release: OpenCV 3.4.15

backport of commit: e5841d3126

cmake/OpenCVCompilerOptions.cmake

@@ -177,7 +177,13 @@ if(CV_GCC OR CV_CLANG)
   endif()
 
   # We need pthread's
-  if(UNIX AND NOT ANDROID AND NOT (APPLE AND CV_CLANG)) # TODO
+  if((UNIX
+          AND NOT ANDROID
+          AND NOT (APPLE AND CV_CLANG)
+          AND NOT EMSCRIPTEN
+      )
+      OR (EMSCRIPTEN AND WITH_PTHREADS_PF)  # https://github.com/opencv/opencv/issues/20285
+  )
     add_extra_compiler_option(-pthread)
   endif()
 

cmake/OpenCVDetectHalide.cmake

@@ -9,9 +9,14 @@ set(HALIDE_ROOT_DIR "${HALIDE_ROOT_DIR}" CACHE PATH "Halide root directory")
 if(NOT HAVE_HALIDE)
   find_package(Halide QUIET) # Try CMake-based config files
   if(Halide_FOUND)
-    set(HALIDE_INCLUDE_DIRS "${Halide_INCLUDE_DIRS}" CACHE PATH "Halide include directories" FORCE)
-    set(HALIDE_LIBRARIES "${Halide_LIBRARIES}" CACHE PATH "Halide libraries" FORCE)
-    set(HAVE_HALIDE TRUE)
+    if(TARGET Halide::Halide)  # modern Halide scripts defines imported target
+      set(HALIDE_INCLUDE_DIRS "")
+      set(HALIDE_LIBRARIES "Halide::Halide")
+      set(HAVE_HALIDE TRUE)
+    else()
+      # using HALIDE_INCLUDE_DIRS / Halide_LIBRARIES
+      set(HAVE_HALIDE TRUE)
+    endif()
   endif()
 endif()
 
@@ -28,18 +33,15 @@ if(NOT HAVE_HALIDE AND HALIDE_ROOT_DIR)
   )
   if(HALIDE_LIBRARY AND HALIDE_INCLUDE_DIR)
     # TODO try_compile
-    set(HALIDE_INCLUDE_DIRS "${HALIDE_INCLUDE_DIR}" CACHE PATH "Halide include directories" FORCE)
-    set(HALIDE_LIBRARIES "${HALIDE_LIBRARY}" CACHE PATH "Halide libraries" FORCE)
+    set(HALIDE_INCLUDE_DIRS "${HALIDE_INCLUDE_DIR}")
+    set(HALIDE_LIBRARIES "${HALIDE_LIBRARY}")
     set(HAVE_HALIDE TRUE)
   endif()
-  if(NOT HAVE_HALIDE)
-    ocv_clear_vars(HALIDE_LIBRARIES HALIDE_INCLUDE_DIRS CACHE)
-  endif()
 endif()
 
 if(HAVE_HALIDE)
-  include_directories(${HALIDE_INCLUDE_DIRS})
+  if(HALIDE_INCLUDE_DIRS)
+    include_directories(${HALIDE_INCLUDE_DIRS})
+  endif()
   list(APPEND OPENCV_LINKER_LIBS ${HALIDE_LIBRARIES})
-else()
-  ocv_clear_vars(HALIDE_INCLUDE_DIRS HALIDE_LIBRARIES)
 endif()

cmake/OpenCVDetectInferenceEngine.cmake

@@ -140,12 +140,21 @@ endif()
 # Add more features to the target
 
 if(INF_ENGINE_TARGET)
-  if(NOT INF_ENGINE_RELEASE)
-    message(WARNING "InferenceEngine version has not been set, 2021.3 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
+  if(DEFINED InferenceEngine_VERSION)
+    message(STATUS "InferenceEngine: ${InferenceEngine_VERSION}")
+    if(NOT INF_ENGINE_RELEASE AND NOT (InferenceEngine_VERSION VERSION_LESS "2021.4"))
+      math(EXPR INF_ENGINE_RELEASE_INIT "${InferenceEngine_VERSION_MAJOR} * 1000000 + ${InferenceEngine_VERSION_MINOR} * 10000 + ${InferenceEngine_VERSION_PATCH} * 100")
+    endif()
   endif()
-  set(INF_ENGINE_RELEASE "2021030000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)")
+  if(NOT INF_ENGINE_RELEASE AND NOT INF_ENGINE_RELEASE_INIT)
+    message(WARNING "InferenceEngine version has not been set, 2021.4 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
+    set(INF_ENGINE_RELEASE_INIT "2021040000")
+  elseif(DEFINED INF_ENGINE_RELEASE)
+    set(INF_ENGINE_RELEASE_INIT "${INF_ENGINE_RELEASE}")
+  endif()
+  set(INF_ENGINE_RELEASE "${INF_ENGINE_RELEASE_INIT}" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)")
   set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
-    INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
+      INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
   )
 endif()
 

modules/core/include/opencv2/core/utils/filesystem.private.hpp

@@ -16,8 +16,8 @@
 #      define OPENCV_HAVE_FILESYSTEM_SUPPORT 1
 #  elif defined(__APPLE__)
 #    include <TargetConditionals.h>
-#    if (defined(TARGET_OS_OSX) && TARGET_OS_OSX) || (!defined(TARGET_OS_OSX) && !TARGET_OS_IPHONE)
-#      define OPENCV_HAVE_FILESYSTEM_SUPPORT 1 // OSX only
+#    if (defined(TARGET_OS_OSX) && TARGET_OS_OSX) || (defined(TARGET_OS_IOS) && TARGET_OS_IOS)
+#      define OPENCV_HAVE_FILESYSTEM_SUPPORT 1 // OSX, iOS only
 #    endif
 #  else
      /* unknown */

modules/core/include/opencv2/core/version.hpp

@@ -8,7 +8,7 @@
 #define CV_VERSION_MAJOR    3
 #define CV_VERSION_MINOR    4
 #define CV_VERSION_REVISION 15
-#define CV_VERSION_STATUS   "-pre"
+#define CV_VERSION_STATUS   ""
 
 #define CVAUX_STR_EXP(__A)  #__A
 #define CVAUX_STR(__A)      CVAUX_STR_EXP(__A)

modules/core/src/norm.cpp

@@ -1171,7 +1171,7 @@ double norm( InputArray _src1, InputArray _src2, int normType, InputArray _mask
         // special case to handle "integer" overflow in accumulator
         const size_t esz = src1.elemSize();
         const int total = (int)it.size;
-        const int intSumBlockSize = normType == NORM_L1 && depth <= CV_8S ? (1 << 23) : (1 << 15);
+        const int intSumBlockSize = (normType == NORM_L1 && depth <= CV_8S ? (1 << 23) : (1 << 15))/cn;
         const int blockSize = std::min(total, intSumBlockSize);
         int isum = 0;
         int count = 0;

modules/core/src/persistence.cpp

@@ -6,6 +6,8 @@
 #include "precomp.hpp"
 #include "persistence.hpp"
 
