OpenCV视频实时跟踪目标，多种算法，python版

• 测试结果

同等条件下对比：

        'csrt',       # 261.0ms, lost 0
        'kcf',        #  51.0ms, lost 157
        'boosting',   #  23.7ms, lost 0
        'mil',        # 273.1ms, lost 0
        'tld',        # 100.7ms, lost 0
        'medianflow', #   6.6ms, lost 37
        'mosse'       #  10.7ms, lost 158

• 具体代码

  import cv2
  import time

  def init_tracker(frame):
  # 创建跟踪器
  if tracker_index == 0:
  tracker = cv2.legacy.TrackerCSRT_create()
  elif tracker_index == 1:
  tracker = cv2.legacy.TrackerKCF_create()
  elif tracker_index == 2:
  tracker = cv2.legacy.TrackerBoosting_create()
  elif tracker_index == 3:
  tracker = cv2.legacy.TrackerMIL_create()
  elif tracker_index == 4:
  tracker = cv2.legacy.TrackerTLD_create()
  elif tracker_index == 5:
  tracker = cv2.legacy.TrackerMedianFlow_create()
  elif tracker_index == 6:
  tracker = cv2.legacy.TrackerMOSSE_create()

    height, width = frame.shape[:2]
    bbox   = [int(width*(1-check_ratio)/2), int(height*(1-check_ratio)/2), width*check_ratio, height*check_ratio]
  
    # 初始化跟踪器
    ok = tracker.init(frame, bbox)
  
    return tracker, bbox

  def track_action(tracker, frame):
  current_time = time.time()

    result = frame.copy()
    
    # 更新跟踪器，获取新边界框
    ok, bbox = tracker.update(result)
  
    lost = 0
    if ok:
        # 跟踪成功：绘制边界框
        (x, y, w, h) = [int(v) for v in bbox]
        cv2.rectangle(result, (x, y), (x+w, y+h), (0, 255, 0), 2)
    else:
        # 跟踪失败
        lost = 1
        cv2.putText(result, "Tracking failure", (50, 80), cv2.FONT_HERSHEY_SIMPLEX, 2, (0,0,255), 2)
    cost_time = (time.time()-current_time)
    return result, cost_time, lost

  def track_video(input_video, output_video):

    # 读取视频
    input = cv2.VideoCapture(input_video)
    ok, frame = input.read()
    if not ok:
        print("Cannot read video")
        return
  
    fps    = int(input.get(cv2.CAP_PROP_FPS))
    width  = int(input.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(input.get(cv2.CAP_PROP_FRAME_HEIGHT))
    
    tracker, bbox = init_tracker(frame)
  
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    output = cv2.VideoWriter(output_video, fourcc, fps, (width*2, height))
  
    frame_counter = 0
    track_lost    = 0
    work_cost     = 0
    while True:
        ok, frame = input.read()
        if not ok:
            break
  
        frame_counter += 1
  
        track_frame, cost, lost = track_action(tracker, frame)
    
        work_cost  += cost
        track_lost += lost
        
        if (merge_video):
            track = cv2.hconcat([frame, track_frame])
        output.write(track)
    
        if (frame_counter % 100 == 0):
            print(frame_counter)
  
    print('tracker(%s): cost per frame(ms)=%.2f' % (tracker_names[tracker_index], (work_cost/frame_counter*1000)))
    print('tracker(%s): track(lost/total)=%d/%d'  % (tracker_names[tracker_index], track_lost, frame_counter))
    
    output.release()
    input.release()

  跟踪器类型, total 527 frames

  tracker name, cost per frame(ms), lost

  tracker_names = [
  'csrt', # 261.0ms, lost 0
  'kcf', # 51.0ms, lost 157
  'boosting', # 23.7ms, lost 0
  'mil', # 273.1ms, lost 0
  'tld', # 100.7ms, lost 0
  'medianflow', # 6.6ms, lost 37
  'mosse' # 10.7ms, lost 158
  ]

  merge_video = True
  check_ratio = 1/10
  tracker_index = 0

  input_video = 'test.mp4'
  output_video = 'track.mp4'

  for index in range(7):
  tracker_index = index
  output_video = ("track%d.mp4" % tracker_index)
  track_video(input_video, output_video)