OpenCV3.0+Python3.6实现特定颜色的物体追踪

# -*- coding : utf-8 -*-# Author: Tom Yuimport cv2import numpy as np cap = cv2.VideoCapture(0)#获取摄像头图像# img = cv2.imread("timg1.jpg")# hsv_img = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) def nothing(x):  passdef createbars():  """  实现创建六个滑块的作用，分别控制H、S、V的最高值与最低值  """  cv2.createTrackbar("H_l","image",0,180,nothing)  cv2.createTrackbar("H_h","image",0,180,nothing)  cv2.createTrackbar("S_l","image",0,255,nothing)  cv2.createTrackbar("S_h","image",0,255,nothing)  cv2.createTrackbar("V_l","image",0,255,nothing)  cv2.createTrackbar("V_h","image",0,255,nothing)cv2.namedWindow("image")createbars()#创建六个滑块 lower = np.array([0,0,0])#设置初始值upper = np.array([0,0,0])while True:  ret,frame = cap.read()  hsv_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)#将图片由BGR颜色空间转化成HSV空间，HSV可以更好地分割颜色图形  lower[0]=cv2.getTrackbarPos("H_l","image")#获取"H_l"滑块的实时值  upper[0]=cv2.getTrackbarPos("H_h","image")#获取"H_h"滑块的实时值  lower[1]=cv2.getTrackbarPos("S_l","image")  upper[1]=cv2.getTrackbarPos("S_h","image")  lower[2]=cv2.getTrackbarPos("V_l","image")  upper[2]=cv2.getTrackbarPos("V_h","image")   mask = cv2.inRange(hsv_frame,lower,upper)#cv2.inrange()函数通过设定的最低、最高阈值获得图像的掩膜  cv2.imshow("img",frame)  cv2.imshow("mask",mask)  if cv2.waitKey(1)&0xff == 27:    break cv2.destroyAllWindows()

# -*- coding : utf-8 -*-# Author: Tom Yuimport cv2import numpy as np cap = cv2.VideoCapture(0)#获取摄像头视频 while True:  ret,frame = cap.read()#读取每一帧图片  hsv_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)#将每一帧图片转化HSV空间颜色  """  依据之前的脚本获取的阈值设置最高值与最低值  """  lower = np.array([0,104,205])  upper = np.array([15,208,255])   mask = cv2.inRange(hsv_frame,lower,upper)  img,conts,hier = cv2.findContours(mask,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)#找出边界  cv2.drawContours(frame,conts,-1,(0,255,0),3)#画出边框  dst = cv2.bitwise_and(frame,frame,mask=mask)#对每一帧进行位与操作，获取追踪图像的颜色  #cv2.imshow("mask",mask)  #cv2.imshow("dst",dst)  cv2.imshow("frame",frame)  if cv2.waitKey(1)&0xff == 27:    break cv2.destroyAllWindows()