Merge pull request #23109 from seanm:misc-warnings

* Fixed clang -Wnewline-eof warnings
* Fixed all trivial clang -Wextra-semi and -Wc++98-compat-extra-semi warnings
* Removed trailing semi from various macros
* Fixed various -Wunused-macros warnings
* Fixed some trivial -Wdocumentation warnings
* Fixed some -Wdocumentation-deprecated-sync warnings
* Fixed incorrect indentation
* Suppressed some clang warnings in 3rd party code
* Fixed QRCodeEncoder::Params documentation.

---------

Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>

modules/dnn/include/opencv2/dnn/all_layers.hpp

@@ -588,11 +588,11 @@ CV__DNN_INLINE_NS_BEGIN
     {
     public:
         virtual void forwardSlice(const float* src, float* dst, int len,
-                                  size_t outPlaneSize, int cn0, int cn1) const {};
+                                  size_t outPlaneSize, int cn0, int cn1) const {}
         virtual void forwardSlice(const int* src, const int* lut, int* dst, int len,
-                                  size_t outPlaneSize, int cn0, int cn1) const {};
+                                  size_t outPlaneSize, int cn0, int cn1) const {}
         virtual void forwardSlice(const int8_t* src, const int8_t* lut, int8_t* dst, int len,
-                                  size_t outPlaneSize, int cn0, int cn1) const {};
+                                  size_t outPlaneSize, int cn0, int cn1) const {}
     };
 
     class CV_EXPORTS ReLULayer : public ActivationLayer

modules/dnn/src/graph_simplifier.hpp

@@ -17,7 +17,7 @@ namespace cv { namespace dnn {
 class ImportNodeWrapper
 {
 public:
-    virtual ~ImportNodeWrapper() {};
+    virtual ~ImportNodeWrapper() {}
 
     virtual int getNumInputs() const = 0;
 
@@ -33,7 +33,7 @@ public:
 class ImportGraphWrapper
 {
 public:
-    virtual ~ImportGraphWrapper() {};
+    virtual ~ImportGraphWrapper() {}
 
     virtual Ptr<ImportNodeWrapper> getNode(int idx) const = 0;
 

modules/dnn/src/layers/convolution_layer.cpp

@@ -242,8 +242,6 @@ public:
 };
 
 
-#define IS_POWER_LAYER(layer) \
-            (!layer.empty() && !layer->type.compare("Power"))
 //TODO: simultaneously convolution and bias addition for cache optimization
 class ConvolutionLayerImpl CV_FINAL : public BaseConvolutionLayerImpl
 {

modules/dnn/src/layers/elementwise_layers.cpp

@@ -2768,11 +2768,6 @@ template<>
 const char* const ReciprocalFunctor::BaseDefaultFunctor<ReciprocalFunctor>::ocl_kernel_name = "ReciprocalForward";
 
 
-#define ACTIVATION_CREATOR_FOR(_Layer, _Functor, ...) \
-Ptr<_Layer> _Layer::create() { \
-    return return Ptr<_Layer>( new ElementWiseLayer<_Functor>(_Functor()) ); }
-
-
 Ptr<ReLULayer> ReLULayer::create(const LayerParams& params)
 {
     float negativeSlope = params.get<float>("negative_slope", 0.f);

modules/dnn/src/legacy_backend.cpp

@@ -24,7 +24,7 @@ BackendNode::BackendNode(int backendId)
     : backendId(backendId)
 {}
 
-BackendNode::~BackendNode() {};
+BackendNode::~BackendNode() {}
 
 BackendWrapper::BackendWrapper(int backendId, int targetId)
     : backendId(backendId)

modules/dnn/src/model.cpp

@@ -306,9 +306,9 @@ void ClassificationModel::classify(InputArray frame, int& classId, float& conf)
 }
 
 KeypointsModel::KeypointsModel(const String& model, const String& config)
-    : Model(model, config) {};
+    : Model(model, config) {}
 
-KeypointsModel::KeypointsModel(const Net& network) : Model(network) {};
+KeypointsModel::KeypointsModel(const Net& network) : Model(network) {}
 
 std::vector<Point2f> KeypointsModel::estimate(InputArray frame, float thresh)
 {
@@ -364,9 +364,9 @@ std::vector<Point2f> KeypointsModel::estimate(InputArray frame, float thresh)
 }
 
 SegmentationModel::SegmentationModel(const String& model, const String& config)
-    : Model(model, config) {};
+    : Model(model, config) {}
 
-SegmentationModel::SegmentationModel(const Net& network) : Model(network) {};
+SegmentationModel::SegmentationModel(const Net& network) : Model(network) {}
 
 void SegmentationModel::segment(InputArray frame, OutputArray mask)
 {

modules/dnn/src/onnx/onnx_importer.cpp

@@ -1498,7 +1498,7 @@ void ONNXImporter::lstm_extractConsts(LayerParams& layerParams, const opencv_onn
             blob = Mat(blobShape, CV_32FC1, 0.);
         }
         layerParams.blobs.push_back(blob);
-};
+}
 
 void ONNXImporter::lstm_add_reshape(const std::string& input_name, const std::string& output_name, int* layerShape, size_t n)
 {
@@ -1513,7 +1513,7 @@ void ONNXImporter::lstm_add_reshape(const std::string& input_name, const std::st
     reshape_proto.add_input(input_name);
     reshape_proto.add_output(output_name);
     addLayer(reshapeLp, reshape_proto);
-};
+}
 
 std::string ONNXImporter::lstm_add_slice(int index, const std::string& input_name, int* begin, int* end, size_t n)
 {
@@ -1532,7 +1532,7 @@ std::string ONNXImporter::lstm_add_slice(int index, const std::string& input_nam
     addLayer(sliceLP, slice_proto);
 
     return slice_proto.output(0);
-};
+}
 
 std::string ONNXImporter::lstm_fix_dims(LayerParams& layerParams, const opencv_onnx::NodeProto& lstm_proto,
                                         int batch_size, int num_directions, int hidden_size, bool need_y, const std::string& y_name,
@@ -1560,7 +1560,7 @@ std::string ONNXImporter::lstm_fix_dims(LayerParams& layerParams, const opencv_o
     addLayer(permuteLP, permute_proto);
 
     return permute_proto.output(0);
-};
+}
 
 void ONNXImporter::lstm_add_transform(int num_directions, int batch_size, int hidden_size,
                                       int index, const std::string& input_name, const std::string& output_name)
@@ -1602,7 +1602,7 @@ void ONNXImporter::lstm_add_transform(int num_directions, int batch_size, int hi
         int layerShape[] = {2, batch_size, hidden_size};
         lstm_add_reshape(concat_proto.output(0), output_name, layerShape, sizeof(layerShape) / sizeof(layerShape[0]));
     }
-};
+}
 
 void ONNXImporter::parseLSTM(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto_)
 {

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -3227,7 +3227,7 @@ void TFLayerHandler::fillRegistry(const tensorflow::GraphDef& net)
         }
     }
     printMissing();
-};
+}
 
 bool TFLayerHandler::handleMissing(const tensorflow::NodeDef& layer)
 {

modules/dnn/test/test_main.cpp

@@ -4,4 +4,4 @@
     #include <hpx/hpx_main.hpp>
 #endif
 
-CV_TEST_MAIN("", initDNNTests());
+CV_TEST_MAIN("", initDNNTests())

modules/dnn/test/test_onnx_conformance.cpp

@@ -1257,4 +1257,4 @@ INSTANTIATE_TEST_CASE_P(/**/, Test_ONNX_conformance,
     printOnnxConfParams
 );
 
-};
+}