多目标追踪器：用 OpenCV 实现多目标追踪

    pip install opencv-python

    pip install --user opencv_contrib_python-3.4.3.18-cp37-cp37m-win_amd64.whl

    pip list

    阿里云 http://mirrors.aliyun.com/pypi/simple/
    
    中国科技大学 https://pypi.mirrors.ustc.edu.cn/simple/
    
    豆瓣(douban) http://pypi.douban.com/simple/
    
    清华大学 https://pypi.tuna.tsinghua.edu.cn/simple/
    
    中国科学技术大学 http://pypi.mirrors.ustc.edu.cn/simple/

    # Set video to load
     videoPath = "videos/run.mp4"
    
     # Create a video capture object to read videos
     cap = cv2.VideoCapture(videoPath)
    
     # Read first frame
     success, frame = cap.read()
     # quit if unable to read the video file
     if not success:
       print('Failed to read video')
       sys.exit(1)

    ## Select boxes
    bboxes = []
    colors = [] 
    
    # OpenCV's selectROI function doesn't work for selecting multiple objects in Python
    # So we will call this function in a loop till we are done selecting all objects
    while True:
     # draw bounding boxes over objects
     # selectROI's default behaviour is to draw box starting from the center
     # when fromCenter is set to false, you can draw box starting from top left corner
     bbox = cv2.selectROI('MultiTracker', frame)
     bboxes.append(bbox)
     colors.append((randint(0, 255), randint(0, 255), randint(0, 255)))
     print("Press q to quit selecting boxes and start tracking")
     print("Press any other key to select next object")
     k = cv2.waitKey(0) & 0xFF
     if (k == 113):  # q is pressed
       break
    
    print('Selected bounding boxes {}'.format(bboxes))

    # Specify the tracker type
    trackerType = "CSRT"   
    
    # Create MultiTracker object
    multiTracker = cv2.MultiTracker_create()
    
    # Initialize MultiTracker 
    for bbox in bboxes:
     multiTracker.add(createTrackerByName(trackerType), frame, bbox)