import cv2
import threading
import RPi.GPIO as GPIO
# import time
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(23, GPIO.OUT)
GPIO.setup(24, GPIO.OUT)
GPIO.output(23, GPIO.HIGH)
GPIO.output(24, GPIO.HIGH)
cap = cv2.VideoCapture(0) # 开启摄像头
classifier = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml')
ok, faceImg = cap.read() # 读取摄像头图像
if ok is False:
print('无法读取到摄像头！')
high=faceImg.shape[0]
width=faceImg.shape[1]
left_point = width/2+25
right_point = width/2-25
gray = cv2.cvtColor(faceImg,cv2.COLOR_BGR2GRAY)
faceRects = classifier.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=3,minSize=(32, 32))
close=0
def LEFT():
GPIO.output(23, GPIO.LOW)
GPIO.output(24, GPIO.HIGH)
def RIGHT():
GPIO.output(23, GPIO.HIGH)
GPIO.output(24, GPIO.LOW)
def STOP():
GPIO.output(23, GPIO.HIGH)
GPIO.output(24, GPIO.HIGH)
def track():
while close==0:
gray = cv2.cvtColor(faceImg,cv2.COLOR_BGR2GRAY)
faceRects = classifier.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=3,minSize=(32, 32))
if len(faceRects):
x,y,w,h = faceRects[0]
# 框选出人脸 最后一个参数2是框线宽度
# cv2.rectangle(faceImg,(x, y), (x + w, y + h), (0,255,0), 2)
central_point = x+w/2
if central_point > left_point:
LEFT()
print("Left")
elif central_point < right_point:
RIGHT()
print("Right")
else:
STOP()
print("Central")
STOP()
print("Stop")
thread1 = threading.Thread(target=track)
thread1.start()
# 循环读取图像
while True:
faceImg = cap.read()[1] # 读取摄像头图像
cv2.imshow("faceImg",cv2.flip(faceImg,1))
if cv2.waitKey(10) == 27: # 通过esc键退出摄像
break
# 关闭摄像头
cap.release()
cv2.destroyAllWindows()
close=1
STOP()
print("Stop")
Track_Test.rar （9个子文件） 
Track_Test 
Track_C51_test_1.0.py 2KB haarcascade_eye.xml 333KB haarcascade_frontalface_alt_tree.xml 2.56MB haarcascade_frontalface_default.xml 908KB GPIO_DJ_test.py 588B haarcascade_frontalface_alt.xml 661KB Track_C51_test_1.1.py 2KB PC_Track_C51_test_1.0.py 2KB haarcascade_frontalface_alt2.xml 528KB
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