人眼检测

face_cascade =cv2.CascadeClassifier('F:\\opencv-3.4.1\\data\\haarcascades\\haarcascade_frontalface_alt.xml')
eye_cascade = cv2.CascadeClassifier('F:\\opencv-3.4.1\\data\haarcascades\\haarcascade_eye.xml')
if face_cascade.empty():
    raise IOError('Unable to load the face cascade classifier xml file')
scaling_factor = 1
img = cv2.imread('C:\\Users\\lenovo\\Desktop\\1.png', cv2.IMREAD_ANYCOLOR)
frame = cv2.resize(img, None, fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_AREA)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
    print(x,y,w,h)
    cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 1)
    roi_gray = gray[y:y+h, x:x+w]
    roi_color = frame[y:y+h, x:x+w]
    eyes = eye_cascade.detectMultiScale(roi_gray)
    for (x_eye,y_eye,w_eye,h_eye) in eyes:
        print('eye:',x_eye,y_eye,w_eye,h_eye)
        center = (int(x_eye + 0.5*w_eye), int(y_eye + 0.5*h_eye))
        radius = int(0.3 * (w_eye + h_eye))
        color = (0, 255, 0)
        thickness = 3
        cv2.circle(roi_color, center, radius, color, thickness)
cv2.imshow('Eye Detector', frame)
cv2.waitKey()