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

3rdparty/ittnotify/src/ittnotify/ittnotify_config.h

@@ -196,6 +196,10 @@
 #  define ITT_ARCH_PPC64  5
 #endif /* ITT_ARCH_PPC64 */
 
+#ifndef ITT_ARCH_AARCH64  /* 64-bit ARM */
+#  define ITT_ARCH_AARCH64  6
+#endif /* ITT_ARCH_AARCH64 */
+
 #ifndef ITT_ARCH
 #  if defined _M_IX86 || defined __i386__
 #    define ITT_ARCH ITT_ARCH_IA32
@@ -205,6 +209,8 @@
 #    define ITT_ARCH ITT_ARCH_IA64
 #  elif defined _M_ARM || defined __arm__
 #    define ITT_ARCH ITT_ARCH_ARM
+#  elif defined __aarch64__
+#    define ITT_ARCH ITT_ARCH_AARCH64
 #  elif defined __powerpc64__
 #    define ITT_ARCH ITT_ARCH_PPC64
 #  endif
@@ -359,7 +365,7 @@ ITT_INLINE long __TBB_machine_fetchadd4(volatile void* ptr, long addend)
                           : "memory");
     return result;
 }
-#elif ITT_ARCH==ITT_ARCH_ARM || ITT_ARCH==ITT_ARCH_PPC64
+#elif ITT_ARCH==ITT_ARCH_ARM || ITT_ARCH==ITT_ARCH_AARCH64 || ITT_ARCH==ITT_ARCH_PPC64
 #define __TBB_machine_fetchadd4(addr, val) __sync_fetch_and_add(addr, val)
 #endif /* ITT_ARCH==ITT_ARCH_IA64 */
 #ifndef ITT_SIMPLE_INIT

CMakeLists.txt

@@ -221,7 +221,10 @@ OCV_OPTION(BUILD_OPENEXR            "Build openexr from source"          (((WIN3
 OCV_OPTION(BUILD_WEBP               "Build WebP from source"             (((WIN32 OR ANDROID OR APPLE) AND NOT WINRT) OR OPENCV_FORCE_3RDPARTY_BUILD) )
 OCV_OPTION(BUILD_TBB                "Download and build TBB from source" (ANDROID OR OPENCV_FORCE_3RDPARTY_BUILD) )
 OCV_OPTION(BUILD_IPP_IW             "Build IPP IW from source"           (NOT MINGW OR OPENCV_FORCE_3RDPARTY_BUILD) IF (X86_64 OR X86) AND NOT WINRT )
-OCV_OPTION(BUILD_ITT                "Build Intel ITT from source"        (NOT MINGW OR OPENCV_FORCE_3RDPARTY_BUILD) IF (X86_64 OR X86) AND NOT WINRT AND NOT APPLE_FRAMEWORK )
+OCV_OPTION(BUILD_ITT                "Build Intel ITT from source"
+    (NOT MINGW OR OPENCV_FORCE_3RDPARTY_BUILD)
+    IF (X86_64 OR X86 OR ARM OR AARCH64 OR PPC64 OR PPC64LE) AND NOT WINRT AND NOT APPLE_FRAMEWORK
+)
 
 # Optional 3rd party components
 # ===================================================

modules/calib3d/src/undistort.avx2.cpp

@@ -124,7 +124,7 @@ int initUndistortRectifyMapLine_AVX(float* m1f, float* m2f, short* m1, ushort* m
             _mm256_mul_pd(__matTilt_20, __xd), _mm256_mul_pd(__matTilt_21, __yd)), __matTilt_22);
 #endif
         __m256d __invProj = _mm256_blendv_pd(
-            __one, _mm256_div_pd(__one, __vecTilt2),
+            _mm256_div_pd(__one, __vecTilt2), __one,
             _mm256_cmp_pd(__vecTilt2, _mm256_setzero_pd(), _CMP_EQ_OQ));
 
