Swapping of stride and pad params inside layers initializers

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

@@ -216,16 +216,14 @@ namespace dnn
     {
     public:
 
-        static Ptr<BaseConvolutionLayer> create();
-        static Ptr<BaseConvolutionLayer> create(Size kernel = Size(3, 3), Size pad = Size(0, 0), Size stride = Size(1, 1));
+        static Ptr<BaseConvolutionLayer> create(Size kernel = Size(3, 3), Size stride = Size(1, 1), Size pad = Size(0, 0));
     };
 
     class CV_EXPORTS_W DeconvolutionLayer : public BaseConvolutionLayer
     {
     public:
 
-        static Ptr<BaseConvolutionLayer> create();
-        static Ptr<BaseConvolutionLayer> create(Size kernel = Size(3, 3), Size pad = Size(0, 0), Size stride = Size(1, 1));
+        static Ptr<BaseConvolutionLayer> create(Size kernel = Size(3, 3), Size stride = Size(1, 1), Size pad = Size(0, 0));
     };
 
     class CV_EXPORTS_W LRNLayer : public Layer
@@ -259,7 +257,7 @@ namespace dnn
         int type;
         Size kernel, stride, pad;
 
-        static Ptr<PoolingLayer> create(int type = MAX, Size kernel = Size(2, 2), Size pad = Size(0, 0), Size stride = Size(1, 1));
+        static Ptr<PoolingLayer> create(int type = MAX, Size kernel = Size(2, 2), Size stride = Size(1, 1), Size pad = Size(0, 0));
     };
 
 //! @}

modules/dnn/src/layers/convolution_layer.cpp

@@ -315,12 +315,7 @@ void DeConvolutionLayerImpl::col2im(const UMat &colMat, UMat &dstImg)
 
 //Initializers
 
-Ptr<BaseConvolutionLayer> ConvolutionLayer::create()
-{
-    return Ptr<BaseConvolutionLayer>(new ConvolutionLayerImpl());
-}
-
-Ptr<BaseConvolutionLayer> ConvolutionLayer::create(Size kernel, Size pad, Size stride)
+Ptr<BaseConvolutionLayer> ConvolutionLayer::create(Size kernel, Size stride, Size pad)
 {
     ConvolutionLayerImpl *l = new ConvolutionLayerImpl();
     l->kernel = kernel;
@@ -329,12 +324,7 @@ Ptr<BaseConvolutionLayer> ConvolutionLayer::create(Size kernel, Size pad, Size s
     return Ptr<BaseConvolutionLayer>(l);
 }
 
-Ptr<BaseConvolutionLayer> DeconvolutionLayer::create()
-{
-    return Ptr<BaseConvolutionLayer>(new DeConvolutionLayerImpl());
-}
-
-Ptr<BaseConvolutionLayer> DeconvolutionLayer::create(Size kernel, Size pad, Size stride)
+Ptr<BaseConvolutionLayer> DeconvolutionLayer::create(Size kernel, Size stride, Size pad)
 {
     DeConvolutionLayerImpl *l = new DeConvolutionLayerImpl();
     l->kernel = kernel;

modules/dnn/src/layers/pooling_layer.cpp

@@ -60,7 +60,7 @@ PoolingLayerImpl::PoolingLayerImpl()
 
 }
 
-PoolingLayerImpl::PoolingLayerImpl(int type_, Size kernel_, Size pad_, Size stride_)
+PoolingLayerImpl::PoolingLayerImpl(int type_, Size kernel_, Size stride_, Size pad_)
 {
     type = type_;
     kernel = kernel_;
@@ -261,9 +261,9 @@ void PoolingLayerImpl::computeOutputShape(Size inpSz)
     }
 }
 
-Ptr<PoolingLayer> PoolingLayer::create(int type, Size kernel, Size pad, Size stride)
+Ptr<PoolingLayer> PoolingLayer::create(int type, Size kernel, Size stride, Size pad)
 {
-    return Ptr<PoolingLayer>(new PoolingLayerImpl(type, kernel, pad, stride));
+    return Ptr<PoolingLayer>(new PoolingLayerImpl(type, kernel, stride, pad));
 }
 
 Ptr<Layer> createPoolingLayerFromCaffe(LayerParams &params)
@@ -290,7 +290,7 @@ Ptr<Layer> createPoolingLayerFromCaffe(LayerParams &params)
 
     getCaffeConvParams(params, kernel, pad, stride);
 
-    return Ptr<Layer>(new PoolingLayerImpl(type, kernel, pad, stride));
+    return Ptr<Layer>(new PoolingLayerImpl(type, kernel, stride, pad));
 }
 
 }

modules/dnn/src/layers/pooling_layer.hpp

@@ -68,7 +68,7 @@ namespace dnn
     public:
 
         PoolingLayerImpl();
-        PoolingLayerImpl(int type, Size kernel, Size pad, Size stride);
+        PoolingLayerImpl(int type, Size kernel, Size stride, Size pad);
 
         void allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
         void forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);