"PYTHON+OPENCV Practice" a color-based object tracking (lower) __python

In this paper, "PYTHON+OPENCV practice" A, color-based object tracking (I.)

The functional enhancements were made as follows:

(1) The addition of PTS emptying, that is, when the target is not detected, empty PTS, showing no longer traces of the image;

(2) The direction of motion and the current coordinate can be judged by the addition of the movement directions.

From collections import deque import NumPy as NP import time #import imutils import Cv2 #设定红色阈值, HSV space redlower = Np.array ([170, MB]) Redupper = Np.array ([179, 255, 255]) #初始化追踪点的列表 Mybuffer = pts = deque (maxlen=mybuffer) counter = 0 # Open the camera camera = Cv2.
    Videocapture (0) #等待两秒 time.sleep (3) #遍历每一帧 to detect a red cap 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, it erations=2) #膨胀操作, in fact, the first corrosion and expansion of the effect is open operation, remove noise mask = cv2.dilate (Mask, None, iterations=2) CNTs = cv2.findcontours (mas K.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 to perform paint if radius > 10:CV2.CIRCL
            E (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, and is added to the left Pts.appendleft (center) Else: #如果图像中没有检测到瓶盖, the PTS is emptied and the trajectory is not displayed on the image.
        Pts.clear () for I-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 >= ten 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 di RY Cv2.puttext (frame, direction, (m), Cv2. Font_hershey_simplex, 2, (0, 255, 0), 3) Cv2.puttext (frame, "DX: {}, dy: {}". Format (d X, DY), (Frame.shape[0]-ten), Cv2. Font_hershey_simplex, 0.35, (0, 0, 255), 1 cv2.imshow (' frame ', frame) #键盘检测, detect Esc key Exit K = Cv2.wa Itkey (1) &0xff counter + + 1 if k = = 27:break #摄像头释放 camera.release () #销毁所有窗口 cv2.destroyallwindows ()

Because the video is mirrored, the south-east result on the picture is correct.