| import matplotlib.pyplot as plt |
| import numpy as np |
|
|
|
|
| def show_mask(mask, random_color=False): |
| if random_color: |
| color = np.concatenate([np.random.random(3), np.array([0.4])], axis=0) |
| else: |
| color = np.array([30, 144, 255, 0.4*255]) |
| h, w = mask.shape[-2:] |
| mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1) |
| ax = plt.gca() |
| ax.imshow(mask_image.astype(np.uint8)) |
| |
| |
| def show_anns(anns, save_mask_path, colors=0.35): |
| if len(anns) == 0: |
| return |
| ax = plt.gca() |
| ax.set_autoscale_on(False) |
| np.savez_compressed(save_mask_path, anns) |
| if len(anns) == 1: |
| mask = anns[0]['segmentation'] |
| h, w = mask.shape[-2:] |
| color = np.array([255, 165, 0, 0.6*255]) |
| mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1) |
| ax = plt.gca() |
| ax.imshow(mask_image.astype(np.uint8)) |
| else: |
| for ann in anns: |
| m = ann['segmentation'] |
| img = np.ones((m.shape[0], m.shape[1], 3)) |
| color_mask = np.random.random((1, 3)).tolist()[0] |
| for i in range(3): |
| img[:,:,i] = color_mask[i] |
| ax.imshow(np.dstack((img, m*colors))) |
| |
| |
| def show_box(box, ax): |
| x0, y0 = box[0], box[1] |
| w, h = box[2] - box[0], box[3] - box[1] |
| ax.add_patch(plt.Rectangle((x0, y0), w, h, edgecolor='green', facecolor=(0,0,0,0), lw=2)) |
