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做了功能上的强化，强化如下：
（1）加了pts清空，即当没有检测到目标时，清空pts，显示的图像上不再有轨迹；
（2）加了运动方向判别，能够判别目标的运动方向及当前坐标。
# coding: utf-8#!/usr/bin/env pythonfrom collections import dequeimport numpy as npimport time#import imutilsimport cv2#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 = 16pts = deque(maxlen=mybuffer)counter = 0#打开摄像头camera = cv2.VideoCapture(0)#等待两秒time.sleep(3)#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) 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) else:#如果图像中没有检测到瓶盖，则清空pts，图像上不显示轨迹。 pts.clear() for i in xrange(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) #判断移动方向 if counter >= 10 and i == 1 and len(pts) >= 10: dX = pts[-10][0] - pts[i][0] dY = pts[-10][1] - pts[i][1] (dirX, dirY) = ("", "") if np.abs(dX) > 20: dirX = "East" if np.sign(dX) == 1 else "West" if np.abs(dY) > 20: dirY = "North" if np.sign(dY) == 1 else "South" if dirX != "" and dirY != "": direction = "{}-{}".format(dirY, dirX) else: direction = dirX if dirX != "" else dirY cv2.putText(frame, direction, (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 255, 0), 3) cv2.putText(frame, "dx: {}, dy: {}".format(dX, dY), (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1) cv2.imshow('Frame', frame) #键盘检测，检测到esc键退出 k = cv2.waitKey(1)&0xFF counter += 1 if k == 27: break#摄像头释放camera.release()#销毁所有窗口cv2.destroyAllWindows() 转载地址：http://qfrof.baihongyu.com/