+using namespace cv;
+
 char* icv_itoa( int _val, char* buffer, int /*radix*/ )
 {
     const int radix = 10;
@@ -519,12 +521,16 @@ static const char symbols[9] = "ucwsifdr";
 
 char icvTypeSymbol(int depth)
 {
-    CV_Assert(depth >=0 && depth < 9);
+    CV_StaticAssert(CV_64F == 6, "");
+    CV_Assert(depth >=0 && depth <= CV_64F);
+    CV_CheckDepth(depth, depth >=0 && depth <= CV_64F, "");
     return symbols[depth];
 }
 
 static int icvSymbolToType(char c)
 {
+    if (c == 'r')
+        return CV_SEQ_ELTYPE_PTR;
     const char* pos = strchr( symbols, c );
     if( !pos )
         CV_Error( CV_StsBadArg, "Invalid data type specification" );
@@ -618,8 +624,12 @@ int icvCalcStructSize( const char* dt, int initial_size )
 {
     int size = icvCalcElemSize( dt, initial_size );
     size_t elem_max_size = 0;
-    for ( const char * type = dt; *type != '\0'; type++ ) {
-        switch ( *type )
+    for ( const char * type = dt; *type != '\0'; type++ )
+    {
+        char v = *type;
+        if (v >= '0' && v <= '9')
+            continue;  // skip vector size
+        switch (v)
         {
         case 'u': { elem_max_size = std::max( elem_max_size, sizeof(uchar ) ); break; }
         case 'c': { elem_max_size = std::max( elem_max_size, sizeof(schar ) ); break; }
@@ -628,7 +638,8 @@ int icvCalcStructSize( const char* dt, int initial_size )
         case 'i': { elem_max_size = std::max( elem_max_size, sizeof(int   ) ); break; }
         case 'f': { elem_max_size = std::max( elem_max_size, sizeof(float ) ); break; }
         case 'd': { elem_max_size = std::max( elem_max_size, sizeof(double) ); break; }
-        default: break;
+        default:
+            CV_Error_(Error::StsNotImplemented, ("Unknown type identifier: '%c' in '%s'", (char)(*type), dt));
         }
     }
     size = cvAlign( size, static_cast<int>(elem_max_size) );

modules/core/test/test_arithm.cpp

@@ -2117,6 +2117,15 @@ TEST(Core_Norm, IPP_regression_NORM_L1_16UC3_small)
     EXPECT_EQ((double)20*cn, cv::norm(a, b, NORM_L1, mask));
 }
 
+TEST(Core_Norm, NORM_L2_8UC4)
+{
+    // Tests there is no integer overflow in norm computation for multiple channels.
+    const int kSide = 100;
+    cv::Mat4b a(kSide, kSide, cv::Scalar(255, 255, 255, 255));
+    cv::Mat4b b = cv::Mat4b::zeros(kSide, kSide);
+    const double kNorm = 2.*kSide*255.;
+    EXPECT_EQ(kNorm, cv::norm(a, b, NORM_L2));
+}
 
 TEST(Core_ConvertTo, regression_12121)
 {

modules/dnn/misc/java/gen_dict.json

@@ -54,7 +54,7 @@
                 ]
 
             ],
-            "jni_name": "(*(cv::dnn::DictValue*)%(n)s_nativeObj)",
+            "jni_name": "(*(*(Ptr<cv::dnn::DictValue>*)%(n)s_nativeObj))",
             "jni_type": "jlong",
             "suffix": "J",
             "j_import": "org.opencv.dnn.DictValue"

modules/dnn/src/ie_ngraph.cpp

@@ -654,7 +654,11 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net)
                 try
                 {
                     InferenceEngine::IExtensionPtr extension =
+#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+                        std::make_shared<InferenceEngine::Extension>(libName);
+#else
                         InferenceEngine::make_so_pointer<InferenceEngine::IExtension>(libName);
+#endif
 
                     ie.AddExtension(extension, "CPU");
                     CV_LOG_INFO(NULL, "DNN-IE: Loaded extension plugin: " << libName);
@@ -1002,35 +1006,54 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
         reqWrapper->req.SetInput(inpBlobs);
         reqWrapper->req.SetOutput(outBlobs);
 
+#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+        InferenceEngine::InferRequest infRequest = reqWrapper->req;
+        NgraphReqWrapper* wrapperPtr = reqWrapper.get();
+        CV_Assert(wrapperPtr && "Internal error");
+#else
         InferenceEngine::IInferRequest::Ptr infRequestPtr = reqWrapper->req;
-        infRequestPtr->SetUserData(reqWrapper.get(), 0);
+        CV_Assert(infRequestPtr);
+        InferenceEngine::IInferRequest& infRequest = *infRequestPtr.get();
+        infRequest.SetUserData(reqWrapper.get(), 0);
+#endif
 
-        infRequestPtr->SetCompletionCallback(
-            [](InferenceEngine::IInferRequest::Ptr request, InferenceEngine::StatusCode status)
+#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+        // do NOT capture 'reqWrapper' (smart ptr) in the lambda callback
+        infRequest.SetCompletionCallback<std::function<void(InferenceEngine::InferRequest, InferenceEngine::StatusCode)>>(
+            [wrapperPtr](InferenceEngine::InferRequest /*request*/, InferenceEngine::StatusCode status)
+#else
+        infRequest.SetCompletionCallback(
+            [](InferenceEngine::IInferRequest::Ptr requestPtr, InferenceEngine::StatusCode status)
+#endif
             {
                 CV_LOG_DEBUG(NULL, "DNN(nGraph): completionCallback(" << (int)status << ")");
+#if !INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4)
+                CV_Assert(requestPtr);
+                InferenceEngine::IInferRequest& request = *requestPtr.get();
 
-                NgraphReqWrapper* wrapper;
-                request->GetUserData((void**)&wrapper, 0);
-                CV_Assert(wrapper && "Internal error");
+                NgraphReqWrapper* wrapperPtr;
+                request.GetUserData((void**)&wrapperPtr, 0);
+                CV_Assert(wrapperPtr && "Internal error");
+#endif
+                NgraphReqWrapper& wrapper = *wrapperPtr;
 
                 size_t processedOutputs = 0;
                 try
                 {
-                    for (; processedOutputs < wrapper->outProms.size(); ++processedOutputs)
+                    for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs)
                     {
-                        const std::string& name = wrapper->outsNames[processedOutputs];
-                        Mat m = ngraphBlobToMat(wrapper->req.GetBlob(name));
+                        const std::string& name = wrapper.outsNames[processedOutputs];
+                        Mat m = ngraphBlobToMat(wrapper.req.GetBlob(name));
 
                         try
                         {
                             CV_Assert(status == InferenceEngine::StatusCode::OK);
-                            wrapper->outProms[processedOutputs].setValue(m.clone());
+                            wrapper.outProms[processedOutputs].setValue(m.clone());
                         }
                         catch (...)
                         {
                             try {
-                                wrapper->outProms[processedOutputs].setException(std::current_exception());
+                                wrapper.outProms[processedOutputs].setException(std::current_exception());
                             } catch(...) {
                                 CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
                             }
@@ -1040,16 +1063,16 @@ void InfEngineNgraphNet::forward(const std::vector<Ptr<BackendWrapper> >& outBlo
                 catch (...)
                 {
                     std::exception_ptr e = std::current_exception();
-                    for (; processedOutputs < wrapper->outProms.size(); ++processedOutputs)
+                    for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs)
                     {
                         try {
-                            wrapper->outProms[processedOutputs].setException(e);
+                            wrapper.outProms[processedOutputs].setException(e);
                         } catch(...) {
                             CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation");
                         }
                     }
                 }
-                wrapper->isReady = true;
+                wrapper.isReady = true;
             }
         );
     }

modules/dnn/src/layers/batch_norm_layer.cpp

@@ -29,6 +29,7 @@ namespace dnn
 class BatchNormLayerImpl CV_FINAL : public BatchNormLayer
 {
 public:
+    Mat origin_weights, origin_bias;
     Mat weights_, bias_;
     UMat umat_weight, umat_bias;
     mutable int dims;
@@ -82,11 +83,11 @@ public:
         const float* weightsData = hasWeights ? blobs[weightsBlobIndex].ptr<float>() : 0;
         const float* biasData = hasBias ? blobs[biasBlobIndex].ptr<float>() : 0;
 
-        weights_.create(1, (int)n, CV_32F);
-        bias_.create(1, (int)n, CV_32F);
+        origin_weights.create(1, (int)n, CV_32F);
+        origin_bias.create(1, (int)n, CV_32F);
 
