|
|
|
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
|
|
|
