使用静态照片的HAAR分类器识别眼睛

Question

可以在静态照片上使用haarclassifier而不是网络摄像头的实时流？

import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0)
while 1:
    ret, img = cap.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
        eyes = eye_cascade.detectMultiScale(roi_gray)
        for (ex,ey,ew,eh) in eyes:
            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,127,255),2)
    cv2.imshow('img',img)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
        cap.release()
cv2.destroyAllWindows()

我只需要识别照片的一只或全眼，而没有脸。有什么建议？

Answer 1

i从ur code

编辑

import cv2
#load haarcascade_eye
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
# Load an color image
img = cv2.imread('Test_Image.jpg',cv2.IMREAD_COLOR)
#convert to gray scale to work with HAAR
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#read HAAR ade loop for find eye(s)
eyes = eye_cascade.detectMultiScale(gray)
for (ex,ey,ew,eh) in eyes:
    cv2.rectangle(img,(ex,ey),(ex+ew,ey+eh),(0,127,255),2)
#show eye(s) rectangle in color image
cv2.imshow('img',img)
#press any key to close
cv2.waitKey(0)
cv2.destroyAllWindows()