-        float* dstWeightsData = weights_.ptr<float>();
-        float* dstBiasData = bias_.ptr<float>();
+        float* dstWeightsData = origin_weights.ptr<float>();
+        float* dstBiasData = origin_bias.ptr<float>();
 
         for (size_t i = 0; i < n; ++i)
         {
@@ -94,15 +95,12 @@ public:
             dstWeightsData[i] = w;
             dstBiasData[i] = (hasBias ? biasData[i] : 0.0f) - w * meanData[i] * varMeanScale;
         }
-        // We will use blobs to store origin weights and bias to restore them in case of reinitialization.
-        weights_.copyTo(blobs[0].reshape(1, 1));
-        bias_.copyTo(blobs[1].reshape(1, 1));
     }
 
     virtual void finalize(InputArrayOfArrays, OutputArrayOfArrays) CV_OVERRIDE
     {
-        blobs[0].reshape(1, 1).copyTo(weights_);
-        blobs[1].reshape(1, 1).copyTo(bias_);
+        origin_weights.reshape(1, 1).copyTo(weights_);
+        origin_bias.reshape(1, 1).copyTo(bias_);
     }
 
     void getScaleShift(Mat& scale, Mat& shift) const CV_OVERRIDE

modules/dnn/src/layers/normalize_bbox_layer.cpp

@@ -328,7 +328,7 @@ public:
             std::iota(axes_data.begin(), axes_data.end(), 1);
         }
         auto axes = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{axes_data.size()}, axes_data);
-        auto norm = std::make_shared<ngraph::op::NormalizeL2>(ieInpNode, axes, epsilon, ngraph::op::EpsMode::ADD);
+        auto norm = std::make_shared<ngraph::op::v0::NormalizeL2>(ieInpNode, axes, epsilon, ngraph::op::EpsMode::ADD);
 
         CV_Assert(blobs.empty() || numChannels == blobs[0].total());
         std::vector<size_t> shape(ieInpNode->get_shape().size(), 1);

modules/dnn/src/onnx/onnx_importer.cpp

@@ -1792,6 +1792,23 @@ void ONNXImporter::handleNode(const opencv_onnx::NodeProto& node_proto_)
                 addConstant(layerParams.name, concatenated[0]);
                 return;
             }
+            else
+            {
+                for (int i = 0; i < node_proto.input_size(); ++i)
+                {
+                    if (constBlobs.find(node_proto.input(i)) != constBlobs.end())
+                    {
+                        LayerParams constParams;
+                        constParams.name = node_proto.input(i);
+                        constParams.type = "Const";
+                        constParams.blobs.push_back(getBlob(node_proto, i));
+
+                        opencv_onnx::NodeProto proto;
+                        proto.add_output(constParams.name);
+                        addLayer(constParams, proto);
+                    }
+                }
+            }
         }
         else if (layer_type == "Resize")
         {

modules/dnn/src/op_inf_engine.hpp

@@ -30,10 +30,11 @@
 #define INF_ENGINE_RELEASE_2021_1 2021010000
 #define INF_ENGINE_RELEASE_2021_2 2021020000
 #define INF_ENGINE_RELEASE_2021_3 2021030000
+#define INF_ENGINE_RELEASE_2021_4 2021040000
 
 #ifndef INF_ENGINE_RELEASE
-#warning("IE version have not been provided via command-line. Using 2021.3 by default")
-#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_3
+#warning("IE version have not been provided via command-line. Using 2021.4 by default")
+#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_4
 #endif
 
 #define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))

modules/dnn/test/test_backends.cpp

@@ -196,7 +196,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
     Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false);
     float diffScores = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 1.5e-2 : 0.0;
     float diffSquares = (target == DNN_TARGET_MYRIAD) ? 0.063  : 0.0;
-    float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.252  : FLT_MIN;
+    float detectionConfThresh = (target == DNN_TARGET_MYRIAD) ? 0.262  : FLT_MIN;
          processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt",
                     inp, "detection_out", "", diffScores, diffSquares, detectionConfThresh);
     expectNoFallbacksFromIE(net);
@@ -301,8 +301,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_coco)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
 #endif
 
-    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.0056 : 0.0;
-    const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.072 : 0.0;
+    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.009 : 0.0;
+    const float lInf = (target == DNN_TARGET_MYRIAD) ? 0.09 : 0.0;
     processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt",
                Size(46, 46), "", "", l1, lInf);
     expectNoFallbacksFromIE(net);
@@ -321,8 +321,8 @@ TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
 #endif
 
     // output range: [-0.001, 0.97]
-    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.012 : 0.0;
-    const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.16 : 0.0;
+    const float l1 = (target == DNN_TARGET_MYRIAD) ? 0.02 : 0.0;
+    const float lInf = (target == DNN_TARGET_MYRIAD || target == DNN_TARGET_OPENCL_FP16) ? 0.2 : 0.0;
     processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt",
                Size(46, 46), "", "", l1, lInf);
     expectNoFallbacksFromIE(net);

modules/dnn/test/test_ie_models.cpp

@@ -288,6 +288,15 @@ TEST_P(DNNTestOpenVINO, models)
     ASSERT_FALSE(backendId != DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019 && backendId != DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) <<
         "Inference Engine backend is required";
 
+#if INF_ENGINE_VER_MAJOR_EQ(2021040000)
+    if (targetId == DNN_TARGET_MYRIAD && (
+            modelName == "person-detection-retail-0013" ||  // ncDeviceOpen:1013 Failed to find booted device after boot
+            modelName == "age-gender-recognition-retail-0013"  // ncDeviceOpen:1013 Failed to find booted device after boot
+        )
+    )
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, CV_TEST_TAG_DNN_SKIP_IE_VERSION);
+#endif
+
 #if INF_ENGINE_VER_MAJOR_GE(2020020000)
     if (targetId == DNN_TARGET_MYRIAD && backendId == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
     {

modules/dnn/test/test_onnx_importer.cpp

@@ -327,6 +327,7 @@ TEST_P(Test_ONNX_layers, Concatenation)
         if (target == DNN_TARGET_MYRIAD)      applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
     }
     testONNXModels("concatenation");
+    testONNXModels("concat_const_blobs");
 }
 
 TEST_P(Test_ONNX_layers, Eltwise3D)

modules/dnn/test/test_torch_importer.cpp

@@ -254,9 +254,14 @@ TEST_P(Test_Torch_layers, net_padding)
 
 TEST_P(Test_Torch_layers, net_non_spatial)
 {
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2021030000)
+#if defined(INF_ENGINE_RELEASE) && ( \
+    INF_ENGINE_VER_MAJOR_EQ(2021030000) || \
+    INF_ENGINE_VER_MAJOR_EQ(2021040000) \
+)
     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);  // crash
+        // 2021.3: crash
+        // 2021.4: [ GENERAL_ERROR ]  AssertionFailed: !out.networkInputs.empty()
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL)
         applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL, CV_TEST_TAG_DNN_SKIP_IE_NGRAPH);  // exception
     if (backend == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH && target == DNN_TARGET_OPENCL_FP16)

modules/features2d/include/opencv2/features2d.hpp

@@ -1314,6 +1314,13 @@ CV_EXPORTS_W void drawMatches( InputArray img1, const std::vector<KeyPoint>& key
                              const std::vector<char>& matchesMask=std::vector<char>(), int flags=DrawMatchesFlags::DEFAULT );
 
 /** @overload */
+CV_EXPORTS_W void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
+                             InputArray img2, const std::vector<KeyPoint>& keypoints2,
+                             const std::vector<DMatch>& matches1to2, InputOutputArray outImg,
+                             const int matchesThickness, const Scalar& matchColor=Scalar::all(-1),
+                             const Scalar& singlePointColor=Scalar::all(-1), const std::vector<char>& matchesMask=std::vector<char>(),
+                             int flags=DrawMatchesFlags::DEFAULT );
+
 CV_EXPORTS_AS(drawMatchesKnn) void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
                              InputArray img2, const std::vector<KeyPoint>& keypoints2,
                              const std::vector<std::vector<DMatch> >& matches1to2, InputOutputArray outImg,

modules/features2d/src/draw.cpp

@@ -183,7 +183,8 @@ static void _prepareImgAndDrawKeypoints( InputArray img1, const std::vector<KeyP
 }
 
 static inline void _drawMatch( InputOutputArray outImg, InputOutputArray outImg1, InputOutputArray outImg2 ,
-                          const KeyPoint& kp1, const KeyPoint& kp2, const Scalar& matchColor, int flags )
+                          const KeyPoint& kp1, const KeyPoint& kp2, const Scalar& matchColor, int flags,
+                          const int matchesThickness )
 {
     RNG& rng = theRNG();
     bool isRandMatchColor = matchColor == Scalar::all(-1);
@@ -199,7 +200,7 @@ static inline void _drawMatch( InputOutputArray outImg, InputOutputArray outImg1
     line( outImg,
           Point(cvRound(pt1.x*draw_multiplier), cvRound(pt1.y*draw_multiplier)),
           Point(cvRound(dpt2.x*draw_multiplier), cvRound(dpt2.y*draw_multiplier)),
-          color, 1, LINE_AA, draw_shift_bits );
+          color, matchesThickness, LINE_AA, draw_shift_bits );
 }
 
