Python cv2.OPTFLOW_FARNEBACK_GAUSSIAN Examples

The following are 2 code examples of cv2.OPTFLOW_FARNEBACK_GAUSSIAN(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: tracking_engine.py    From DetectAndTrack with Apache License 2.0 6 votes vote down vote up 
def run_farneback(frames):
    try:
        return cv2.calcOpticalFlowFarneback(
            frames[0], frames[1],
            # options, defaults
            None,  # output
            0.5,  # pyr_scale, 0.5
            10,  # levels, 3
            min(frames[0].shape[:2]) // 5,  # winsize, 15
            10,  # iterations, 3
            7,  # poly_n, 5
            1.5,  # poly_sigma, 1.2
            cv2.OPTFLOW_FARNEBACK_GAUSSIAN,  # flags, 0
        )
    except cv2.error:
        return None
Example #2
Source File: video_avi_flow.py    From self-supervision with BSD 3-Clause "New" or "Revised" License 4 votes vote down vote up 
def extract_optical_flow(fn, times, frames=8, scale_factor=1.0):
    cap = cv2.VideoCapture(fn)
    if not cap.isOpened():
        return []
    n_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
    outputs = []
    if n_frames < frames * 2:
        return outputs

    def resize(im):
        if scale_factor != 1.0:
            new_size = (int(im.shape[1] * scale_factor), int(im.shape[0] * scale_factor))
            return cv2.resize(im, new_size, interpolation=cv2.INTER_LINEAR)
        else:
            return im

    for t in times:
        cap.set(cv2.CAP_PROP_POS_FRAMES, min(t * n_frames, n_frames - 1 - frames))
        ret, frame0 = cap.read()
        im0 = resize(cv2.cvtColor(frame0, cv2.COLOR_BGR2GRAY))
        mags = []
        middle_frame = frame0
        flows = []
        for f in range(frames - 1):
            ret, frame1 = cap.read()
            if f == frames // 2:
                middle_frame = frame1
            im1 = resize(cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY))
            flow = cv2.calcOpticalFlowFarneback(im0, im1,
                        None,
                        0.5, # py_scale
                        8,   # levels
                        int(40 * scale_factor),  # winsize
                        10,   # iterations
                        5,  # poly_n
                        1.1, # poly_sigma
                        cv2.OPTFLOW_FARNEBACK_GAUSSIAN)
            #mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
            #mags.append(mag)
            flows.append(flow)
            im0 = im1
        flow = (np.mean(flows, 0) / 100).clip(-1, 1)

        #flow = np.mean(flows, 0)
        #flow /= (flow.mean() * 5 + 1e-5)
        #flow = flow.clip(-1, 1)
        #flows = flows / (np.mean(flows, 0, keepdims=True) + 1e-5)
        x = middle_frame[..., ::-1].astype(np.float32) / 255
        outputs.append((x, flow))
    return outputs