python+opencv实时跟踪红色物体并画出轨迹实战

from collections import  deque
import numpy as np
#import imutils
import cv2
import time
#设定红色阈值，HSV空间
redLower = np.array([170, 100, 100])
redUpper = np.array([179, 255, 255])
#初始化追踪点的列表
mybuffer = 64
pts = deque(maxlen=mybuffer)
#打开摄像头
camera = cv2.VideoCapture(0)
#等待两秒
time.sleep(2)
#遍历每一帧，检测红色瓶盖
while True:
    #读取帧
    (ret, frame) = camera.read()
    #判断是否成功打开摄像头
    if not ret:
        print('No Camera')
        break
    #frame = imutils.resize(frame, width=600)
    #转到HSV空间
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    #根据阈值构建掩膜
    mask = cv2.inRange(hsv, redLower, redUpper)
    #腐蚀操作
    mask = cv2.erode(mask, None, iterations=2)
    #膨胀操作，其实先腐蚀再膨胀的效果是开运算，去除噪点
    mask = cv2.dilate(mask, None, iterations=2)
    #轮廓检测
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
    #初始化瓶盖圆形轮廓质心
    center = None
    #如果存在轮廓
    if len(cnts) > 0:
        #找到面积最大的轮廓
        c = max(cnts, key = cv2.contourArea)
        #确定面积最大的轮廓的外接圆
        ((x, y), radius) = cv2.minEnclosingCircle(c)
        #计算轮廓的矩
        M = cv2.moments(c)
        #计算质心
        center = (int(M["m10"]/M["m00"]), int(M["m01"]/M["m00"]))
        #只有当半径大于10时，才执行画图
        if radius > 10:
            cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
            cv2.circle(frame, center, 5, (0, 0, 255), -1)
            #把质心添加到pts中，并且是添加到列表左侧
            pts.appendleft(center)
    #遍历追踪点，分段画出轨迹
    for i in range(1, len(pts)):
        if pts[i - 1] is None or pts[i] is None:
            continue
        #计算所画小线段的粗细
        thickness = int(np.sqrt(mybuffer / float(i + 1)) * 2.5)
        #画出小线段
        cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
    #res = cv2.bitwise_and(frame, frame, mask=mask)
    cv2.imshow('Frame', frame)
    #键盘检测，检测到esc键退出
    k = cv2.waitKey(5)&0xFF
    if k == 27:
        break
#摄像头释放
camera.release()
#销毁所有窗口
cv2.destroyAllWindows()