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

3rdparty/libpng/CMakeLists.txt

@@ -77,9 +77,11 @@ endif(MSVC)
 add_library(${PNG_LIBRARY} STATIC ${OPENCV_3RDPARTY_EXCLUDE_FROM_ALL} ${lib_srcs} ${lib_hdrs})
 target_link_libraries(${PNG_LIBRARY} ${ZLIB_LIBRARIES})
 
-ocv_warnings_disable(CMAKE_C_FLAGS -Wundef -Wcast-align -Wimplicit-fallthrough -Wunused-parameter -Wsign-compare)
+ocv_warnings_disable(CMAKE_C_FLAGS -Wundef -Wcast-align -Wimplicit-fallthrough -Wunused-parameter -Wsign-compare
-ocv_warnings_disable(CMAKE_C_FLAGS -Wnull-pointer-subtraction)  # clang15
+    -Wmaybe-uninitialized
-ocv_warnings_disable(CMAKE_C_FLAGS -Wunused-but-set-variable)  # clang15
+    -Wnull-pointer-subtraction                   # clang15
+    -Wunused-but-set-variable                    # clang15
+)
 
 set_target_properties(${PNG_LIBRARY}
   PROPERTIES OUTPUT_NAME ${PNG_LIBRARY}

3rdparty/libtiff/CMakeLists.txt

@@ -452,9 +452,10 @@ ocv_warnings_disable(CMAKE_C_FLAGS -Wno-unused-but-set-variable -Wmissing-protot
                                    -Wcast-align -Wshadow -Wno-maybe-uninitialized -Wno-pointer-to-int-cast -Wno-int-to-pointer-cast
                                    -Wmisleading-indentation
                                    -Wimplicit-fallthrough
+                                   -Wunused-parameter  # clang
+                                   -Warray-parameter
+                                   -Wstrict-prototypes  # clang15
 )
-ocv_warnings_disable(CMAKE_C_FLAGS -Wunused-parameter) # clang
-ocv_warnings_disable(CMAKE_C_FLAGS -Wstrict-prototypes) # clang15
 ocv_warnings_disable(CMAKE_CXX_FLAGS -Wmissing-declarations -Wunused-parameter -Wmissing-prototypes
     -Wundef  # tiffiop.h: #if __clang_major__ >= 4
 )

apps/traincascade/cascadeclassifier.cpp

@@ -252,7 +252,7 @@ bool CvCascadeClassifier::train( const string _cascadeDirName,
             fs << "}";
         }
         // save current stage
-        char buf[10];
+        char buf[32];
         sprintf(buf, "%s%d", "stage", i );
         string stageFilename = dirName + buf + ".xml";
         FileStorage fs( stageFilename, FileStorage::WRITE );

modules/dnn/src/onnx/onnx_importer.cpp

@@ -197,8 +197,18 @@ private:
     void parseOperatorSet();
 
     const std::string str_domain_ai_onnx = "ai.onnx";
+
+
+    bool useLegacyNames;
+    bool getParamUseLegacyNames()
+    {
+        bool param = utils::getConfigurationParameterBool("OPENCV_DNN_ONNX_USE_LEGACY_NAMES", false);
+        return param;
+    }
+    const std::string extractNodeName(const opencv_onnx::NodeProto& node_proto);
 };
 
+
 class ONNXLayerHandler : public detail::LayerHandler
 {
 public:
@@ -233,6 +243,7 @@ ONNXImporter::ONNXImporter(Net& net, const char *onnxFile)
     : layerHandler(DNN_DIAGNOSTICS_RUN ? new ONNXLayerHandler(this) : nullptr)
     , dstNet(net)
     , onnx_opset(0)
+    , useLegacyNames(getParamUseLegacyNames())
 {
     hasDynamicShapes = false;
     CV_Assert(onnxFile);
@@ -256,6 +267,7 @@ ONNXImporter::ONNXImporter(Net& net, const char* buffer, size_t sizeBuffer)
     : layerHandler(DNN_DIAGNOSTICS_RUN ? new ONNXLayerHandler(this) : nullptr)
     , dstNet(net)
     , onnx_opset(0)
+    , useLegacyNames(getParamUseLegacyNames())
 {
     hasDynamicShapes = false;
     CV_LOG_DEBUG(NULL, "DNN/ONNX: processing in-memory ONNX model (" << sizeBuffer << " bytes)");
@@ -278,6 +290,7 @@ ONNXImporter::ONNXImporter(Net& net, const char* buffer, size_t sizeBuffer)
     populateNet();
 }
 
+
 inline void replaceLayerParam(LayerParams& layerParams, const String& oldKey, const String& newKey)
 {
     if (layerParams.has(oldKey)) {
@@ -909,11 +922,14 @@ const ONNXImporter::DispatchMap& ONNXImporter::getDispatchMap(const opencv_onnx:
     return it->second;
 }
 