 #if CV_FMA3

modules/calib3d/test/test_undistort.cpp

@@ -1469,4 +1469,34 @@ TEST(Calib3d_UndistortPoints, outputShape)
     }
 }
 
+TEST(Calib3d_initUndistortRectifyMap, regression_14467)
+{
+    Size size_w_h(512 + 3, 512);
+    Matx33f k(
+        6200, 0, size_w_h.width / 2.0f,
+        0, 6200, size_w_h.height / 2.0f,
+        0, 0, 1
+    );
+
+    Mat mesh_uv(size_w_h, CV_32FC2);
+    for (int i = 0; i < size_w_h.height; i++)
+    {
+        for (int j = 0; j < size_w_h.width; j++)
+        {
+            mesh_uv.at<Vec2f>(i, j) = Vec2f((float)j, (float)i);
+        }
+    }
+
+    Matx<double, 1, 14> d(
+        0, 0, 0, 0, 0,
+        0, 0, 0, 0, 0, 0, 0,
+        0.09, 0.0
+    );
+    Mat mapxy, dst;
+    initUndistortRectifyMap(k, d, noArray(), k, size_w_h, CV_32FC2, mapxy, noArray());
+    undistortPoints(mapxy.reshape(2, (int)mapxy.total()), dst, k, d, noArray(), k);
+    dst = dst.reshape(2, mapxy.rows);
+    EXPECT_LE(cvtest::norm(dst, mesh_uv, NORM_INF), 1e-3);
+}
+
 }} // namespace

modules/dnn/src/layers/max_unpooling_layer.cpp

@@ -43,12 +43,18 @@ public:
                          std::vector<MatShape> &outputs,
                          std::vector<MatShape> &internals) const CV_OVERRIDE
     {
-        CV_Assert(inputs.size() == 2);
+        CV_Assert(inputs.size() == 2 || inputs.size() == 3);
         CV_Assert(total(inputs[0]) == total(inputs[1]));
 
-        MatShape outShape = inputs[0];
+        MatShape outShape;
+        if (inputs.size() == 2)
+        {
+            outShape = inputs[0];
             outShape[2] = (outShape[2] - 1) * poolStride.height + poolKernel.height - 2 * poolPad.height;
             outShape[3] = (outShape[3] - 1) * poolStride.width + poolKernel.width - 2 * poolPad.width;
+        }
+        else
+            outShape = inputs[2];
 
         outputs.clear();
         outputs.push_back(outShape);
@@ -71,7 +77,7 @@ public:
         inputs_arr.getMatVector(inputs);
         outputs_arr.getMatVector(outputs);
 
-        CV_Assert(inputs.size() == 2);
+        CV_Assert(inputs.size() == 2 || inputs.size() == 3);
         Mat& input = inputs[0];
         Mat& indices = inputs[1];
 

modules/dnn/src/onnx/onnx_importer.cpp

@@ -530,6 +530,13 @@ void ONNXImporter::populateNet(Net dstNet)
                 layerParams.type = "Power";
             }
         }
+        else if (layer_type == "Clip")
+        {
+            layerParams.type = "ReLU6";
+            replaceLayerParam(layerParams, "min", "min_value");
+            replaceLayerParam(layerParams, "max", "max_value");
+
+        }
         else if (layer_type == "LeakyRelu")
         {
             layerParams.type = "ReLU";

