第39月第3日 opencv Haar Cascade人脸检测 1秒n帧

1.

import cv2
import sys
 
img=cv2.imread('2.jpg')
 
#加载分类器
face_haar=cv2.CascadeClassifier("data/haarcascades/haarcascade_frontalface_default.xml")
eye_haar=cv2.CascadeClassifier("data/haarcascades/haarcascade_eye.xml")
 
#把图像转为黑白图像
gray_img=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
 
#检测图像中所有的脸
 
faces=face_haar.detectMultiScale(gray_img,1.3,5)
print(faces)
 
for face_x,face_y,face_w,face_h in faces:
    cv2.rectangle(img, (face_x, face_y), (face_x+face_w, face_y+face_h), (0,255,0), 2)
    # 眼长在脸上
    roi_gray_img=gray_img[face_y:face_y+face_h,face_x:face_x+face_w]
    roi_img=img[face_y:face_y+face_h,face_x:face_x+face_w]
    eyes=eye_haar.detectMultiScale(roi_gray_img,1.3,5)
    for eye_x,eye_y,eye_w,eye_h in eyes:
        cv2.rectangle(roi_img, (eye_x,eye_y), (eye_x+eye_w, eye_y+eye_h), (255,0,0), 2)
 
cv2.imshow('img', img)
cv2.waitKey(0)
 
cv2.destroyAllWindows()

 

 

https://blog.csdn.net/eereere/article/details/79582988

 https://zhuanlan.zhihu.com/p/63154631

 

2.

-(void)processImage:(cv::Mat &)image {
    if( GetTickCount()-self.dwLastCaptureTime < 1000/frame)
        return;
    self.dwLastCaptureTime = GetTickCount();



long GetTickCount()
{
    struct timeval tv;
    
    if(gettimeofday(&tv, 0))
        return 0;
    
    return (tv.tv_sec * 1000) + (tv.tv_usec / 1000);
}