modify samples for feature storing option

Author: wangyida

modules/cnn_3dobj/include/opencv2/cnn_3dobj.hpp

@@ -72,7 +72,6 @@ the use of this software, even if advised of the possibility of such damage.
 #include "opencv2/highgui.hpp"
 #include "opencv2/highgui/highgui_c.h"
 #include "opencv2/imgproc.hpp"
-using std::string;
 using caffe::Blob;
 using caffe::Caffe;
 using caffe::Datum;
@@ -185,7 +184,7 @@ namespace cnn_3dobj
 
         /** @brief Suit the position of bytes in 4 byte data structure for particular system.
          */
-        CV_WRAP static uint32_t swapEndian(uint32_t val);
+        CV_WRAP static int swapEndian(int val);
 
         /** @brief Create header in binary files collecting the image data and label.
         @param num_item Number of items.
@@ -206,7 +205,7 @@ namespace cnn_3dobj
         @param z Pose label of Z.
         @param isrgb Option for choice of using RGB images or not.
          */
-        CV_WRAP static void writeBinaryfile(string filenameImg, const char* binaryPath, const char* headerPath, int num_item, int label_class, int x, int y, int z, int isrgb);
+        CV_WRAP static void writeBinaryfile(String filenameImg, const char* binaryPath, const char* headerPath, int num_item, int label_class, int x, int y, int z, int isrgb);
     };
 
 /** @brief Caffe based 3D images descriptor.
@@ -223,13 +222,13 @@ namespace cnn_3dobj
         bool net_set;
         int net_ready;
         cv::Mat mean_;
-        string deviceType;
+        String deviceType;
         int deviceId;
 
         /** @brief Load the mean file in binaryproto format if it is needed.
         @param mean_file Path of mean file which stores the mean of training images, it is usually generated by Caffe tool.
          */
-        void setMean(const string& mean_file);
+        void setMean(const String& mean_file);
 
         /** @brief Wrap the input layer of the network in separate cv::Mat objects(one per channel).
          This way we save one memcpy operation and we don't need to rely on cudaMemcpy2D.
@@ -246,11 +245,11 @@ namespace cnn_3dobj
         @param device_type CPU or GPU.
         @param device_id ID of GPU.
          */
-        descriptorExtractor(const string& device_type, int device_id = 0);
+        descriptorExtractor(const String& device_type, int device_id = 0);
 
         /** @brief Get device type information for feature extraction.
          */
-        string getDeviceType();
+        String getDeviceType();
 
         /** @brief Get device ID information for feature extraction.
          */
@@ -260,7 +259,7 @@ namespace cnn_3dobj
          Useful to change device without the need to reload the net.
         @param device_type CPU or GPU.
          */
-        void setDeviceType(const string& device_type);
+        void setDeviceType(const String& device_type);
 
         /** @brief Set device ID information for feature extraction.
          Useful to change device without the need to reload the net. Only used for GPU.
@@ -274,15 +273,15 @@ namespace cnn_3dobj
         @param trained_file Path of prototxt which defining the structure of CNN.
         @param mean_file Path of mean file(option).
          */
-        void loadNet(const string& model_file, const string& trained_file, const string& mean_file = "");
+        void loadNet(const String& model_file, const String& trained_file, const String& mean_file = "");
 
         /** @brief Extract features from a single image or from a vector of images.
          If loadNet was not called before, this method invocation will fail.
         @param inputimg Input images.
         @param feature Output features.
         @param feature_blob Layer which the feature is extracted from.
          */
-        void extract(InputArrayOfArrays inputimg, OutputArray feature, std::string feature_blob);
+        void extract(InputArrayOfArrays inputimg, OutputArray feature, String feature_blob);
     };
     //! @}
 }