python+openCV利用摄像头实现人员活动检测

camera = cv2.VideoCapture(0)

width = int(camera.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))

gray_pic = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

start = time.time()
"""
xxxxx中间一部分代码省略
"""
 seconds = end - start
 if seconds < 1.0 / fps:
 time.sleep(1.0 / fps - seconds）

gray_pic = cv2.GaussianBlur(gray_pic, (21, 21), 0) 

img_delta = cv2.absdiff(pre_frame, gray_pic)

thresh = cv2.threshold(img_delta, 30, 255, cv2.THRESH_BINARY)[1]

thresh = cv2.dilate(thresh, None, iterations=2)

image, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

if cv2.waitKey(1) & 0xFF == ord('q'):
 break

import cv2
import time
# 定义摄像头对象，其参数0表示第一个摄像头
camera = cv2.VideoCapture(0)
# 测试用,查看视频size
width = int(camera.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = width,height
#打印一下分辨率
print(repr(size))
#设置一下帧数和前背景
fps = 5
pre_frame = None
 
while (1):
 start = time.time()
 # 读取视频流
 ret, frame = camera.read()
 # 转灰度图
 gray_pic = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
 if not ret:
 print("打开摄像头失败")
 break
 end = time.time()
 
 cv2.imshow("capture", frame)
 
 # 运动检测部分,看看是不是5FPS
 seconds = end - start
 if seconds < 1.0 / fps:
 time.sleep(1.0 / fps - seconds)
 gray_pic = cv2.resize(gray_pic, (480, 480))
 # 用高斯滤波进行模糊处理
 gray_pic = cv2.GaussianBlur(gray_pic, (21, 21), 0)
 
 # 如果没有背景图像就将当前帧当作背景图片
 if pre_frame is None:
 pre_frame = gray_pic
 else:
 # absdiff把两幅图的差的绝对值输出到另一幅图上面来
 img_delta = cv2.absdiff(pre_frame, gray_pic)
 # threshold阈值函数(原图像应该是灰度图,对像素值进行分类的阈值,当像素值高于（有时是小于）阈值时应该被赋予的新的像素值,阈值方法)
 thresh = cv2.threshold(img_delta, 30, 255, cv2.THRESH_BINARY)[1]
 # 用一下腐蚀与膨胀
 thresh = cv2.dilate(thresh, None, iterations=2)
 # findContours检测物体轮廓(寻找轮廓的图像,轮廓的检索模式,轮廓的近似办法)
 image, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
 for c in contours:
  # 设置敏感度
  # contourArea计算轮廓面积
  if cv2.contourArea(c) < 1000:
  continue
  else:
  print("有人员活动！！！")
  # 保存图像
  TI = time.strftime('%Y-%m-%d', time.localtime(time.time()))
  cv2.imwrite("D:\\PYthon\\first_j\\" + "JC"+TI+ '.jpg', frame)
  break
 pre_frame = gray_pic
 
 if cv2.waitKey(1) & 0xFF == ord('q'):
 break
 
# release()释放摄像头
camera.release()
# destroyAllWindows()关闭所有图像窗口
cv2.destroyAllWindows()