(D_est_np, D_gt_np, abs_thres=3., rel_thres=0.05, dilate_radius=1)
| 18 | error_colormap = gen_error_colormap() |
| 19 | |
| 20 | def vis(D_est_np, D_gt_np, abs_thres=3., rel_thres=0.05, dilate_radius=1): |
| 21 | B, H, W = D_gt_np.shape |
| 22 | |
| 23 | mask = D_gt_np > 0 |
| 24 | error = np.abs(D_gt_np - D_est_np) |
| 25 | error[np.logical_not(mask)] = 0 |
| 26 | error[mask] = np.minimum(error[mask] / abs_thres, (error[mask] / D_gt_np[mask]) / rel_thres) |
| 27 | cols = error_colormap |
| 28 | error_image = np.zeros([B, H, W, 3], dtype=np.float32) |
| 29 | for i in range(cols.shape[0]): |
| 30 | error_image[np.logical_and(error >= cols[i][0], error < cols[i][1])] = cols[i, 2:] |
| 31 | |
| 32 | error_image[np.logical_not(mask)] = 0. |
| 33 | for i in range(cols.shape[0]): |
| 34 | distance = 20 |
| 35 | error_image[:, :10, i * distance:(i + 1) * distance, :] = cols[i, 2:] |
| 36 | |
| 37 | return np.ascontiguousarray(error_image.transpose([0, 3, 1, 2])) |
| 38 | |
| 39 |
no outgoing calls