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modify samples for feature storing option

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This commit is contained in:
Wangyida
2015-10-07 20:22:00 +08:00
parent a81322a8bd
commit dd50d5bc93
12 changed files with 431 additions and 235 deletions
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19
modules/cnn_3dobj/include/opencv2/cnn_3dobj.hpp
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@@ -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.
@@ -274,7 +273,7 @@ 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.
@@ -282,7 +281,7 @@ namespace cnn_3dobj
@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);
};
//! @}
}