 void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
@@ -207,6 +208,21 @@ void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
                   const std::vector<DMatch>& matches1to2, InputOutputArray outImg,
                   const Scalar& matchColor, const Scalar& singlePointColor,
                   const std::vector<char>& matchesMask, int flags )
+{
+    drawMatches( img1, keypoints1,
+                 img2, keypoints2,
+                 matches1to2, outImg,
+                 1, matchColor,
+                 singlePointColor, matchesMask,
+                 flags);
+}
+
+void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
+                  InputArray img2, const std::vector<KeyPoint>& keypoints2,
+                  const std::vector<DMatch>& matches1to2, InputOutputArray outImg,
+                  const int matchesThickness, const Scalar& matchColor,
+                  const Scalar& singlePointColor, const std::vector<char>& matchesMask,
+                  int flags )
 {
     if( !matchesMask.empty() && matchesMask.size() != matches1to2.size() )
         CV_Error( Error::StsBadSize, "matchesMask must have the same size as matches1to2" );
@@ -226,11 +242,12 @@ void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
             CV_Assert(i2 >= 0 && i2 < static_cast<int>(keypoints2.size()));
 
             const KeyPoint &kp1 = keypoints1[i1], &kp2 = keypoints2[i2];
-            _drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags );
+            _drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags, matchesThickness );
         }
     }
 }
 
+
 void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
                   InputArray img2, const std::vector<KeyPoint>& keypoints2,
                   const std::vector<std::vector<DMatch> >& matches1to2, InputOutputArray outImg,
@@ -254,7 +271,7 @@ void drawMatches( InputArray img1, const std::vector<KeyPoint>& keypoints1,
             if( matchesMask.empty() || matchesMask[i][j] )
             {
                 const KeyPoint &kp1 = keypoints1[i1], &kp2 = keypoints2[i2];
-                _drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags );
+                _drawMatch( outImg, outImg1, outImg2, kp1, kp2, matchColor, flags, 1 );
             }
         }
     }

modules/highgui/src/window_gtk.cpp

@@ -1881,6 +1881,7 @@ static gboolean icvOnMouse( GtkWidget *widget, GdkEvent *event, gpointer user_da
                (unsigned)pt.y < (unsigned)(image_widget->original_image->height)
             ))
         {
+            state &= gtk_accelerator_get_default_mod_mask();
             flags |= BIT_MAP(state, GDK_SHIFT_MASK,   CV_EVENT_FLAG_SHIFTKEY) |
                 BIT_MAP(state, GDK_CONTROL_MASK, CV_EVENT_FLAG_CTRLKEY)  |
                 BIT_MAP(state, GDK_MOD1_MASK,    CV_EVENT_FLAG_ALTKEY)   |

modules/imgproc/src/intersection.cpp

@@ -47,24 +47,16 @@
 namespace cv
 {
 
-int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, OutputArray intersectingRegion )
+static int _rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, std::vector<Point2f> &intersection )
 {
     CV_INSTRUMENT_REGION();
 
     // L2 metric
     const float samePointEps = std::max(1e-16f, 1e-6f * (float)std::max(rect1.size.area(), rect2.size.area()));
 
-    if (rect1.size.empty() || rect2.size.empty())
-    {
-        intersectingRegion.release();
-        return INTERSECT_NONE;
-    }
-
     Point2f vec1[4], vec2[4];
     Point2f pts1[4], pts2[4];
 
-    std::vector <Point2f> intersection; intersection.reserve(24);
-
     rect1.points(pts1);
     rect2.points(pts2);
 
@@ -92,8 +84,6 @@ int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& r
                 intersection[i] = pts1[i];
             }
 
-            Mat(intersection).copyTo(intersectingRegion);
-
             return INTERSECT_FULL;
         }
     }
@@ -300,7 +290,50 @@ int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& r
     }
 
     intersection.resize(N);
-    Mat(intersection).copyTo(intersectingRegion);
+
+    return ret;
+}
+
+int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, OutputArray intersectingRegion )
+{
+    CV_INSTRUMENT_REGION();
+
+    if (rect1.size.empty() || rect2.size.empty())
+    {
+        intersectingRegion.release();
+        return INTERSECT_NONE;
+    }
+
+    // Shift rectangles closer to origin (0, 0) to improve the calculation of the intesection region
+    // To do that, the average center of the rectangles is moved to the origin
+    const Point2f averageCenter = (rect1.center + rect2.center) / 2.0f;
+
+    RotatedRect shiftedRect1(rect1);
+    RotatedRect shiftedRect2(rect2);
+
+    // Move rectangles closer to origin
+    shiftedRect1.center -= averageCenter;
+    shiftedRect2.center -= averageCenter;
+
+    std::vector <Point2f> intersection; intersection.reserve(24);
+
+    const int ret = _rotatedRectangleIntersection(shiftedRect1, shiftedRect2, intersection);
+
+    // If return is not None, the intersection Points are shifted back to the original position
+    // and copied to the interesectingRegion
+    if (ret != INTERSECT_NONE)
+    {
+        for (size_t i = 0; i < intersection.size(); ++i)
+        {
+            intersection[i] += averageCenter;
+        }
+
+        Mat(intersection).copyTo(intersectingRegion);
+    }
+    else
+    {
+        intersectingRegion.release();
+    }
 
     return ret;
 }

modules/imgproc/test/test_intersection.cpp

@@ -391,4 +391,21 @@ TEST(Imgproc_RotatedRectangleIntersection, regression_18520)
     }
 }
 
+TEST(Imgproc_RotatedRectangleIntersection, regression_19824)
+{
+    RotatedRect r1(
+        Point2f(246805.033f, 4002326.94f),
+        Size2f(26.40587f, 6.20026f),
+        -62.10156f);
+    RotatedRect r2(
+        Point2f(246805.122f, 4002326.59f),
+        Size2f(27.4821f, 8.5361f),
+        -56.33761f);
+
+    std::vector<Point2f> intersections;
+    int interType = cv::rotatedRectangleIntersection(r1, r2, intersections);
+    EXPECT_EQ(INTERSECT_PARTIAL, interType);
+    EXPECT_LE(intersections.size(), (size_t)7);
+}
+
 }} // namespace

modules/java/generator/gen_java.py

@@ -224,6 +224,9 @@ class ClassInfo(GeneralInfo):
         for m in decl[2]:
             if m.startswith("="):
                 self.jname = m[1:]
+            if m == '/Simple':
+                self.smart = False
+
         self.base = ''
         if decl[1]:
             #self.base = re.sub(r"\b"+self.jname+r"\b", "", decl[1].replace(":", "")).strip()
@@ -370,7 +373,7 @@ class JavaWrapperGenerator(object):
 
