
import cv2
cap = cv2.VideoCapture(0)
cap.set(3,640)#改变高度
cap.set(4,480)#改变宽度
cap.set(10,100)#改变亮度
def Face_Detect_Pic(image):
gray = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
cv2.imshow("gray", gray)
face_detector = cv2.CascadeClassifier("D:/python/venv/Lib/site-packages/cv2/data/haarcascade_frontalface_alt2.xml")#人脸识别器
faces_rect = face_detector.detectMultiScale(gray, 1.05, 7,0,(100,100),(600,600))
dst = image.copy()
for x, y, w, h in faces_rect:
cv2.rectangle(dst, (x, y), (x + w, y + h), (0, 0, 255), 3)
cv2.imshow("dst", dst)
return dst
def Face_Detect_Cam():
# 打开摄像头
capture = cv2.VideoCapture(0) # 0:本地摄像头 1:外接摄像头
while (True):
# 1、按帧读取视频
ret, frame = capture.read() # frame为每一帧的图像
# 2、左右翻转(否则向左右移动的时候,对象右左移动,反着移)
frame = cv2.flip(frame, 1)
# 3、对每一帧图像人脸识别
result = Face_Detect_Pic(frame)
# q键退出(设置读帧间隔时间)
if cv2.waitKey(1) & 0XFF == ord("q"):
break
image=cv2.imread("face1.jpg")
Face_Detect_Pic(image )
cv2.imshow("44",image )
Face_Detect_Cam() # 人脸识别(视频)
cv2.waitKey(0)欢迎分享,转载请注明来源:内存溢出
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