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add classifier Class and a demo on classification on 3D data

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This commit is contained in:
Wangyida
2015-07-26 23:42:45 +08:00
parent d6cb8889b4
commit 6f38d89160
17 changed files with 481 additions and 134 deletions
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40
modules/cnn_3dobj/include/opencv2/cnn_3dobj.hpp
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@@ -60,10 +60,6 @@ the use of this software, even if advised of the possibility of such damage.
#include <glog/logging.h>
#include <google/protobuf/text_format.h>
#include <leveldb/db.h>
//#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/viz/vizcore.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>
#define CPU_ONLY
#include <caffe/blob.hpp>
#include <caffe/common.hpp>
@@ -71,6 +67,10 @@ the use of this software, even if advised of the possibility of such damage.
#include <caffe/proto/caffe.pb.h>
#include <caffe/util/io.hpp>
#include <caffe/vision_layers.hpp>
#include "opencv2/viz/vizcore.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/imgproc.hpp"
using std::string;
using caffe::Blob;
using caffe::Caffe;
@@ -161,6 +161,38 @@ class CV_EXPORTS_W DataTrans
/** @brief Extract feature into a binary file and vector<cv::Mat> for classification, the model proto and network proto are needed, All images in the file root will be used for feature extraction.
*/
};
class CV_EXPORTS_W Classification
{
private:
caffe::shared_ptr<caffe::Net<float> > net_;
cv::Size input_geometry_;
int num_channels_;
cv::Mat mean_;
std::vector<string> labels_;
void SetMean(const string& mean_file);
/** @brief Load the mean file in binaryproto format.
*/
void WrapInputLayer(std::vector<cv::Mat>* input_channels);
/** @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. The last preprocessing operation will write the separate channels directly to the input layer.
*/
void Preprocess(const cv::Mat& img, std::vector<cv::Mat>* input_channels, bool mean_subtract);
/** @brief Convert the input image to the input image format of the network.
*/
public:
Classification(const string& model_file, const string& trained_file, const string& mean_file, const string& label_file);
/** @brief Initiate a classification structure.
*/
std::vector<std::pair<string, float> > Classify(const std::vector<cv::Mat>& reference, const cv::Mat& img, int N = 4, bool mean_substract = false);
/** @brief Make a classification.
*/
cv::Mat feature_extract(const cv::Mat& img, bool mean_subtract);
/** @brief Extract a single featrue of one image.
*/
std::vector<int> Argmax(const std::vector<float>& v, int N);
/** @brief Find the N largest number.
*/
};
//! @}
}}