     def clear(self):
         self.namespaces = ["cv"]
-        self.classes = { "Mat" : ClassInfo([ 'class Mat', '', [], [] ], self.namespaces) }
+        self.classes = { "Mat" : ClassInfo([ 'class Mat', '', ['/Simple'], [] ], self.namespaces) }
         self.module = ""
         self.Module = ""
         self.ported_func_list = []
@@ -390,10 +393,15 @@ class JavaWrapperGenerator(object):
         if name in type_dict and not classinfo.base:
             logging.warning('duplicated: %s', classinfo)
             return
+        if self.isSmartClass(classinfo):
+            jni_name = "*((*(Ptr<"+classinfo.fullName(isCPP=True)+">*)%(n)s_nativeObj).get())"
+        else:
+            jni_name = "(*("+classinfo.fullName(isCPP=True)+"*)%(n)s_nativeObj)"
         type_dict.setdefault(name, {}).update(
             { "j_type" : classinfo.jname,
               "jn_type" : "long", "jn_args" : (("__int64", ".nativeObj"),),
-              "jni_name" : "(*("+classinfo.fullName(isCPP=True)+"*)%(n)s_nativeObj)", "jni_type" : "jlong",
+              "jni_name" : jni_name,
+              "jni_type" : "jlong",
               "suffix" : "J",
               "j_import" : "org.opencv.%s.%s" % (self.module, classinfo.jname)
             }
@@ -401,7 +409,8 @@ class JavaWrapperGenerator(object):
         type_dict.setdefault(name+'*', {}).update(
             { "j_type" : classinfo.jname,
               "jn_type" : "long", "jn_args" : (("__int64", ".nativeObj"),),
-              "jni_name" : "("+classinfo.fullName(isCPP=True)+"*)%(n)s_nativeObj", "jni_type" : "jlong",
+              "jni_name" : "&("+jni_name+")",
+              "jni_type" : "jlong",
               "suffix" : "J",
               "j_import" : "org.opencv.%s.%s" % (self.module, classinfo.jname)
             }
@@ -889,7 +898,13 @@ class JavaWrapperGenerator(object):
                 ret = "return env->NewStringUTF(_retval_.c_str());"
                 default = 'return env->NewStringUTF("");'
             elif self.isWrapped(fi.ctype): # wrapped class:
-                ret = "return (jlong) new %s(_retval_);" % self.fullTypeName(fi.ctype)
+                ret = None
+                if fi.ctype in self.classes:
+                    ret_ci = self.classes[fi.ctype]
+                    if self.isSmartClass(ret_ci):
+                        ret = "return (jlong)(new Ptr<%(ctype)s>(new %(ctype)s(_retval_)));" % { 'ctype': self.fullTypeName(fi.ctype) }
+                if ret is None:
+                    ret = "return (jlong) new %s(_retval_);" % self.fullTypeName(fi.ctype)
             elif fi.ctype.startswith('Ptr_'):
                 c_prologue.append("typedef Ptr<%s> %s;" % (self.fullTypeName(fi.ctype[4:]), fi.ctype))
                 ret = "return (jlong)(new %(ctype)s(_retval_));" % { 'ctype':fi.ctype }
@@ -1128,17 +1143,7 @@ JNIEXPORT void JNICALL Java_org_opencv_%(module)s_%(j_cls)s_delete
         if ci.smart != None:
             return ci.smart
 
-        # if parents are smart (we hope) then children are!
-        # if not we believe the class is smart if it has "create" method
-        ci.smart = False
-        if ci.base or ci.name == 'Algorithm':
-            ci.smart = True
-        else:
-            for fi in ci.methods:
-                if fi.name == "create":
-                    ci.smart = True
-                    break
-
+        ci.smart = True  # smart class is not properly handled in case of base/derived classes
         return ci.smart
 
     def smartWrap(self, ci, fullname):

platforms/winpack_dldt/2021.4/20210630-dldt-disable-multidevice-autoplugin.patch

@@ -0,0 +1,16 @@
+diff --git a/inference-engine/src/CMakeLists.txt b/inference-engine/src/CMakeLists.txt
+index 0ba0dd78..7d34e7cb 100644
+--- a/inference-engine/src/CMakeLists.txt
++++ b/inference-engine/src/CMakeLists.txt
+@@ -26,9 +26,9 @@ endif()
+ 
+ add_subdirectory(hetero_plugin)
+ 
+-add_subdirectory(auto_plugin)
++#add_subdirectory(auto_plugin)
+ 
+-add_subdirectory(multi_device)
++#add_subdirectory(multi_device)
+ 
+ add_subdirectory(transformations)
+ 

