OpenCV學習筆記(一):使用CascadeClassifier檢測人臉
阿新 • • 發佈:2019-02-16
#include "stdafx.h" #include <opencv2/opencv.hpp> class FaceRecognition { private: cv::Mat m_mImg; char* face_cascade_name = "D:\\OpenCV\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml"; char* eyes_cascade_name = "D:\\OpenCV\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml"; cv::CascadeClassifier face_cascade; cv::CascadeClassifier eyes_cascade; public: FaceRecognition(); ~FaceRecognition(); void recognition(); void setImg(cv::Mat mat); }; FaceRecognition::FaceRecognition(){} FaceRecognition::~FaceRecognition() { delete face_cascade_name; delete eyes_cascade_name; } void FaceRecognition::setImg(cv::Mat mat) { this->m_mImg = mat; } void FaceRecognition::recognition() { //-- 1. Load the cascades if (!face_cascade.load(face_cascade_name)){ printf("--(!)Error loading face cascade\n"); return ; }; if (!eyes_cascade.load(eyes_cascade_name)){ printf("--(!)Error loading eyes cascade\n"); return ; }; std::vector<cv::Rect> faces; cv::Mat img_gray; cvtColor(m_mImg, img_gray, cv::COLOR_BGR2GRAY); cv::equalizeHist(img_gray, img_gray); //-- 2. Detect faces face_cascade.detectMultiScale(img_gray, faces, 1.1, 2, 0 | cv::CASCADE_SCALE_IMAGE, cv::Size(30, 30)); for (int i = 0; i < faces.size(); i++) { cv::Point center(faces[i].x + faces[i].width / 2, faces[i].y + faces[i].height / 2); ellipse(m_mImg, center, cv::Size(faces[i].width / 2, faces[i].height / 2), 0, 0, 360, cv::Scalar(255, 0, 255), 4, 8, 0); cv::Mat faceROI = img_gray(faces[i]); std::vector<cv::Rect> eyes; //-- In each face, detect eyes eyes_cascade.detectMultiScale(faceROI, eyes, 1.1, 2, 0 | cv::CASCADE_SCALE_IMAGE, cv::Size(30, 30)); for (size_t j = 0; j < eyes.size(); j++) { cv::Point eye_center(faces[i].x + eyes[j].x + eyes[j].width / 2, faces[i].y + eyes[j].y + eyes[j].height / 2); int radius = cvRound((eyes[j].width + eyes[j].height)*0.25); circle(m_mImg, eye_center, radius, cv::Scalar(255, 0, 0), 4, 8, 0); } } //-- 3. Show result cv::imshow("Res", m_mImg); }