【V1.0】基于树莓派OpenCV的摄像头人脸追踪系统
该系统目前结合了树莓派+51单片机
树莓派主要用于运行Python程序 追踪人脸 同时用GPIO口给出信号
单片机用于控制42步进电机导轨左右移动
资源：
https://download.csdn.net/download/weixin_53403301/80270053
最新：
https://blog.csdn.net/weixin_53403301/article/details/123252275
视频：
【V1.0】基于树莓派的OpenCV-Python摄像头人脸追踪系统-哔哩哔哩 https://b23.tv/gk7YVaO
【V1.0】基于树莓派的OpenCV-Python摄像头人脸追踪系统
先前的文章:
人脸追踪部分：
https://blog.csdn.net/weixin_53403301/article/details/120497427
单片机控制42步进电机导轨部分：
https://blog.csdn.net/weixin_53403301/article/details/122658780
树莓派Python代码如下：
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)
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)
cap = cv2.VideoCapture(0) # 开启摄像头
classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
def track():
faceRects = classifier.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=3,minSize=(32, 32))
if len(faceRects):
for faceRect in faceRects:
x,y,w,h = faceRect
# 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)
# print(x+w/2)
if x+w/2 > width/2+50:
print("Left")
LEFT()
# time.sleep(0.1)
elif x+w/2 < width/2-50:
print("Right")
RIGHT()
# time.sleep(0.1)
elif width/2-50 < x+w/2 < width/2+50:
print("Central")
STOP()
# 循环读取图像
while True:
ok, faceImg = cap.read() # 读取摄像头图像
if ok is False:
print('无法读取到摄像头！')
break
# faceImg = img
high=faceImg.shape[0]
width=faceImg.shape[1]
# print(width,high)
gray = cv2.cvtColor(faceImg,cv2.COLOR_BGR2GRAY)
cv2.imshow("faceImg",faceImg)
# 展示图像
thread = threading.Thread(target=track)
thread.start()
if cv2.waitKey(10) == 27: # 通过esc键退出摄像
break
# 关闭摄像头
cap.release()
cv2.destroyAllWindows()
纯Python代码如下：
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)
#
#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)
cap = cv2.VideoCapture(0) # 开启摄像头
classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
def track():
faceRects = classifier.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=3,minSize=(32, 32))
if len(faceRects):
for faceRect in faceRects:
x,y,w,h = faceRect
# 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)
# print(x+w/2)
if x+w/2 > width/2+50:
print("Left")
# LEFT()
# time.sleep(0.1)
elif x+w/2 < width/2-50:
print("Right")
# RIGHT()
# time.sleep(0.1)
elif width/2-50 < x+w/2 < width/2+50:
print("Central")
# STOP()
# 循环读取图像
while True:
ok, faceImg = cap.read() # 读取摄像头图像
if ok is False:
print('无法读取到摄像头！')
break
# faceImg = img
high=faceImg.shape[0]
width=faceImg.shape[1]
# print(width,high)
gray = cv2.cvtColor(faceImg,cv2.COLOR_BGR2GRAY)
cv2.imshow("faceImg",faceImg)
# 展示图像
thread = threading.Thread(target=track)
thread.start()
if cv2.waitKey(10) == 27: # 通过esc键退出摄像
break
# 关闭摄像头
cap.release()
cv2.destroyAllWindows()
版权声明：本文为CSDN博主「网易独家音乐人Mike Zhou」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/weixin_53403301/article/details/122898050
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