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| from functools import lru_cache | |
| import cv2 | |
| import numpy as np | |
| def visualize_instances(imask, bg_color=255, | |
| boundaries_color=None, boundaries_width=1, boundaries_alpha=0.8): | |
| num_objects = imask.max() + 1 | |
| palette = get_palette(num_objects) | |
| if bg_color is not None: | |
| palette[0] = bg_color | |
| result = palette[imask].astype(np.uint8) | |
| if boundaries_color is not None: | |
| boundaries_mask = get_boundaries(imask, boundaries_width=boundaries_width) | |
| tresult = result.astype(np.float32) | |
| tresult[boundaries_mask] = boundaries_color | |
| tresult = tresult * boundaries_alpha + (1 - boundaries_alpha) * result | |
| result = tresult.astype(np.uint8) | |
| return result | |
| def get_palette(num_cls): | |
| palette = np.zeros(3 * num_cls, dtype=np.int32) | |
| for j in range(0, num_cls): | |
| lab = j | |
| i = 0 | |
| while lab > 0: | |
| palette[j*3 + 0] |= (((lab >> 0) & 1) << (7-i)) | |
| palette[j*3 + 1] |= (((lab >> 1) & 1) << (7-i)) | |
| palette[j*3 + 2] |= (((lab >> 2) & 1) << (7-i)) | |
| i = i + 1 | |
| lab >>= 3 | |
| return palette.reshape((-1, 3)) | |
| def visualize_mask(mask, num_cls): | |
| palette = get_palette(num_cls) | |
| mask[mask == -1] = 0 | |
| return palette[mask].astype(np.uint8) | |
| def visualize_proposals(proposals_info, point_color=(255, 0, 0), point_radius=1): | |
| proposal_map, colors, candidates = proposals_info | |
| proposal_map = draw_probmap(proposal_map) | |
| for x, y in candidates: | |
| proposal_map = cv2.circle(proposal_map, (y, x), point_radius, point_color, -1) | |
| return proposal_map | |
| def draw_probmap(x): | |
| return cv2.applyColorMap((x * 255).astype(np.uint8), cv2.COLORMAP_HOT) | |
| def draw_points(image, points, color, radius=3): | |
| image = image.copy() | |
| for p in points: | |
| if p[0] < 0: | |
| continue | |
| if len(p) == 3: | |
| pradius = {0: 8, 1: 6, 2: 4}[p[2]] if p[2] < 3 else 2 | |
| else: | |
| pradius = radius | |
| image = cv2.circle(image, (int(p[1]), int(p[0])), pradius, color, -1) | |
| return image | |
| def draw_instance_map(x, palette=None): | |
| num_colors = x.max() + 1 | |
| if palette is None: | |
| palette = get_palette(num_colors) | |
| return palette[x].astype(np.uint8) | |
| def blend_mask(image, mask, alpha=0.6): | |
| if mask.min() == -1: | |
| mask = mask.copy() + 1 | |
| imap = draw_instance_map(mask) | |
| result = (image * (1 - alpha) + alpha * imap).astype(np.uint8) | |
| return result | |
| def get_boundaries(instances_masks, boundaries_width=1): | |
| boundaries = np.zeros((instances_masks.shape[0], instances_masks.shape[1]), dtype=bool) | |
| for obj_id in np.unique(instances_masks.flatten()): | |
| if obj_id == 0: | |
| continue | |
| obj_mask = instances_masks == obj_id | |
| kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3)) | |
| inner_mask = cv2.erode(obj_mask.astype(np.uint8), kernel, iterations=boundaries_width).astype(bool) | |
| obj_boundary = np.logical_xor(obj_mask, np.logical_and(inner_mask, obj_mask)) | |
| boundaries = np.logical_or(boundaries, obj_boundary) | |
| return boundaries | |
| def draw_with_blend_and_clicks(img, mask=None, alpha=0.6, clicks_list=None, pos_color=(0, 255, 0), | |
| neg_color=(255, 0, 0), radius=4): | |
| result = img.copy() | |
| if mask is not None: | |
| palette = get_palette(np.max(mask) + 1) | |
| rgb_mask = palette[mask.astype(np.uint8)] | |
| mask_region = (mask > 0).astype(np.uint8) | |
| result = result * (1 - mask_region[:, :, np.newaxis]) + \ | |
| (1 - alpha) * mask_region[:, :, np.newaxis] * result + \ | |
| alpha * rgb_mask | |
| result = result.astype(np.uint8) | |
| # result = (result * (1 - alpha) + alpha * rgb_mask).astype(np.uint8) | |
| if clicks_list is not None and len(clicks_list) > 0: | |
| pos_points = [click.coords for click in clicks_list if click.is_positive] | |
| neg_points = [click.coords for click in clicks_list if not click.is_positive] | |
| result = draw_points(result, pos_points, pos_color, radius=radius) | |
| result = draw_points(result, neg_points, neg_color, radius=radius) | |
| return result | |
| def draw_contour(img, mask, color=(253, 211, 106), thickness=2): | |
| contours, _ = cv2.findContours(mask.astype(np.uint8), cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) | |
| img = cv2.drawContours(img, contours, -1, color=color, thickness=thickness) | |
| return img | |
| def draw_mask(img, mask, opacity=0.6): | |
| mask = (mask > 0)[..., None] | |
| img = img * mask + img * ~mask * (1 - opacity) | |
| return img.astype(np.uint8) | |
| def draw_click(img, clicks, radius=5): | |
| for click in clicks: | |
| color = (146, 208, 80) if click.is_positive else (192, 0, 0) | |
| coords = (click.coords[1], click.coords[0]) | |
| img = cv2.circle(img.copy(), coords, int(radius * 1.5), (0, 0, 0), -1) | |
| img = cv2.circle(img, coords, radius, color, -1) | |
| return img |