openCV学习笔记（十八） —— 人脸识别 —— 程序 —— LBPH局部二值模式直方图

r囧r小猫 2021-09-27 06:46 297阅读 0赞

#include <opencv2/core.hpp>
    #include <opencv2/face.hpp>
    #include <opencv2/highgui.hpp>
    
    #include <iostream>
    #include <fstream>
    #include <sstream>
    
    using namespace std;
    using namespace cv;
    using namespace cv::face;
    
    void read_csv(string& filename, vector<Mat>& images, vector<int>& labels, char separator = ';')
    {
    	ifstream file;
    	file.open(filename.c_str(), ifstream::in);
    	if (!file)
    	{
    		printf("can't open file: %s\n", filename.c_str());
    		exit(-1);
    	}
    
    	string line, path, classlabel;
    	while (getline(file, line))
    	{
    		stringstream liness(line);
    		getline(liness, path, separator);
    		getline(liness, classlabel);
    		if (!path.empty() && !classlabel.empty())
    		{
    			images.push_back(imread(path, 0));
    			labels.push_back(atoi(classlabel.c_str()));
    		}
    	}
    }
    
    int main()
    {
    	string filename = string(".\\face_recg\\face\\at.txt");
    
    	vector<Mat> images;
    	vector<int> labels;
    
    	try
    	{
    		read_csv(filename, images, labels);
    	}
    	catch (const cv::Exception& e)
    	{
    		printf("failed opening file %s reason %s\n", filename.c_str(), e.msg.c_str());
    		exit(1);
    	}
    
    	if (images.size() <= 1)
    	{
    		printf("This demo needs at least 2 images to work. Please add more images to your data set!\n");
    		exit(1);
    	}
    
    	Mat testSample = images[images.size() - 1];
    	int testLabel = labels[labels.size() - 1];
    
    	images.pop_back();
    	labels.pop_back();
    
    	Ptr<LBPHFaceRecognizer> model = LBPHFaceRecognizer::create();
    	model->train(images, labels);
    
    	int predictLabel = model->predict(testSample);
    
    	printf("test label = %d, predict label = %d\n", testLabel, predictLabel);
    
    	//model->setThreshold(0.0);
    	//predictLabel = model->predict(testSample);
    
    	//printf("test label = %d, predict label = %d\n", testLabel, predictLabel);
    
    	//打印参数
    	int radius = model->getRadius();	//中心像素点到周围像素点的距离
    	int neibs = model->getNeighbors();	//周围像素点的个数
    	int grid_x = model->getGridX();		//将一张图片在x方向分成几块
    	int grid_y = model->getGridY();		//将一张图片在y方向分成几块
    	double threshold = model->getThreshold();	//相似度阈值
    
    	printf("radius = %d\n", radius);
    	printf("neibs = %d\n", neibs);
    	printf("grid_x = %d\n", grid_x);
    	printf("grid_y = %d\n", grid_y);
    	printf("threshold = %e\n", threshold);
    
    	vector<Mat> histograms = model->getHistograms();
    	printf("Size of the histograms: %zd\n", histograms[0].total());
    
    	waitKey(0);
    
    	return 0;
    }