我第一次使用python 3.5和OpenCV 3.4.0.12尝试进行面部识别,并且在运行代码时出现此错误。
File "/Users/connorwoodford/anaconda3/envs/chatbot/lib/python3.5/site-packages/spyder/utils/site/sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "/Users/connorwoodford/Desktop/temp.py", line 11, in <module>
ret, img = cap.imread()
AttributeError: 'cv2.VideoCapture' object has no attribute 'imread'
代码:
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('CascadeClassifier')
cap = cv2.VideoCapture(0)
while True:
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), (255,0,0), 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), (0,255,0), 2)
cv2.imshow('img',img)
k = cv2.waitkey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
答案 0 :(得分:0)
你的eye_cascade指的是错误的级联文件,它应以.xml扩展名结尾。您可以从此处haarcascade_eye.xml下载。
另请注意,您对cv2.rectangle的调用格式不正确。
从
更改它cv2.rectangle(img, (x+y), (x+w, y+h), (255,0,0), 2)
到
cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)
你需要做的就是将捕获逻辑包装在一个方法中。完整代码如下:
import numpy as np
import cv2
def sample_demo():
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),(255,0,0),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),(0,255,0),2)
cv2.imshow('img',img)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
并简单地调用方法sample_demo()
sample_demo()