.py

@@ -58,7 +58,7 @@ if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument("--imgs_dir", help="path to ImageNet validation subset images dir, ILSVRC2012_img_val dir")
     parser.add_argument("--img_cls_file", help="path to file with classes ids for images, download it here:"
-                            "https://github.com/opencv/opencv_extra/tree/master/testdata/dnn/img_classes_inception.txt")
+                            "https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn/img_classes_inception.txt")
     parser.add_argument("--model", help="path to tensorflow model, download it here:"
                                         "https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip")
     parser.add_argument("--log", help="path to logging file")

modules/dnn/test/pascal_semsegm_test_fcn.py

@@ -205,9 +205,9 @@ if __name__ == "__main__":
     parser.add_argument("--val_names", help="path to file with validation set image names, download it here: "
                         "https://github.com/shelhamer/fcn.berkeleyvision.org/blob/master/data/pascal/seg11valid.txt")
     parser.add_argument("--cls_file", help="path to file with colors for classes, download it here: "
-                        "https://github.com/opencv/opencv/blob/master/samples/data/dnn/pascal-classes.txt")
+                        "https://github.com/opencv/opencv/blob/4.x/samples/data/dnn/pascal-classes.txt")
     parser.add_argument("--prototxt", help="path to caffe prototxt, download it here: "
-                        "https://github.com/opencv/opencv/blob/master/samples/data/dnn/fcn8s-heavy-pascal.prototxt")
+                        "https://github.com/opencv/opencv/blob/4.x/samples/data/dnn/fcn8s-heavy-pascal.prototxt")
     parser.add_argument("--caffemodel", help="path to caffemodel file, download it here: "
                                              "http://dl.caffe.berkeleyvision.org/fcn8s-heavy-pascal.caffemodel")
     parser.add_argument("--log", help="path to logging file")

modules/objdetect/include/opencv2/objdetect.hpp

@@ -91,7 +91,7 @@ compensate for the differences in the size of areas. The sums of pixel values ov
 regions are calculated rapidly using integral images (see below and the integral description).
 
 To see the object detector at work, have a look at the facedetect demo:
-<https://github.com/opencv/opencv/tree/master/samples/cpp/dbt_face_detection.cpp>
+<https://github.com/opencv/opencv/tree/4.x/samples/cpp/dbt_face_detection.cpp>
 
 The following reference is for the detection part only. There is a separate application called
 opencv_traincascade that can train a cascade of boosted classifiers from a set of samples.

modules/python/test/tests_common.py

@@ -25,7 +25,7 @@ class NewOpenCVTests(unittest.TestCase):
     repoPath = None
     extraTestDataPath = None
     # github repository url
-    repoUrl = 'https://raw.github.com/opencv/opencv/master'
+    repoUrl = 'https://raw.github.com/opencv/opencv/4.x'
 
     def find_file(self, filename, searchPaths=[], required=True):
         searchPaths = searchPaths if searchPaths else [self.repoPath, self.extraTestDataPath]