Fixed some warnings

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

@@ -53,7 +53,7 @@ public:
 
     bool has(const String &name)
     {
-        return dict.count(name);
+        return dict.count(name) != 0;
     }
 
     DictValue *ptr(const String &name)
@@ -125,7 +125,7 @@ inline double DictValue::get<double>() const
     if (type == cv::Param::REAL)
         return d;
     else if (type == cv::Param::INT)
-        return i;
+        return (double)i;
     else
     {
         CV_Assert(type == cv::Param::REAL || type == cv::Param::INT);
@@ -156,7 +156,7 @@ inline bool DictValue::get<bool>() const
     }
     else if (type == cv::Param::INT)
     {
-        return i;
+        return i != 0;
     }
     else
     {

modules/dnn/src/caffe/util/io.hpp

@@ -2,7 +2,7 @@
 #define CAFFE_UTIL_IO_H_
 
 //instead of GLOG
-#include "glog_emulator.hpp"
+#include "../glog_emulator.hpp"
 
 //#include <unistd.h>
 #include <string>

modules/dnn/src/caffe_importer.cpp

@@ -156,12 +156,12 @@ namespace
             }
 
             dstBlob.create(shape.size(), shape, CV_32F);
-            CV_Assert(protoBlob.data_size() == dstBlob.getMatRef().total());
+            CV_Assert(protoBlob.data_size() == (int)dstBlob.getMatRef().total());
 
             CV_DbgAssert(protoBlob.GetDescriptor()->FindFieldByLowercaseName("data")->cpp_type() == FieldDescriptor::CPPTYPE_FLOAT);
             float *dstData = dstBlob.getMatRef().ptr<float>();
 
-            for (size_t i = 0; i < protoBlob.data_size(); i++)
+            for (int i = 0; i < protoBlob.data_size(); i++)
                 dstData[i] = protoBlob.data(i);
         }
 
@@ -247,7 +247,7 @@ Ptr<Importer> cv::dnn::createCaffeImporter(const String &prototxt, const String
 
 #else //HAVE_PROTOBUF
 
-Ptr<Importer> cv::dnn::createCaffeImporter(const String &prototxt, const String &caffeModel)
+Ptr<Importer> cv::dnn::createCaffeImporter(const String&, const String&)
 {
     CV_Error(cv::Error::StsNotImplemented, "libprotobuf required to import data from Caffe models");
     return Ptr<Importer>();

modules/dnn/src/layers/blank_layer.cpp

@@ -9,7 +9,7 @@ namespace dnn
     {
     public:
 
-        BlankLayer(LayerParams &params)
+        BlankLayer(LayerParams&)
         {
 
         }

modules/dnn/src/layers/elementwise_layers.cpp

@@ -59,7 +59,7 @@ namespace dnn
 
     struct TanHFunctor
     {
-        TanHFunctor(LayerParams &params) {}
+        TanHFunctor(LayerParams&) {}
 
         inline float operator()(float x)
         {

modules/dnn/src/layers/fully_connected_layer.cpp

@@ -12,7 +12,7 @@ namespace dnn
         int numOutputs;
 
         int inC, inH, inW;
-        size_t inSize;
+        int inSize;
 
     public:
         FullyConnectedLayer(LayerParams &params);

modules/dnn/src/layers/layers_common.cpp

@@ -41,7 +41,7 @@ void getKernelParams(LayerParams &params, int &kernelH, int &kernelW, int &padH,
         strideH = strideW = params.get<int>("stride", 1);
     }
 
-    CV_Assert(kernelH > 0 && kernelW > 0 && padH >= 0 && padW >= 0 && strideH > 0 & strideW > 0);
+    CV_Assert(kernelH > 0 && kernelW > 0 && padH >= 0 && padW >= 0 && strideH > 0 && strideW > 0);
 }
 
 }

modules/dnn/src/layers/lrn_layer.cpp

@@ -129,7 +129,7 @@ namespace dnn
                 cv::pow(dst, beta, dst);
                 cv::divide(src, dst, dst);
 
-                CV_DbgAssert(dataDst0 == dst.data);
+                CV_Assert(dataDst0 == dst.data); //debug
             }
         }
     }

modules/dnn/src/layers/softmax_layer.cpp

@@ -50,7 +50,6 @@ namespace dnn
         float *dstPtr = dst.ptr<float>();
         float *bufPtr = maxAggregator.ptr<float>();
 
-        size_t totalSize = src.total();
         size_t outerSize = src.total(0, axis);
         size_t channels = src.size(axis);
         size_t innerSize = src.total(axis + 1, -1);