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

cmake/OpenCVUtils.cmake

@@ -868,6 +868,7 @@ macro(ocv_check_modules define)
           list(APPEND _libs_paths ${CMAKE_MATCH_1})
         elseif(IS_ABSOLUTE "${flag}"
             OR flag STREQUAL "-lstdc++"
+            OR flag STREQUAL "-latomic"
         )
           list(APPEND _libs "${flag}")
         elseif(flag MATCHES "^-l(.*)")

doc/js_tutorials/js_imgproc/js_gradients/js_gradients.markdown

@@ -15,7 +15,7 @@ We will see each one of them.
 
 ### 1. Sobel and Scharr Derivatives
 
-Sobel operators is a joint Gausssian smoothing plus differentiation operation, so it is more
+Sobel operators is a joint Gaussian smoothing plus differentiation operation, so it is more
 resistant to noise. You can specify the direction of derivatives to be taken, vertical or horizontal
 (by the arguments, yorder and xorder respectively). You can also specify the size of kernel by the
 argument ksize. If ksize = -1, a 3x3 Scharr filter is used which gives better results than 3x3 Sobel
@@ -97,4 +97,4 @@ Try it
 <iframe src="../../js_gradients_absSobel.html" width="100%"
         onload="this.style.height=this.contentDocument.body.scrollHeight +'px';">
 </iframe>
-\endhtmlonly
+\endhtmlonly

doc/py_tutorials/py_core/py_optimization/py_optimization.markdown

@@ -14,7 +14,7 @@ So in this chapter, you will learn:
 Apart from OpenCV, Python also provides a module **time** which is helpful in measuring the time of
 execution. Another module **profile** helps to get a detailed report on the code, like how much time
 each function in the code took, how many times the function was called, etc. But, if you are using
-IPython, all these features are integrated in an user-friendly manner. We will see some important
+IPython, all these features are integrated in a user-friendly manner. We will see some important
 ones, and for more details, check links in the **Additional Resources** section.
 
 Measuring Performance with OpenCV

doc/py_tutorials/py_imgproc/py_gradients/py_gradients.markdown

@@ -17,7 +17,7 @@ We will see each one of them.
 
 ### 1. Sobel and Scharr Derivatives
 
-Sobel operators is a joint Gausssian smoothing plus differentiation operation, so it is more
+Sobel operators is a joint Gaussian smoothing plus differentiation operation, so it is more
 resistant to noise. You can specify the direction of derivatives to be taken, vertical or horizontal
 (by the arguments, yorder and xorder respectively). You can also specify the size of kernel by the
 argument ksize. If ksize = -1, a 3x3 Scharr filter is used which gives better results than 3x3 Sobel

modules/core/src/minmax.cpp

@@ -976,6 +976,12 @@ bool ocl_minMaxIdx( InputArray _src, double* minVal, double* maxVal, int* minLoc
         return false;
 #endif
 
+    if (dev.deviceVersionMajor() == 1 && dev.deviceVersionMinor() < 2)
+    {
+        // 'static' storage class specifier used by "minmaxloc" is available from OpenCL 1.2+ only
+        return false;
+    }
+
     bool doubleSupport = dev.doubleFPConfig() > 0, haveMask = !_mask.empty(),
         haveSrc2 = _src2.kind() != _InputArray::NONE;
     int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),

modules/dnn/src/ie_ngraph.cpp

@@ -204,14 +204,13 @@ class InfEngineNgraphCustomLayer : public InferenceEngine::ILayerExecImpl
         std::vector<InferenceEngine::DataConfig> outDataConfig;
 #if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2)
         InferenceEngine::SizeVector order;
-        size_t offset = std::numeric_limits<size_t>::max();
         for (int i = 0; i < node->get_input_size(); ++i)
         {
             InferenceEngine::DataConfig conf;
             auto shape = node->input_value(i).get_shape();
             order.resize(shape.size());
             std::iota(order.begin(), order.end(), 0);
-            conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order, offset});
+            conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order});
             inDataConfig.push_back(conf);
         }
 
