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# Copyright (c) OpenMMLab. All rights reserved. | |
from __future__ import division | |
import numpy as np | |
from annotator.uniformer.mmcv.image import rgb2bgr | |
from annotator.uniformer.mmcv.video import flowread | |
from .image import imshow | |
def flowshow(flow, win_name='', wait_time=0): | |
"""Show optical flow. | |
Args: | |
flow (ndarray or str): The optical flow to be displayed. | |
win_name (str): The window name. | |
wait_time (int): Value of waitKey param. | |
""" | |
flow = flowread(flow) | |
flow_img = flow2rgb(flow) | |
imshow(rgb2bgr(flow_img), win_name, wait_time) | |
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 | |
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 make_color_wheel(bins=None): | |
"""Build a color wheel. | |
Args: | |
bins(list or tuple, optional): Specify the number of bins for each | |
color range, corresponding to six ranges: red -> yellow, | |
yellow -> green, green -> cyan, cyan -> blue, blue -> magenta, | |
magenta -> red. [15, 6, 4, 11, 13, 6] is used for default | |
(see Middlebury). | |
Returns: | |
ndarray: Color wheel of shape (total_bins, 3). | |
""" | |
if bins is None: | |
bins = [15, 6, 4, 11, 13, 6] | |
assert len(bins) == 6 | |
RY, YG, GC, CB, BM, MR = tuple(bins) | |
ry = [1, np.arange(RY) / RY, 0] | |
yg = [1 - np.arange(YG) / YG, 1, 0] | |
gc = [0, 1, np.arange(GC) / GC] | |
cb = [0, 1 - np.arange(CB) / CB, 1] | |
bm = [np.arange(BM) / BM, 0, 1] | |
mr = [1, 0, 1 - np.arange(MR) / MR] | |
num_bins = RY + YG + GC + CB + BM + MR | |
color_wheel = np.zeros((3, num_bins), dtype=np.float32) | |
col = 0 | |
for i, color in enumerate([ry, yg, gc, cb, bm, mr]): | |
for j in range(3): | |
color_wheel[j, col:col + bins[i]] = color[j] | |
col += bins[i] | |
return color_wheel.T | |