人脸检测

た入场券 2023-01-11 08:39 217阅读 0赞

待补充

import cv2
    print(cv2.__file__)
    img = cv2.imread('test5.jpg')
    #加载人脸特征,该文件在Python安装目录下，下面是我的绝对路径
    face_cascade = cv2.CascadeClassifier(r'/Users/wing/anaconda3/lib/python3.6/site-packages/cv2/data/haarcascade_frontalface_default.xml')
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    #检测出的人脸个数
    faces = face_cascade.detectMultiScale(gray,scaleFactor=1.15,minNeighbors =4,minSize=(5,5))
    print("Face:{0}".format(len(faces)))
    print(len(faces))
    for(x,y,w,h) in faces:
          cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
    cv2.namedWindow("Faces")
    cv2.imshow("Faces",img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dpbmdneW4_size_16_color_FFFFFF_t_70][]

import cv2
    import dlib
    import numpy as np
    predictor_model ='shape_predictor_68_face_landmarks/shape_predictor_68_face_landmarks.dat'
    detector = dlib.get_frontal_face_detector()
    predictor = dlib.shape_predictor(predictor_model)
    img = cv2.imread('test7.jpg')
    img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    rects = detector(img_gray,0)
    print(rects[0])
    for i in range(len(rects)):
        landmarks = np.matrix([[p.x,p.y] for p in predictor(img,rects[i]).parts()])
        print(landmarks,type(landmarks))
        for idx,point in enumerate(landmarks):
            pos = (point[0,0],point[0,1])
            cv2.circle(img,pos,3,color=(0,255,0))
            font = cv2.FONT_HERSHKY_SIMPLEX
            cv2.putText(img,str(idx+1),pos,font,0.5,(0,0,255),1,cv2.LINE_AA)
    cv2.imshow("img",img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dpbmdneW4_size_16_color_FFFFFF_t_70]: /images/20221119/2555a12cd7314a7d8cabe060d4c8cd08.png