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -1370,6 +1370,24 @@ void TFImporter::populateNet(Net dstNet)
 
             connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, layer.input_size());
         }
+        else if (type == "MaxPoolGrad")
+        {
+            CV_Assert(layer.input_size() == 3);
+
+            layerParams.set("pool_k_h", 0);
+            layerParams.set("pool_k_w", 0);
+            layerParams.set("pool_stride_h", 0);
+            layerParams.set("pool_stride_w", 0);
+            layerParams.set("pool_pad_h", 0);
+            layerParams.set("pool_pad_w", 0);
+
+            int id = dstNet.addLayer(name, "MaxUnpool", layerParams);
+            layer_id[name] = id;
+
+            connect(layer_id, dstNet, parsePin(layer.input(2)), id, 0);
+            connect(layer_id, dstNet, parsePin(layer.input(1) + ":1"), id, 1);
+            connect(layer_id, dstNet, parsePin(layer.input(0)), id, 2);
+        }
         else if (type == "Placeholder")
         {
             if (!hasLayerAttr(layer, "dtype") ||

modules/dnn/test/test_caffe_importer.cpp

@@ -205,7 +205,7 @@ TEST(Reproducibility_FCN, Accuracy)
     Net net;
     {
         const string proto = findDataFile("dnn/fcn8s-heavy-pascal.prototxt");
-        const string model = findDataFile("dnn/fcn8s-heavy-pascal.caffemodel");
+        const string model = findDataFile("dnn/fcn8s-heavy-pascal.caffemodel", false);
         net = readNetFromCaffe(proto, model);
         ASSERT_FALSE(net.empty());
     }

modules/dnn/test/test_onnx_importer.cpp

@@ -136,6 +136,11 @@ TEST_P(Test_ONNX_layers, ReLU)
     testONNXModels("ReLU");
 }
 
+TEST_P(Test_ONNX_layers, Clip)
+{
+    testONNXModels("clip", npy);
+}
+
 TEST_P(Test_ONNX_layers, MaxPooling_Sigmoid)
 {
     testONNXModels("maxpooling_sigmoid");

modules/dnn/test/test_tf_importer.cpp

@@ -218,6 +218,13 @@ TEST_P(Test_TensorFlow_layers, pooling)
     runTensorFlowNet("reduce_mean");  // an average pooling over all spatial dimensions.
 }
 
+TEST_P(Test_TensorFlow_layers, max_pool_grad)
+{
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE);
+    runTensorFlowNet("max_pool_grad");
+}
+
 // TODO: fix tests and replace to pooling
 TEST_P(Test_TensorFlow_layers, ave_pool_same)
 {

modules/ts/src/ts.cpp

@@ -968,13 +968,15 @@ static std::string findData(const std::string& relative_path, bool required, boo
                 std::string prefix = path_join(datapath, subdir);
                 std::string result_;
                 CHECK_FILE_WITH_PREFIX(prefix, result_);
-#if 1  // check for misused 'optional' mode
                 if (!required && !result_.empty())
                 {
                     std::cout << "TEST ERROR: Don't use 'optional' findData() for " << relative_path << std::endl;
+                    static bool checkOptionalFlag = cv::utils::getConfigurationParameterBool("OPENCV_TEST_CHECK_OPTIONAL_DATA", false);
+                    if (checkOptionalFlag)
+                    {
                         CV_Assert(required || result_.empty());
                     }
-#endif
+                }
                 if (!result_.empty())
                     return result_;
             }

modules/videoio/src/cap_gstreamer.cpp

@@ -85,6 +85,11 @@ static void handleMessage(GstElement * pipeline);
 
 namespace {
 
+#if defined __clang__
+# pragma clang diagnostic push
+# pragma clang diagnostic ignored "-Wunused-function"
+#endif
+
 template<typename T> static inline void GSafePtr_addref(T* ptr)
 {
     if (ptr)
@@ -109,6 +114,10 @@ template<> inline void GSafePtr_release<GstEncodingContainerProfile>(GstEncoding
 template<> inline void GSafePtr_addref<char>(char* pPtr);  // declaration only. not defined. should not be used
 template<> inline void GSafePtr_release<char>(char** pPtr) { if (pPtr) { g_free(*pPtr); *pPtr = NULL; } }
 
+#if defined __clang__
+# pragma clang diagnostic pop
+#endif
+
 template <typename T>
 class GSafePtr
 {