#include<opencv2\opencv.hpp>
#include<opencv2\face.hpp>
using namespace cv;
using namespace face;
using namespace std;
char win_title[40] = {};
 
int main(int arc, char** argv) { 
 //namedWindow("input",CV_WINDOW_AUTOSIZE);
 
 //讀入模型需要輸入的數據，用來訓練的圖像vector<Mat>images和標簽vector<int>labels
 string filename = string("path.txt");
 ifstream file(filename);
 if (!file) { printf("could not load file"); }
 vector<Mat>images;
 vector<int>labels;
 char separator = ';';
 string line,path, classlabel;
 while (getline(file,line)) {
 stringstream lines(line);
 getline(lines, path, separator);
 getline(lines, classlabel);
 //printf("%d\n", atoi(classlabel.c_str()));
 images.push_back(imread(path, 0));
 labels.push_back(atoi(classlabel.c_str()));//atoi(ASCLL to int)將字符串轉換為整數型
 }
 int height = images[0].rows;
 int width = images[0].cols;
 printf("height:%d,width:%d\n", height, width);
 //將最后一個樣本作為測試樣本
 Mat testSample = images[images.size() - 1];
 int testLabel = labels[labels.size() - 1];
 //刪除列表末尾的元素
 images.pop_back();
 labels.pop_back();
 
 //加載，訓練，預測
 Ptr<LBPHFaceRecognizer> model = LBPHFaceRecognizer::create();
 model->train(images, labels);
 int predictedLabel = model->predict(testSample);
 printf("actual label:%d,predict label :%d\n", testLabel, predictedLabel);
 
 int radius = model->getRadius();
 int neibs = model->getNeighbors();
 int grad_x = model->getGridX();
 int grad_y = model->getGridY();
 double t = model->getThreshold();
 printf("radius:%d\n", radius);
 printf("neibs:%d\n", neibs);
 printf("grad_x:%d\n", grad_x);
 printf("grad_y:%d\n", grad_y);
 printf("threshold:%.2f\n", t);
 
 waitKey(0);
 return 0;
}