Merge branch 4.x

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

@@ -291,7 +291,7 @@ CV__DNN_INLINE_NS_BEGIN
         static Ptr<BaseConvolutionLayer> create(const LayerParams& params);
         bool fusedActivation = false;
         bool fusedAdd = false;
-        bool useWinograd = false; // Flag whether to use Winograd to speed up 3x3 convolution.
+        bool useWinograd = true; // Flag whether to use Winograd to speed up 3x3 convolution.
     };
 
     class CV_EXPORTS ConvolutionLayerInt8 : public BaseConvolutionLayer
@@ -303,7 +303,7 @@ CV__DNN_INLINE_NS_BEGIN
         // quantization type flag. The perChannel default is true, that means it contains the parameters
         // of per-Channel quantization. Otherwise, that means this layer contains per-Tensor quantized parameters.
         bool per_channel;
-        bool useWinograd = true; // Flag whether to use Winograd to speed up 3x3 convolution.
+        bool useWinograd = false; // Flag whether to use Winograd to speed up 3x3 convolution.
         static Ptr<BaseConvolutionLayer> create(const LayerParams& params);
     };
 
@@ -1160,12 +1160,29 @@ CV__DNN_INLINE_NS_BEGIN
         static Ptr<GemmLayer> create(const LayerParams& params);
     };
 
+    class CV_EXPORTS MatMulLayer : public Layer {
+     public:
+        static Ptr<MatMulLayer> create(const LayerParams &params);
+    };
+
     class CV_EXPORTS ExpandLayer : public Layer
     {
     public:
         static Ptr<ExpandLayer> create(const LayerParams &params);
     };
 
+    class CV_EXPORTS InstanceNormLayer : public Layer {
+    public:
+        float epsilon;
+
+        static Ptr<InstanceNormLayer> create(const LayerParams &params);
+    };
+
+    class CV_EXPORTS AttentionLayer : public Layer {
+     public:
+        static Ptr<AttentionLayer> create(const LayerParams &params);
+    };
+
 //! @}
 //! @}
 CV__DNN_INLINE_NS_END

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

@@ -1127,7 +1127,7 @@ CV__DNN_INLINE_NS_BEGIN
         CV_WRAP Image2BlobParams();
         CV_WRAP Image2BlobParams(const Scalar& scalefactor, const Size& size = Size(), const Scalar& mean = Scalar(),
                             bool swapRB = false, int ddepth = CV_32F, DataLayout datalayout = DNN_LAYOUT_NCHW,
-                            ImagePaddingMode mode = DNN_PMODE_NULL);
+                            ImagePaddingMode mode = DNN_PMODE_NULL, Scalar borderValue = 0.0);
 
         CV_PROP_RW Scalar scalefactor; //!< scalefactor multiplier for input image values.
         CV_PROP_RW Size size;    //!< Spatial size for output image.
@@ -1136,6 +1136,21 @@ CV__DNN_INLINE_NS_BEGIN
         CV_PROP_RW int ddepth;   //!< Depth of output blob. Choose CV_32F or CV_8U.
         CV_PROP_RW DataLayout datalayout; //!< Order of output dimensions. Choose DNN_LAYOUT_NCHW or DNN_LAYOUT_NHWC.
         CV_PROP_RW ImagePaddingMode paddingmode;   //!< Image padding mode. @see ImagePaddingMode.
+        CV_PROP_RW Scalar borderValue;   //!< Value used in padding mode for padding.
+
+        /** @brief Get rectangle coordinates in original image system from rectangle in blob coordinates.
+         *  @param rBlob rect in blob coordinates.
+         *  @param size original input image size.
+         *  @returns rectangle in original image coordinates.
+         */
+        CV_WRAP Rect blobRectToImageRect(const Rect &rBlob, const Size &size);
+
+        /** @brief Get rectangle coordinates in original image system from rectangle in blob coordinates.
+         *  @param rBlob rect in blob coordinates.
+         *  @param rImg result rect in image coordinates.
+         *  @param size original input image size.
+         */
+        CV_WRAP void blobRectsToImageRects(const std::vector<Rect> &rBlob, CV_OUT std::vector<Rect>& rImg, const Size& size);
     };
 
     /** @brief Creates 4-dimensional blob from image with given params.
@@ -1373,6 +1388,9 @@ CV__DNN_INLINE_NS_BEGIN
          /// @sa Net::setPreferableTarget
          CV_WRAP Model& setPreferableTarget(dnn::Target targetId);
 
+         /// @sa Net::enableWinograd
+         CV_WRAP Model& enableWinograd(bool useWinograd);
+
          CV_DEPRECATED_EXTERNAL
          operator Net&() const { return getNetwork_(); }
 

modules/dnn/include/opencv2/dnn/version.hpp

@@ -6,7 +6,7 @@
 #define OPENCV_DNN_VERSION_HPP
 
 /// Use with major OpenCV version only.
-#define OPENCV_DNN_API_VERSION 20230620
+#define OPENCV_DNN_API_VERSION 20231225
 
 #if !defined CV_DOXYGEN && !defined CV_STATIC_ANALYSIS && !defined CV_DNN_DONT_ADD_INLINE_NS
 #define CV__DNN_INLINE_NS __CV_CAT(dnn5_v, OPENCV_DNN_API_VERSION)