Made some deep learning layers params are public (#1134)

Author: dkurt

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

@@ -329,6 +329,8 @@ namespace dnn
     class CV_EXPORTS ReLULayer : public Layer
     {
     public:
+        float negativeSlope;
+
         static Ptr<ReLULayer> create(const LayerParams &params);
     };
 
@@ -365,6 +367,8 @@ namespace dnn
     class CV_EXPORTS PowerLayer : public Layer
     {
     public:
+        float power, scale, shift;
+
         static Ptr<PowerLayer> create(const LayerParams &params);
     };
 
@@ -395,18 +399,27 @@ namespace dnn
     class CV_EXPORTS BatchNormLayer : public Layer
     {
     public:
+        bool hasWeights, hasBias;
+        float epsilon;
+
         static Ptr<BatchNormLayer> create(const LayerParams &params);
     };
 
     class CV_EXPORTS MaxUnpoolLayer : public Layer
     {
     public:
+        Size poolKernel;
+        Size poolPad;
+        Size poolStride;
+
         static Ptr<MaxUnpoolLayer> create(const LayerParams &params);
     };
 
     class CV_EXPORTS ScaleLayer : public Layer
     {
     public:
+        bool hasBias;
+
         static Ptr<ScaleLayer> create(const LayerParams& params);
     };
 

modules/dnn/src/layers/batch_norm_layer.cpp

@@ -91,9 +91,6 @@ class BatchNormLayerImpl : public BatchNormLayer
         }
         return flops;
     }
-
-    bool hasWeights, hasBias;
-    float epsilon;
 };
 
 Ptr<BatchNormLayer> BatchNormLayer::create(const LayerParams& params)

modules/dnn/src/layers/blank_layer.cpp

@@ -47,7 +47,10 @@ namespace dnn
 class BlankLayerImpl : public BlankLayer
 {
 public:
-    BlankLayerImpl(const LayerParams&) {}
+    BlankLayerImpl(const LayerParams& params)
+    {
+        setParamsFrom(params);
+    }
 
     bool getMemoryShapes(const std::vector<MatShape> &inputs,
                          const int requiredOutputs,

modules/dnn/src/layers/elementwise_layers.cpp

@@ -261,6 +261,7 @@ Ptr<ReLULayer> ReLULayer::create(const LayerParams& params)
     float negativeSlope = params.get<float>("negative_slope", 0.f);
     Ptr<ReLULayer> l(new ElementWiseLayer<ReLUFunctor>(true, ReLUFunctor(negativeSlope)));
     l->setParamsFrom(params);
+    l->negativeSlope = negativeSlope;
 
     return l;
 }
@@ -306,6 +307,9 @@ Ptr<PowerLayer> PowerLayer::create(const LayerParams& params)
                       (PowerLayer*)(new ElementWiseLayer<PowerFunctor1>(false, PowerFunctor1(scale, shift))) :
                       (PowerLayer*)(new ElementWiseLayer<PowerFunctor>(true, PowerFunctor(power, scale, shift))));
     l->setParamsFrom(params);
+    l->power = power;
+    l->scale = scale;
+    l->shift = shift;
 
     return l;
 }

modules/dnn/src/layers/max_unpooling_layer.cpp

@@ -81,10 +81,6 @@ class MaxUnpoolLayerImpl : public MaxUnpoolLayer
             }
         }
     }
-
-    Size poolKernel;
-    Size poolPad;
-    Size poolStride;
 };
 
 Ptr<MaxUnpoolLayer> MaxUnpoolLayer::create(const LayerParams& params)

modules/dnn/src/layers/scale_layer.cpp

@@ -67,8 +67,6 @@ class ScaleLayerImpl : public ScaleLayer
         }
         return flops;
     }
-
-    bool hasBias;
 };