mmcv/visualization/optflow.py
def flow2rgb(flow, color_wheel=None, unknown_thr=1e6):
    """Convert flow map to RGB image.

    Args:
        flow (ndarray): Array of optical flow.
        color_wheel (ndarray or None): Color wheel used to map flow field to
            RGB colorspace. Default color wheel will be used if not specified.
        unknown_thr (str): Values above this threshold will be marked as
            unknown and thus ignored.

    Returns:
        ndarray: RGB image that can be visualized.
    """
    assert flow.ndim == 3 and flow.shape[-1] == 2
    if color_wheel is None:
        color_wheel = make_color_wheel()
    assert color_wheel.ndim == 2 and color_wheel.shape[1] == 3
    num_bins = color_wheel.shape[0]

    dx = flow[:, :, 0].copy()
    dy = flow[:, :, 1].copy()

    ignore_inds = (np.isnan(dx) | np.isnan(dy) | (np.abs(dx) > unknown_thr) |
                   (np.abs(dy) > unknown_thr))
    dx[ignore_inds] = 0
    dy[ignore_inds] = 0

    rad = np.sqrt(dx**2 + dy**2)
    if np.any(rad > np.finfo(float).eps):
        max_rad = np.max(rad)
        dx /= max_rad
        dy /= max_rad

    [h, w] = dx.shape

    rad = np.sqrt(dx**2 + dy**2)
    angle = np.arctan2(-dy, -dx) / np.pi

    bin_real = (angle + 1) / 2 * (num_bins - 1)
    bin_left = np.floor(bin_real).astype(int)
    bin_right = (bin_left + 1) % num_bins
    w = (bin_real - bin_left.astype(np.float32))[..., None]
    flow_img = (
        1 - w) * color_wheel[bin_left, :] + w * color_wheel[bin_right, :]
    small_ind = rad <= 1
    flow_img[small_ind] = 1 - rad[small_ind, None] * (1 - flow_img[small_ind])
    flow_img[np.logical_not(small_ind)] *= 0.75

    flow_img[ignore_inds, :] = 0

    return flow_img
def flow2rgb(flow, color_wheel=None, unknown_thr=1e6):
    """Convert flow map to RGB image.

    Args:
        flow (ndarray): Array of optical flow.
        color_wheel (ndarray or None): Color wheel used to map flow field to
            RGB colorspace. Default color wheel will be used if not specified.
        unknown_thr (str): Values above this threshold will be marked as
            unknown and thus ignored.

    Returns:
        ndarray: RGB image that can be visualized.
    """
    assert flow.ndim == 3 and flow.shape[-1] == 2
    if color_wheel is None:
        color_wheel = make_color_wheel()
    assert color_wheel.ndim == 2 and color_wheel.shape[1] == 3
    num_bins = color_wheel.shape[0]

    dx = flow[:, :, 0].copy()
    dy = flow[:, :, 1].copy()

    ignore_inds = (np.isnan(dx) | np.isnan(dy) | (np.abs(dx) > unknown_thr) |
                   (np.abs(dy) > unknown_thr))
    dx[ignore_inds] = 0
    dy[ignore_inds] = 0

    rad = np.sqrt(dx**2 + dy**2)
    if np.any(rad > np.finfo(float).eps):
        max_rad = np.max(rad)
        dx /= max_rad
        dy /= max_rad

    [h, w] = dx.shape

    rad = np.sqrt(dx**2 + dy**2)
    angle = np.arctan2(-dy, -dx) / np.pi

    bin_real = (angle + 1) / 2 * (num_bins - 1)
    bin_left = np.floor(bin_real).astype(int)
    bin_right = (bin_left + 1) % num_bins
    w = (bin_real - bin_left.astype(np.float32))[..., None]
    flow_img = (
        1 - w) * color_wheel[bin_left, :] + w * color_wheel[bin_right, :]
    small_ind = rad <= 1
    flow_img[small_ind] = 1 - rad[small_ind, None] * (1 - flow_img[small_ind])
    flow_img[np.logical_not(small_ind)] *= 0.75

    flow_img[ignore_inds, :] = 0

    return flow_img
def flow2rgb ( flow , color_wheel = None , unknown_thr = 1e6 ) : assert flow . ndim == 3 and flow . shape [ - 1 ] == 2 if color_wheel is None : color_wheel = make_color_wheel ( ) assert color_wheel . ndim == 2 and color_wheel . shape [ 1 ] == 3 num_bins = color_wheel . shape [ 0 ] dx = flow [ : , : , 0 ] . copy ( ) dy = flow [ : , : , 1 ] . copy ( ) ignore_inds = ( np . isnan ( dx ) | np . isnan ( dy ) | ( np . abs ( dx ) > unknown_thr ) | ( np . abs ( dy ) > unknown_thr ) ) dx [ ignore_inds ] = 0 dy [ ignore_inds ] = 0 rad = np . sqrt ( dx ** 2 + dy ** 2 ) if np . any ( rad > np . finfo ( float ) . eps ) : max_rad = np . max ( rad ) dx /= max_rad dy /= max_rad [ h , w ] = dx . shape rad = np . sqrt ( dx ** 2 + dy ** 2 ) angle = np . arctan2 ( - dy , - dx ) / np . pi bin_real = ( angle + 1 ) / 2 * ( num_bins - 1 ) bin_left = np . floor ( bin_real ) . astype ( int ) bin_right = ( bin_left + 1 ) % num_bins w = ( bin_real - bin_left . astype ( np . float32 ) ) [ ... , None ] flow_img = ( 1 - w ) * color_wheel [ bin_left , : ] + w * color_wheel [ bin_right , : ] small_ind = rad <= 1 flow_img [ small_ind ] = 1 - rad [ small_ind , None ] * ( 1 - flow_img [ small_ind ] ) flow_img [ np . logical_not ( small_ind ) ] *= 0.75 flow_img [ ignore_inds , : ] = 0 return flow_img
Convert flow map to RGB image.

    Args:
        flow (ndarray): Array of optical flow.
        color_wheel (ndarray or None): Color wheel used to map flow field to
            RGB colorspace. Default color wheel will be used if not specified.
        unknown_thr (str): Values above this threshold will be marked as
            unknown and thus ignored.

    Returns:
        ndarray: RGB image that can be visualized.
Convert flow map to RGB image .