platforms/winpack_dldt/2021.4/20210630-dldt-disable-unused-targets.patch

@@ -0,0 +1,219 @@
+diff --git a/cmake/developer_package/add_ie_target.cmake b/cmake/developer_package/add_ie_target.cmake
+index d49f16a4d..2726ca787 100644
+--- a/cmake/developer_package/add_ie_target.cmake
++++ b/cmake/developer_package/add_ie_target.cmake
+@@ -92,7 +92,7 @@ function(addIeTarget)
+     if (ARG_TYPE STREQUAL EXECUTABLE)
+         add_executable(${ARG_NAME} ${all_sources})
+     elseif(ARG_TYPE STREQUAL STATIC OR ARG_TYPE STREQUAL SHARED)
+-        add_library(${ARG_NAME} ${ARG_TYPE} ${all_sources})
++        add_library(${ARG_NAME} ${ARG_TYPE} EXCLUDE_FROM_ALL ${all_sources})
+     else()
+         message(SEND_ERROR "Invalid target type ${ARG_TYPE} specified for target name ${ARG_NAME}")
+     endif()
+diff --git a/inference-engine/CMakeLists.txt b/inference-engine/CMakeLists.txt
+index 1ac7fd8bf..df7091e51 100644
+--- a/inference-engine/CMakeLists.txt
++++ b/inference-engine/CMakeLists.txt
+@@ -39,7 +39,7 @@ if(ENABLE_TESTS)
+     add_subdirectory(tests)
+ endif()
+ 
+-add_subdirectory(tools)
++#add_subdirectory(tools)
+ 
+ function(ie_build_samples)
+     # samples should be build with the same flags as from OpenVINO package,
+@@ -58,7 +58,7 @@ endfunction()
+ 
+ # gflags and format_reader targets are kept inside of samples directory and
+ # they must be built even if samples build is disabled (required for tests and tools).
+-ie_build_samples()
++#ie_build_samples()
+ 
+ if(ENABLE_PYTHON)
+     add_subdirectory(ie_bridges/python)
+@@ -142,7 +142,7 @@ endif()
+ # Developer package
+ #
+ 
+-openvino_developer_export_targets(COMPONENT openvino_common TARGETS format_reader gflags ie_samples_utils)
++#openvino_developer_export_targets(COMPONENT openvino_common TARGETS format_reader gflags ie_samples_utils)
+ 
+ # for Template plugin
+ if(NGRAPH_INTERPRETER_ENABLE)
+@@ -166,7 +166,7 @@ function(ie_generate_dev_package_config)
+                 @ONLY)
+ endfunction()
+ 
+-ie_generate_dev_package_config()
++#ie_generate_dev_package_config()
+ 
+ #
+ # Coverage
+diff --git a/inference-engine/src/inference_engine/CMakeLists.txt b/inference-engine/src/inference_engine/CMakeLists.txt
+index e8ed1a5c4..1fc9fc3ff 100644
+--- a/inference-engine/src/inference_engine/CMakeLists.txt
++++ b/inference-engine/src/inference_engine/CMakeLists.txt
+@@ -110,7 +110,7 @@ add_cpplint_target(${TARGET_NAME}_plugin_api_cpplint FOR_SOURCES ${plugin_api_sr
+ 
+ # Create object library
+ 
+-add_library(${TARGET_NAME}_obj OBJECT
++add_library(${TARGET_NAME}_obj OBJECT EXCLUDE_FROM_ALL
+             ${LIBRARY_SRC}
+             ${LIBRARY_HEADERS}
+             ${PUBLIC_HEADERS})
+@@ -181,7 +181,7 @@ ie_add_api_validator_post_build_step(TARGET ${TARGET_NAME})
+ 
+ # Static library used for unit tests which are always built
+ 
+-add_library(${TARGET_NAME}_s STATIC
++add_library(${TARGET_NAME}_s STATIC EXCLUDE_FROM_ALL
+             $<TARGET_OBJECTS:${TARGET_NAME}_legacy_obj>
+             $<TARGET_OBJECTS:${TARGET_NAME}_obj>
+             ${IE_STATIC_DEPENDENT_FILES})
+diff --git a/inference-engine/src/legacy_api/CMakeLists.txt b/inference-engine/src/legacy_api/CMakeLists.txt
+index 8eae82bd2..e0e6745b1 100644
+--- a/inference-engine/src/legacy_api/CMakeLists.txt
++++ b/inference-engine/src/legacy_api/CMakeLists.txt
+@@ -26,7 +26,7 @@ endif()
+ 
+ file(TOUCH ${CMAKE_CURRENT_BINARY_DIR}/dummy.cpp)
+ 
+-add_library(${TARGET_NAME}_obj OBJECT
++add_library(${TARGET_NAME}_obj OBJECT EXCLUDE_FROM_ALL
+             ${LIBRARY_SRC}
+             ${PUBLIC_HEADERS})
+ 
+diff --git a/inference-engine/src/mkldnn_plugin/CMakeLists.txt b/inference-engine/src/mkldnn_plugin/CMakeLists.txt
+index fe57b29dd..07831e2fb 100644
+--- a/inference-engine/src/mkldnn_plugin/CMakeLists.txt
++++ b/inference-engine/src/mkldnn_plugin/CMakeLists.txt
+@@ -67,7 +67,7 @@ ie_add_api_validator_post_build_step(TARGET ${TARGET_NAME})
+ 
+ #  add test object library
+ 
+-add_library(${TARGET_NAME}_obj OBJECT ${SOURCES} ${HEADERS})
++add_library(${TARGET_NAME}_obj OBJECT EXCLUDE_FROM_ALL ${SOURCES} ${HEADERS})
+ target_link_libraries(${TARGET_NAME}_obj PUBLIC mkldnn)
+ 
+ target_include_directories(${TARGET_NAME}_obj PRIVATE $<TARGET_PROPERTY:inference_engine_preproc_s,INTERFACE_INCLUDE_DIRECTORIES>
+diff --git a/inference-engine/src/preprocessing/CMakeLists.txt b/inference-engine/src/preprocessing/CMakeLists.txt
+index f9548339d..ef962145a 100644
+--- a/inference-engine/src/preprocessing/CMakeLists.txt
++++ b/inference-engine/src/preprocessing/CMakeLists.txt
+@@ -101,7 +101,7 @@ endif()
+ 
+ # Create object library
+ 
+-add_library(${TARGET_NAME}_obj OBJECT
++add_library(${TARGET_NAME}_obj OBJECT EXCLUDE_FROM_ALL
+             ${LIBRARY_SRC}
+             ${LIBRARY_HEADERS})
+ 
+@@ -153,7 +153,7 @@ ie_add_api_validator_post_build_step(TARGET ${TARGET_NAME})
+ 
+ # Static library used for unit tests which are always built
+ 
+-add_library(${TARGET_NAME}_s STATIC
++add_library(${TARGET_NAME}_s STATIC EXCLUDE_FROM_ALL
+             $<TARGET_OBJECTS:${TARGET_NAME}_obj>)
+ 
+ set_ie_threading_interface_for(${TARGET_NAME}_s)
+diff --git a/inference-engine/src/vpu/common/CMakeLists.txt b/inference-engine/src/vpu/common/CMakeLists.txt
+index 249e47c28..4ddf63049 100644
+--- a/inference-engine/src/vpu/common/CMakeLists.txt
++++ b/inference-engine/src/vpu/common/CMakeLists.txt
+@@ -5,7 +5,7 @@
+ file(GLOB_RECURSE SOURCES *.cpp *.hpp *.h)
+ 
+ function(add_common_target TARGET_NAME STATIC_IE)
+-    add_library(${TARGET_NAME} STATIC ${SOURCES})
++    add_library(${TARGET_NAME} STATIC EXCLUDE_FROM_ALL ${SOURCES})
+ 
+     ie_faster_build(${TARGET_NAME}
+         UNITY
+@@ -60,7 +60,7 @@ add_common_target("vpu_common_lib" FALSE)
+ 
+ # Unit tests support for graph transformer
+ if(WIN32)
+-    add_common_target("vpu_common_lib_test_static" TRUE)
++    #add_common_target("vpu_common_lib_test_static" TRUE)
+ else()
+     add_library("vpu_common_lib_test_static" ALIAS "vpu_common_lib")
+ endif()
+diff --git a/inference-engine/src/vpu/graph_transformer/CMakeLists.txt b/inference-engine/src/vpu/graph_transformer/CMakeLists.txt
+index bc73ab5b1..b4c1547fc 100644
+--- a/inference-engine/src/vpu/graph_transformer/CMakeLists.txt
++++ b/inference-engine/src/vpu/graph_transformer/CMakeLists.txt
+@@ -5,7 +5,7 @@
+ file(GLOB_RECURSE SOURCES *.cpp *.hpp *.h *.inc)
+ 
+ function(add_graph_transformer_target TARGET_NAME STATIC_IE)
+-    add_library(${TARGET_NAME} STATIC ${SOURCES})
++    add_library(${TARGET_NAME} STATIC EXCLUDE_FROM_ALL ${SOURCES})
+ 
+     set_ie_threading_interface_for(${TARGET_NAME})
+ 
+@@ -70,7 +70,7 @@ add_graph_transformer_target("vpu_graph_transformer" FALSE)
+ 
+ # Unit tests support for graph transformer
+ if(WIN32)
+-    add_graph_transformer_target("vpu_graph_transformer_test_static" TRUE)
++    #add_graph_transformer_target("vpu_graph_transformer_test_static" TRUE)
+ else()
+     add_library("vpu_graph_transformer_test_static" ALIAS "vpu_graph_transformer")
+ endif()
+diff --git a/inference-engine/thirdparty/pugixml/CMakeLists.txt b/inference-engine/thirdparty/pugixml/CMakeLists.txt
+index 8bcb2801a..f7e031c01 100644
+--- a/inference-engine/thirdparty/pugixml/CMakeLists.txt
++++ b/inference-engine/thirdparty/pugixml/CMakeLists.txt
+@@ -41,7 +41,7 @@ if(BUILD_SHARED_LIBS)
+ else()
+ 	add_library(pugixml STATIC ${SOURCES})
+ 	if (MSVC)
+-		add_library(pugixml_mt STATIC ${SOURCES})
++                #add_library(pugixml_mt STATIC ${SOURCES})
+ 		#if (WIN32)
+ 		#	set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /MT")
+ 		#	set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /MTd")
+diff --git a/ngraph/core/builder/CMakeLists.txt b/ngraph/core/builder/CMakeLists.txt
+index ff5c381e7..2797ec9ab 100644
+--- a/ngraph/core/builder/CMakeLists.txt
++++ b/ngraph/core/builder/CMakeLists.txt
+@@ -16,7 +16,7 @@ source_group("src" FILES ${LIBRARY_SRC})
+ source_group("include" FILES ${PUBLIC_HEADERS})
+ 
+ # Create shared library
+-add_library(${TARGET_NAME} STATIC ${LIBRARY_SRC} ${PUBLIC_HEADERS})
++add_library(${TARGET_NAME} STATIC EXCLUDE_FROM_ALL ${LIBRARY_SRC} ${PUBLIC_HEADERS})
+ 
+ if(COMMAND ie_faster_build)
+     ie_faster_build(${TARGET_NAME}
+diff --git a/ngraph/core/reference/CMakeLists.txt b/ngraph/core/reference/CMakeLists.txt
+index ef4a764ab..f6d3172e2 100644
+--- a/ngraph/core/reference/CMakeLists.txt
++++ b/ngraph/core/reference/CMakeLists.txt
+@@ -16,7 +16,7 @@ source_group("src" FILES ${LIBRARY_SRC})
+ source_group("include" FILES ${PUBLIC_HEADERS})
+ 
+ # Create shared library
+-add_library(${TARGET_NAME} STATIC ${LIBRARY_SRC} ${PUBLIC_HEADERS})
++add_library(${TARGET_NAME} STATIC EXCLUDE_FROM_ALL ${LIBRARY_SRC} ${PUBLIC_HEADERS})
+ 
+ if(COMMAND ie_faster_build)
+     ie_faster_build(${TARGET_NAME}
+diff --git a/openvino/itt/CMakeLists.txt b/openvino/itt/CMakeLists.txt
+index e9f880b8c..c63f4df63 100644
+--- a/openvino/itt/CMakeLists.txt
++++ b/openvino/itt/CMakeLists.txt
+@@ -6,7 +6,7 @@ set(TARGET_NAME itt)
+ 
+ file(GLOB_RECURSE SOURCES "src/*.cpp" "src/*.hpp")
+ 
+-add_library(${TARGET_NAME} STATIC ${SOURCES})
++add_library(${TARGET_NAME} STATIC EXCLUDE_FROM_ALL ${SOURCES})
+ 
+ add_library(openvino::itt ALIAS ${TARGET_NAME})
+ 

