| |
| 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 |
|
|
