Merge remote-tracking branch 'upstream/3.4' into merge-3.4

modules/core/include/opencv2/core/bindings_utils.hpp

@@ -116,6 +116,12 @@ String dumpRange(const Range& argument)
     }
 }
 
+CV_WRAP static inline
+String testReservedKeywordConversion(int positional_argument, int lambda = 2, int from = 3)
+{
+    return format("arg=%d, lambda=%d, from=%d", positional_argument, lambda, from);
+}
+
 CV_WRAP static inline
 void testRaiseGeneralException()
 {

modules/dnn/misc/python/test/test_dnn.py

@@ -62,6 +62,12 @@ def printParams(backend, target):
     }
     print('%s/%s' % (backendNames[backend], targetNames[target]))
 
+def getDefaultThreshold(target):
+    if target == cv.dnn.DNN_TARGET_OPENCL_FP16 or target == cv.dnn.DNN_TARGET_MYRIAD:
+        return 4e-3
+    else:
+        return 1e-5
+
 testdata_required = bool(os.environ.get('OPENCV_DNN_TEST_REQUIRE_TESTDATA', False))
 
 g_dnnBackendsAndTargets = None
@@ -373,5 +379,35 @@ class dnn_test(NewOpenCVTests):
 
         cv.dnn_unregisterLayer('CropCaffe')
 
+    # check that dnn module can work with 3D tensor as input for network
+    def test_input_3d(self):
+        model = self.find_dnn_file('dnn/onnx/models/hidden_lstm.onnx')
+        input_file = self.find_dnn_file('dnn/onnx/data/input_hidden_lstm.npy')
+        output_file = self.find_dnn_file('dnn/onnx/data/output_hidden_lstm.npy')
+        if model is None:
+            raise unittest.SkipTest("Missing DNN test files (dnn/onnx/models/hidden_lstm.onnx). "
+                                    "Verify OPENCV_DNN_TEST_DATA_PATH configuration parameter.")
+        if input_file is None or output_file is None:
+            raise unittest.SkipTest("Missing DNN test files (dnn/onnx/data/{input/output}_hidden_lstm.npy). "
+                                    "Verify OPENCV_DNN_TEST_DATA_PATH configuration parameter.")
+
+        net = cv.dnn.readNet(model)
+        input = np.load(input_file)
+        # we have to expand the shape of input tensor because Python bindings cut 3D tensors to 2D
+        # it should be fixed in future. see : https://github.com/opencv/opencv/issues/19091
+        # please remove `expand_dims` after that
+        input = np.expand_dims(input, axis=3)
+        gold_output = np.load(output_file)
+        net.setInput(input)
+
+        for backend, target in self.dnnBackendsAndTargets:
+            printParams(backend, target)
+
+            net.setPreferableBackend(backend)
+            net.setPreferableTarget(target)
+            real_output = net.forward()
+
+            normAssert(self, real_output, gold_output, "", getDefaultThreshold(target))
+
 if __name__ == '__main__':
     NewOpenCVTests.bootstrap()

modules/python/src2/gen2.py

@@ -214,6 +214,16 @@ simple_argtype_mapping = {
     "Stream": ArgTypeInfo("Stream", FormatStrings.object, 'Stream::Null()', True),
 }
 
+# Set of reserved keywords for Python. Can be acquired via the following call
+# $ python -c "help('keywords')"
+# Keywords that are reserved in C/C++ are excluded because they can not be
+# used as variables identifiers
+python_reserved_keywords = {
+    "True", "None", "False", "as", "assert", "def", "del", "elif", "except", "exec",
+    "finally", "from", "global",  "import", "in", "is", "lambda", "nonlocal",
+    "pass", "print", "raise", "with", "yield"
+}
+
 
 def normalize_class_name(name):
     return re.sub(r"^cv\.", "", name).replace(".", "_")
@@ -371,6 +381,8 @@ class ArgInfo(object):
     def __init__(self, arg_tuple):
         self.tp = handle_ptr(arg_tuple[0])
         self.name = arg_tuple[1]
+        if self.name in python_reserved_keywords:
+            self.name += "_"
         self.defval = arg_tuple[2]
         self.isarray = False
         self.arraylen = 0

modules/python/src2/hdr_parser.py

@@ -979,7 +979,8 @@ class CppHeaderParser(object):
                                 has_mat = len(list(filter(lambda x: x[0] in {"Mat", "vector_Mat"}, args))) > 0
                                 if has_mat:
                                     _, _, _, gpumat_decl = self.parse_stmt(stmt, token, mat="cuda::GpuMat", docstring=docstring)
-                                    decls.append(gpumat_decl)
+                                    if gpumat_decl != decl:
+                                        decls.append(gpumat_decl)
 
                             if self._generate_umat_decls:
                                 # If function takes as one of arguments Mat or vector<Mat> - we want to create the
@@ -988,7 +989,8 @@ class CppHeaderParser(object):
                                 has_mat = len(list(filter(lambda x: x[0] in {"Mat", "vector_Mat"}, args))) > 0
                                 if has_mat:
                                     _, _, _, umat_decl = self.parse_stmt(stmt, token, mat="UMat", docstring=docstring)
-                                    decls.append(umat_decl)
+                                    if umat_decl != decl:
+                                        decls.append(umat_decl)
 
                         docstring = ""
                     if stmt_type == "namespace":

modules/python/test/test_misc.py

@@ -464,6 +464,23 @@ class Arguments(NewOpenCVTests):
             with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)):
                 _ = cv.utils.dumpRange(not_convertible)
 
+    def test_reserved_keywords_are_transformed(self):
+        default_lambda_value = 2
+        default_from_value = 3
+        format_str = "arg={}, lambda={}, from={}"
+        self.assertEqual(
+            cv.utils.testReservedKeywordConversion(20), format_str.format(20, default_lambda_value, default_from_value)
+        )
+        self.assertEqual(
+            cv.utils.testReservedKeywordConversion(10, lambda_=10), format_str.format(10, 10, default_from_value)
+        )
+        self.assertEqual(
+            cv.utils.testReservedKeywordConversion(10, from_=10), format_str.format(10, default_lambda_value, 10)
+        )
+        self.assertEqual(
+            cv.utils.testReservedKeywordConversion(20, lambda_=-4, from_=12), format_str.format(20, -4, 12)
+        )
+
 
 class SamplesFindFile(NewOpenCVTests):