platforms/winpack_dldt/2021.4/20210630-dldt-pdb.patch

@@ -0,0 +1,15 @@
+iff --git a/CMakeLists.txt b/CMakeLists.txt
+index e0706a72e..9a053b1e4 100644
+--- a/CMakeLists.txt
++++ b/CMakeLists.txt
+@@ -6,6 +6,10 @@ cmake_minimum_required(VERSION 3.13)
+ 
+ project(OpenVINO)
+ 
++set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /Zi /FS")
++set(CMAKE_SHARED_LINKER_FLAGS_RELEASE "${CMAKE_SHARED_LINKER_FLAGS_RELEASE} /DEBUG /OPT:REF /OPT:ICF")
++set(CMAKE_MODULE_LINKER_FLAGS_RELEASE "${CMAKE_SHARED_LINKER_FLAGS_RELEASE} /DEBUG /OPT:REF /OPT:ICF")
++
+ set(OpenVINO_MAIN_SOURCE_DIR ${CMAKE_CURRENT_SOURCE_DIR})
+ set(IE_MAIN_SOURCE_DIR ${OpenVINO_MAIN_SOURCE_DIR}/inference-engine)
+ 

platforms/winpack_dldt/2021.4/20210630-dldt-vs-version.patch

@@ -0,0 +1,16 @@
+diff --git a/cmake/developer_package/vs_version/vs_version.cmake b/cmake/developer_package/vs_version/vs_version.cmake
+index 14d4c0e1e..6a44f73b9 100644
+--- a/cmake/developer_package/vs_version/vs_version.cmake
++++ b/cmake/developer_package/vs_version/vs_version.cmake
+@@ -8,9 +8,9 @@ set(IE_VS_VER_FILEVERSION_STR "${IE_VERSION_MAJOR}.${IE_VERSION_MINOR}.${IE_VERS
+ 
+ set(IE_VS_VER_COMPANY_NAME_STR "Intel Corporation")
+ set(IE_VS_VER_PRODUCTVERSION_STR "${CI_BUILD_NUMBER}")
+-set(IE_VS_VER_PRODUCTNAME_STR "OpenVINO toolkit")
++set(IE_VS_VER_PRODUCTNAME_STR "OpenVINO toolkit (for OpenCV Windows package)")
+ set(IE_VS_VER_COPYRIGHT_STR "Copyright (C) 2018-2021, Intel Corporation")
+-set(IE_VS_VER_COMMENTS_STR "https://docs.openvinotoolkit.org/")
++set(IE_VS_VER_COMMENTS_STR "https://github.com/opencv/opencv/wiki/Intel%27s-Deep-Learning-Inference-Engine-backend")
+ 
+ #
+ # ie_add_vs_version_file(NAME <name>

platforms/winpack_dldt/2021.4/build.config.py

@@ -0,0 +1 @@
+os.environ['CI_BUILD_NUMBER'] = '2021.4.0-opencv_winpack_dldt'

platforms/winpack_dldt/2021.4/patch.config.py

@@ -0,0 +1,4 @@
+applyPatch('20210630-dldt-disable-unused-targets.patch')
+applyPatch('20210630-dldt-pdb.patch')
+applyPatch('20210630-dldt-disable-multidevice-autoplugin.patch')
+applyPatch('20210630-dldt-vs-version.patch')

platforms/winpack_dldt/2021.4/sysroot.config.py

@@ -0,0 +1,56 @@
+sysroot_bin_dir = prepare_dir(self.sysrootdir / 'bin')
+copytree(self.build_dir / 'install', self.sysrootdir / 'ngraph')
+#rm_one(self.sysrootdir / 'ngraph' / 'lib' / 'ngraph.dll')
+
+build_config = 'Release' if not self.config.build_debug else 'Debug'
+build_bin_dir = self.build_dir / 'bin' / 'intel64' / build_config
+
+def copy_bin(name):
+    global build_bin_dir, sysroot_bin_dir
+    copytree(build_bin_dir / name, sysroot_bin_dir / name)
+
+dll_suffix = 'd' if self.config.build_debug else ''
+def copy_dll(name):
+    global copy_bin, dll_suffix
+    copy_bin(name + dll_suffix + '.dll')
+    copy_bin(name + dll_suffix + '.pdb')
+
+copy_bin('cache.json')
+copy_dll('clDNNPlugin')
+copy_dll('HeteroPlugin')
+copy_dll('inference_engine')
+copy_dll('inference_engine_ir_reader')
+#copy_dll('inference_engine_ir_v7_reader')
+copy_dll('inference_engine_legacy')
+copy_dll('inference_engine_transformations')  # runtime
+copy_dll('inference_engine_lp_transformations')  # runtime
+#copy_dll('inference_engine_preproc')  # runtime
+copy_dll('MKLDNNPlugin')  # runtime
+copy_dll('myriadPlugin')  # runtime
+#copy_dll('MultiDevicePlugin')  # runtime, not used
+copy_dll('ngraph')
+copy_bin('plugins.xml')
+copy_bin('pcie-ma2x8x.elf')
+copy_bin('usb-ma2x8x.mvcmd')
+
+copytree(self.srcdir / 'inference-engine' / 'temp' / 'tbb' / 'bin', sysroot_bin_dir)
+copytree(self.srcdir / 'inference-engine' / 'temp' / 'tbb', self.sysrootdir / 'tbb')
+
+sysroot_ie_dir = prepare_dir(self.sysrootdir / 'deployment_tools' / 'inference_engine')
+sysroot_ie_lib_dir = prepare_dir(sysroot_ie_dir / 'lib' / 'intel64')
+
+copytree(self.srcdir / 'inference-engine' / 'include', sysroot_ie_dir / 'include')
+if not self.config.build_debug:
+    copytree(build_bin_dir / 'ngraph.lib', sysroot_ie_lib_dir / 'ngraph.lib')
+    copytree(build_bin_dir / 'inference_engine.lib', sysroot_ie_lib_dir / 'inference_engine.lib')
+    copytree(build_bin_dir / 'inference_engine_ir_reader.lib', sysroot_ie_lib_dir / 'inference_engine_ir_reader.lib')
+    copytree(build_bin_dir / 'inference_engine_legacy.lib', sysroot_ie_lib_dir / 'inference_engine_legacy.lib')
+else:
+    copytree(build_bin_dir / 'ngraphd.lib', sysroot_ie_lib_dir / 'ngraphd.lib')
+    copytree(build_bin_dir / 'inference_engined.lib', sysroot_ie_lib_dir / 'inference_engined.lib')
+    copytree(build_bin_dir / 'inference_engine_ir_readerd.lib', sysroot_ie_lib_dir / 'inference_engine_ir_readerd.lib')
+    copytree(build_bin_dir / 'inference_engine_legacyd.lib', sysroot_ie_lib_dir / 'inference_engine_legacyd.lib')
+
+sysroot_license_dir = prepare_dir(self.sysrootdir / 'etc' / 'licenses')
+copytree(self.srcdir / 'LICENSE', sysroot_license_dir / 'dldt-LICENSE')
+copytree(self.sysrootdir / 'tbb/LICENSE', sysroot_license_dir / 'tbb-LICENSE')

platforms/winpack_dldt/build_package.py

@@ -214,7 +214,7 @@ class BuilderDLDT:
             patch_hashsum = hashlib.md5(self.patch_file_contents.encode('utf-8')).hexdigest()
         except:
             log.warn("Can't compute hashsum of patches: %s", self.patch_file)
-        self.patch_hashsum = patch_hashsum
+        self.patch_hashsum = self.config.override_patch_hashsum if self.config.override_patch_hashsum else patch_hashsum
 
 
     def prepare_sources(self):
@@ -355,7 +355,6 @@ class Builder:
             BUILD_PERF_TESTS='OFF',
             ENABLE_CXX11='ON',
             WITH_INF_ENGINE='ON',
-            INF_ENGINE_RELEASE=str(self.config.dldt_release),
             WITH_TBB='ON',
             CPU_BASELINE='AVX2',
             CMAKE_INSTALL_PREFIX=str(self.install_dir),
@@ -381,6 +380,9 @@ class Builder:
             OPENCV_PYTHON_INSTALL_PATH='python',
         )
 