@@ -221,7 +220,7 @@ class InfEngineNgraphCustomLayer : public InferenceEngine::ILayerExecImpl
             auto shape = node->output(i).get_shape();
             order.resize(shape.size());
             std::iota(order.begin(), order.end(), 0);
-            conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order, offset});
+            conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order});
             outDataConfig.push_back(conf);
         }
 #else

modules/dnn/test/test_backends.cpp

@@ -201,12 +201,6 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe_Different_Width_Height)
     if (backend == DNN_BACKEND_HALIDE)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_HALIDE);
 #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
     // May hang on some configurations
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
         applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,

modules/dnn/test/test_caffe_importer.cpp

@@ -726,10 +726,6 @@ TEST_P(Test_Caffe_nets, FasterRCNN_vgg16)
 #endif
 
 #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-
     // Check 'backward_compatible_check || in_out_elements_equal' failed at core/src/op/reshape.cpp:427:
     // While validating node 'v1::Reshape bbox_pred_reshape (bbox_pred[0]:f32{1,84}, Constant_265242[0]:i64{4}) -> (f32{?,?,?,?})' with friendly_name 'bbox_pred_reshape':
     // Requested output shape {1,6300,4,1} is incompatible with input shape {1, 84}
@@ -761,12 +757,6 @@ TEST_P(Test_Caffe_nets, FasterRCNN_zf)
         );
 #endif
 
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-#endif
-
     if ((backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 ||
          backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) && target == DNN_TARGET_OPENCL_FP16)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
@@ -802,15 +792,6 @@ TEST_P(Test_Caffe_nets, RFCN)
     }
 
 #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // Exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-    // Sporadic: "Cannot get memory!"
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
-        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
-            CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
-        );
-
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)
     {
         scoreDiff = 0.1f;

modules/dnn/test/test_darknet_importer.cpp

@@ -975,20 +975,10 @@ TEST_P(Test_Darknet_layers, shortcut_leaky)
 }
 TEST_P(Test_Darknet_layers, shortcut_unequal)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-#endif
     testDarknetLayer("shortcut_unequal");
 }
 TEST_P(Test_Darknet_layers, shortcut_unequal_2)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-#endif
     testDarknetLayer("shortcut_unequal_2");
 }
 

modules/dnn/test/test_halide_layers.cpp

@@ -643,12 +643,6 @@ TEST_P(NoParamActivation, Accuracy)
     Target targetId = get<1>(get<1>(GetParam()));
     std::string layer_type = get<0>(GetParam());
 
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // Cannot get memory!
-    if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && targetId == DNN_TARGET_CPU && layer_type == "BNLL")
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-#endif
-
     LayerParams lp;
     lp.type = layer_type;
     lp.name = "testLayer";

modules/dnn/test/test_layers.cpp

@@ -1486,12 +1486,6 @@ static void test_dldt_fused_output(Backend backend, Target target)
 
 TEST_P(Test_DLDT_layers, fused_output)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // IE exception: Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-#endif
-
     CV_DNN_REGISTER_LAYER_CLASS(Unsupported, UnsupportedLayer);
     try
     {
@@ -1651,16 +1645,7 @@ TEST_P(Test_Caffe_layers, Interp)
 TEST_P(Test_Caffe_layers, DISABLED_Interp)  // requires patched protobuf (available in OpenCV source tree only)
 #endif
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-    // Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
-        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
-            CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
-        );
-#elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);  // exception
 #endif

modules/dnn/test/test_model.cpp

@@ -407,19 +407,11 @@ TEST_P(Test_Model, DetectRegionWithNmsAcrossClasses)
 TEST_P(Test_Model, DetectionOutput)
 {
 #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
     // Check 'backward_compatible_check || in_out_elements_equal' failed at core/src/op/reshape.cpp:427:
     // While validating node 'v1::Reshape bbox_pred_reshape (ave_bbox_pred_rois[0]:f32{1,8,1,1}, Constant_388[0]:i64{4}) -> (f32{?,?,?,?})' with friendly_name 'bbox_pred_reshape':
     // Requested output shape {1,300,8,1} is incompatible with input shape {1, 8, 1, 1}
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
-    // Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && (target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
-        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16,
-            CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION
-        );
 #elif defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021040000)
     // Exception: Function contains several inputs and outputs with one friendly name! (HETERO bug?)
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target != DNN_TARGET_CPU)
@@ -634,9 +626,6 @@ TEST_P(Test_Model, Segmentation)
     float norm = 0;
 
 #if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2022010000)
-    // Cannot get memory!
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_CPU)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_CPU, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
     // Failed to allocate graph: NC_ERROR
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_MYRIAD)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);