opencv - 如何在整个视频中保存Farnebacks方法的流量估计？

Question

我在视频上使用了Farneback的方法，但最终结果是光流的参数为flow.Magnitude和flow.Orientation仅适用于最后两帧。如何保存整个视频的结果？我的意思是我想保存第一到第二帧的计算结果，然后第二到第三，第三到第四，...，n-1 n

Answer 1

与上一帧相比，通常在while循环中为每一帧计算光流。因此，如果您保存流，则每次在循环中使用单独的文件名保存流文件时，将保存整个视频。

#pseudo code
params= {}#fill in the params needed to calculate flow
prev_frame=get_frame()
i_frame=1
while(1)
  cur_frame=get_frame()
  flow=calculate_flow(prev_frame, cur_frame, **params)
  save_path='frame_%d' % i_frame
  np.save(save_path, flow)
  i_frame += 1
  prev_frame=cur_frame

这是一些工作代码

def draw_optical_flow(current_frame_rgb, flow, step=20, scale=1.0, thickness=4):
    assert(len(flow.shape)==3)
    assert(current_frame_rgb.shape[0:2] == flow.shape[0:2])
    assert(flow.shape[2] == 2)
    for r in range(0, current_frame_rgb.shape[0], step):
        for c in range(0, current_frame_rgb.shape[1], step):
            cv2.arrowedLine(current_frame_rgb, (c,r), (int(c+scale*flow[r,c,0]), int(r+scale*flow[r,c,1])), (0,0,255), thickness=thickness )
    return current_frame_rgb

这是主要功能

def main():
    def graceful_exit():
        cv2.destroyAllWindows()
        sys.exit(0)

    cap = cv2.VideoCapture('data/sample.mov')
    ret, prev_frame_rgb = cap.read()
    flow=np.zeros((prev_frame_rgb.shape[0], prev_frame_rgb.shape[1], 2), dtype=np.float32)
    prev_frame_gray = cv2.cvtColor(prev_frame_rgb, cv2.COLOR_BGR2GRAY)
    farneback_params={
        'pyr_scale':0.5,'levels':3,
        'winsize':15,'iterations': 3,
        'poly_n': 5,'poly_sigma':1.2,
        'flags':cv2.OPTFLOW_USE_INITIAL_FLOW}
    num_frames_to_consider=180
    iFrame=1
    while(iFrame < num_frames_to_consider):
        ret, current_frame_rgb = cap.read()
        if(not ret):
            break
        current_frame_gray = cv2.cvtColor(current_frame_rgb, cv2.COLOR_BGR2GRAY)
        flow = cv2.calcOpticalFlowFarneback(prev_frame_gray, current_frame_gray, flow, **farneback_params)
        save_path='data/farneback_output/out_frame_%d.npy' % iFrame
        if not os.path.isdir(os.path.dirname(save_path)):
            os.makedirs(os.path.dirname(save_path))
        #save flow, and load it back
        np.save(save_path, flow)
        flow=np.load(save_path)
        prev_frame_gray = current_frame_gray
        #show
        current_frame_rgb=draw_optical_flow(current_frame_rgb, flow)
        cv2.imshow('flow', current_frame_rgb)
        k=cv2.waitKey(0)
        if k == 27:
            graceful_exit()
        iFrame += 1

    graceful_exit()