+        if self.config.dldt_release:
+            cmake_vars['INF_ENGINE_RELEASE'] = str(self.config.dldt_release)
+
         cmake_vars['INF_ENGINE_LIB_DIRS:PATH'] = str(builderDLDT.sysrootdir / 'deployment_tools/inference_engine/lib/intel64')
         assert os.path.exists(cmake_vars['INF_ENGINE_LIB_DIRS:PATH']), cmake_vars['INF_ENGINE_LIB_DIRS:PATH']
         cmake_vars['INF_ENGINE_INCLUDE_DIRS:PATH'] = str(builderDLDT.sysrootdir / 'deployment_tools/inference_engine/include')
@@ -464,8 +466,8 @@ class Builder:
 def main():
 
     dldt_src_url = 'https://github.com/openvinotoolkit/openvino'
-    dldt_src_commit = '2021.3'
-    dldt_release = '2021030000'
+    dldt_src_commit = '2021.4'
+    dldt_release = None
 
     build_cache_dir_default = os.environ.get('BUILD_CACHE_DIR', '.build_cache')
     build_subst_drive = os.environ.get('BUILD_SUBST_DRIVE', None)
@@ -492,13 +494,15 @@ def main():
     parser.add_argument('--dldt_src_branch', help='DLDT checkout branch')
     parser.add_argument('--dldt_src_commit', default=dldt_src_commit, help='DLDT source commit / tag (default: %s)' % dldt_src_commit)
     parser.add_argument('--dldt_src_git_clone_extra', action='append', help='DLDT git clone extra args')
-    parser.add_argument('--dldt_release', default=dldt_release, help='DLDT release code for INF_ENGINE_RELEASE (default: %s)' % dldt_release)
+    parser.add_argument('--dldt_release', default=dldt_release, help='DLDT release code for INF_ENGINE_RELEASE, e.g 2021030000 (default: %s)' % dldt_release)
 
     parser.add_argument('--dldt_reference_dir', help='DLDT reference git repository (optional)')
     parser.add_argument('--dldt_src_dir', help='DLDT custom source repository (skip git checkout and patching, use for TESTING only)')
 
     parser.add_argument('--dldt_config', help='Specify DLDT build configuration (defaults to evaluate from DLDT commit/branch)')
 
+    parser.add_argument('--override_patch_hashsum', default='', help='(script debug mode)')
+
     args = parser.parse_args()
 
     log.basicConfig(

samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp

@@ -89,7 +89,7 @@ void MatchingMethod( int, void* )
 
   //! [create_result_matrix]
   /// Create the result matrix
-  int result_cols =  img.cols - templ.cols + 1;
+  int result_cols = img.cols - templ.cols + 1;
   int result_rows = img.rows - templ.rows + 1;
 
   result.create( result_rows, result_cols, CV_32FC1 );

samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp

@@ -72,18 +72,18 @@ void Hist_and_Backproj(int, void* )
     //! [initialize]
     int histSize = MAX( bins, 2 );
     float hue_range[] = { 0, 180 };
-    const float* ranges = { hue_range };
+    const float* ranges[] = { hue_range };
     //! [initialize]
 
     //! [Get the Histogram and normalize it]
     Mat hist;
-    calcHist( &hue, 1, 0, Mat(), hist, 1, &histSize, &ranges, true, false );
+    calcHist( &hue, 1, 0, Mat(), hist, 1, &histSize, ranges, true, false );
     normalize( hist, hist, 0, 255, NORM_MINMAX, -1, Mat() );
     //! [Get the Histogram and normalize it]
 
     //! [Get Backprojection]
     Mat backproj;
-    calcBackProject( &hue, 1, 0, hist, backproj, &ranges, 1, true );
+    calcBackProject( &hue, 1, 0, hist, backproj, ranges, 1, true );
     //! [Get Backprojection]
 
     //! [Draw the backproj]

samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp

@@ -37,7 +37,7 @@ int main(int argc, char** argv)
 
     //! [Set the ranges ( for B,G,R) )]
     float range[] = { 0, 256 }; //the upper boundary is exclusive
-    const float* histRange = { range };
+    const float* histRange[] = { range };
     //! [Set the ranges ( for B,G,R) )]
 
     //! [Set histogram param]
@@ -46,9 +46,9 @@ int main(int argc, char** argv)
 
     //! [Compute the histograms]
     Mat b_hist, g_hist, r_hist;
-    calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );
-    calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate );
-    calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate );
+    calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, histRange, uniform, accumulate );
+    calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, histRange, uniform, accumulate );
+    calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, histRange, uniform, accumulate );
     //! [Compute the histograms]
 
     //! [Draw the histograms for B, G and R]

samples/python/camera_calibration_show_extrinsics.py

@@ -188,7 +188,7 @@ def main():
 
     fig = plt.figure()
     ax = fig.gca(projection='3d')
-    ax.set_aspect("equal")
+    ax.set_aspect("auto")
 
     cam_width = args.cam_width
     cam_height = args.cam_height

samples/python/gaussian_mix.py

@@ -32,7 +32,7 @@ def draw_gaussain(img, mean, cov, color):
     w, u, _vt = cv.SVDecomp(cov)
     ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi)
     s1, s2 = np.sqrt(w)*3.0
-    cv.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv.LINE_AA)
+    cv.ellipse(img, (int(x), int(y)), (int(s1), int(s2)), ang, 0, 360, color, 1, cv.LINE_AA)
 
 
 def main():

samples/python/hist.py

@@ -48,7 +48,7 @@ def hist_lines(im):
     cv.normalize(hist_item,hist_item,0,255,cv.NORM_MINMAX)
     hist=np.int32(np.around(hist_item))
     for x,y in enumerate(hist):
-        cv.line(h,(x,0),(x,y),(255,255,255))
+        cv.line(h,(x,0),(x,y[0]),(255,255,255))
     y = np.flipud(h)
     return y
 

samples/python/lk_homography.py

@@ -77,8 +77,8 @@ class App:
 
                 for (x0, y0), (x1, y1), good in zip(self.p0[:,0], self.p1[:,0], status[:,0]):
                     if good:
-                        cv.line(vis, (x0, y0), (x1, y1), (0, 128, 0))
-                    cv.circle(vis, (x1, y1), 2, (red, green)[good], -1)
+                        cv.line(vis, (int(x0), int(y0)), (int(x1), int(y1)), (0, 128, 0))
+                    cv.circle(vis, (int(x1), int(y1)), 2, (red, green)[good], -1)
                 draw_str(vis, (20, 20), 'track count: %d' % len(self.p1))
                 if self.use_ransac:
                     draw_str(vis, (20, 40), 'RANSAC')
@@ -86,7 +86,7 @@ class App:
                 p = cv.goodFeaturesToTrack(frame_gray, **feature_params)
                 if p is not None:
                     for x, y in p[:,0]:
-                        cv.circle(vis, (x, y), 2, green, -1)
+                        cv.circle(vis, (int(x), int(y)), 2, green, -1)
                     draw_str(vis, (20, 20), 'feature count: %d' % len(p))
 
             cv.imshow('lk_homography', vis)

samples/python/lk_track.py

@@ -65,7 +65,7 @@ class App:
                     if len(tr) > self.track_len:
                         del tr[0]
                     new_tracks.append(tr)
-                    cv.circle(vis, (x, y), 2, (0, 255, 0), -1)
+                    cv.circle(vis, (int(x), int(y)), 2, (0, 255, 0), -1)
                 self.tracks = new_tracks
                 cv.polylines(vis, [np.int32(tr) for tr in self.tracks], False, (0, 255, 0))
                 draw_str(vis, (20, 20), 'track count: %d' % len(self.tracks))

samples/python/video_v4l2.py

@@ -30,7 +30,7 @@ def main():
     color = (0, 255, 0)
 
     cap = cv.VideoCapture(0)
-    cap.set(cv.CAP_PROP_AUTOFOCUS, False)  # Known bug: https://github.com/opencv/opencv/pull/5474
+    cap.set(cv.CAP_PROP_AUTOFOCUS, 0)  # Known bug: https://github.com/opencv/opencv/pull/5474
 
     cv.namedWindow("Video")
 
@@ -67,7 +67,7 @@ def main():
             break
         elif k == ord('g'):
             convert_rgb = not convert_rgb
-            cap.set(cv.CAP_PROP_CONVERT_RGB, convert_rgb)
+            cap.set(cv.CAP_PROP_CONVERT_RGB, 1 if convert_rgb else 0)
 
     print('Done')