-const std::string& extractNodeName(const opencv_onnx::NodeProto& node_proto)
+const std::string ONNXImporter::extractNodeName(const opencv_onnx::NodeProto& node_proto)
 {
+    // We need to rework DNN outputs API, this is a workaround for #21698
     if (node_proto.has_name() && !node_proto.name().empty())
     {
-        return node_proto.name();
+        if (useLegacyNames)
+            return node_proto.name();
+        return cv::format("onnx_node!%s", node_proto.name().c_str());
     }
     for (int i = 0; i < node_proto.output_size(); ++i)
     {
@@ -923,7 +939,9 @@ const std::string& extractNodeName(const opencv_onnx::NodeProto& node_proto)
         // the second method is to use an empty string in place of an input or output name.
         if (!name.empty())
         {
-            return name;
+            if (useLegacyNames)
+                return name.c_str();
+            return cv::format("onnx_node_output_%d!%s", i, name.c_str());
         }
     }
     CV_Error(Error::StsAssert, "Couldn't deduce Node name.");

modules/dnn/test/test_int8_layers.cpp

@@ -265,14 +265,32 @@ TEST_P(Test_Int8_layers, Mish)
     testLayer("mish", "ONNX", 0.0015, 0.0025);
 }
 
-TEST_P(Test_Int8_layers, Softmax)
+TEST_P(Test_Int8_layers, Softmax_Caffe)
 {
     testLayer("layer_softmax", "Caffe", 0.0011, 0.0036);
+}
+TEST_P(Test_Int8_layers, Softmax_keras_TF)
+{
     testLayer("keras_softmax", "TensorFlow", 0.00093, 0.0027);
+}
+TEST_P(Test_Int8_layers, Softmax_slim_TF)
+{
     testLayer("slim_softmax", "TensorFlow", 0.0016, 0.0034);
+}
+TEST_P(Test_Int8_layers, Softmax_slim_v2_TF)
+{
     testLayer("slim_softmax_v2", "TensorFlow", 0.0029, 0.017);
+}
+TEST_P(Test_Int8_layers, Softmax_ONNX)
+{
     testLayer("softmax", "ONNX", 0.0016, 0.0028);
+}
+TEST_P(Test_Int8_layers, Softmax_log_ONNX)
+{
     testLayer("log_softmax", "ONNX", 0.014, 0.025);
+}
+TEST_P(Test_Int8_layers, DISABLED_Softmax_unfused_ONNX)  // FIXIT Support 'Identity' layer for outputs (#22022)
+{
     testLayer("softmax_unfused", "ONNX", 0.0009, 0.0021);
 }
 
@@ -389,7 +407,7 @@ TEST_P(Test_Int8_layers, Slice_strided_tf)
     testLayer("strided_slice", "TensorFlow", 0.008, 0.0142);
 }
 
-TEST_P(Test_Int8_layers, Slice_onnx)
+TEST_P(Test_Int8_layers, DISABLED_Slice_onnx)  // FIXIT Support 'Identity' layer for outputs (#22022)
 {
     testLayer("slice", "ONNX", 0.0046, 0.0077);
 }

modules/dnn/test/test_onnx_importer.cpp

@@ -1855,6 +1855,11 @@ TEST_P(Test_ONNX_layers, Quantized_Constant)
     testONNXModels("quantized_constant", npy, 0.002, 0.008);
 }
 
+TEST_P(Test_ONNX_layers, OutputRegistration)
+{
+    testONNXModels("output_registration", npy, 0, 0, false, true, 2);
+}
+
 INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_ONNX_layers, dnnBackendsAndTargets());
 
 class Test_ONNX_nets : public Test_ONNX_layers

modules/ts/src/ts_gtest.cpp

@@ -8718,7 +8718,7 @@ static void StackLowerThanAddress(const void* ptr, bool* result) {
 // Make sure AddressSanitizer does not tamper with the stack here.
 GTEST_ATTRIBUTE_NO_SANITIZE_ADDRESS_
 static bool StackGrowsDown() {
-  int dummy;
+  int dummy = 0;
   bool result;
   StackLowerThanAddress(&dummy, &result);
   return result;

modules/video/src/tracking/tracker_dasiamrpn.cpp

@@ -160,7 +160,7 @@ void TrackerDaSiamRPNImpl::trackerInit(Mat img)
     dnn::blobFromImage(zCrop, blob, 1.0, Size(trackState.exemplarSize, trackState.exemplarSize), Scalar(), trackState.swapRB, false, CV_32F);
     siamRPN.setInput(blob);
     Mat out1;
-    siamRPN.forward(out1, "63");
+    siamRPN.forward(out1, "onnx_node_output_0!63");
 
     siamKernelCL1.setInput(out1);
     siamKernelR1.setInput(out1);
@@ -169,8 +169,8 @@ void TrackerDaSiamRPNImpl::trackerInit(Mat img)
     Mat r1 = siamKernelR1.forward();
     std::vector<int> r1_shape = { 20, 256, 4, 4 }, cls1_shape = { 10, 256, 4, 4 };
 
-    siamRPN.setParam(siamRPN.getLayerId("65"), 0, r1.reshape(0, r1_shape));
+    siamRPN.setParam(siamRPN.getLayerId("onnx_node_output_0!65"), 0, r1.reshape(0, r1_shape));
-    siamRPN.setParam(siamRPN.getLayerId("68"), 0, cls1.reshape(0, cls1_shape));
+    siamRPN.setParam(siamRPN.getLayerId("onnx_node_output_0!68"), 0, cls1.reshape(0, cls1_shape));
 }
 
 bool TrackerDaSiamRPNImpl::update(InputArray image, Rect& boundingBox)