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import numpy as np |
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import matplotlib.pyplot as plt |
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def show_mask(mask, ax, random_color=False, borders=True): |
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if random_color: |
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color = np.concatenate([np.random.random(3), np.array([0.6])], axis=0) |
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else: |
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color = np.array([30 / 255, 144 / 255, 255 / 255, 0.6]) |
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h, w = mask.shape[-2:] |
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mask = mask.astype(np.uint8) |
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mask_image = mask.reshape(h, w, 1) * color.reshape(1, 1, -1) |
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if borders: |
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import cv2 |
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) |
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contours = [ |
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cv2.approxPolyDP(contour, epsilon=0.01, closed=True) for contour in contours |
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] |
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mask_image = cv2.drawContours( |
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mask_image, contours, -1, (1, 1, 1, 0.5), thickness=2 |
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) |
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ax.imshow(mask_image) |
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def show_points(coords, labels, ax, marker_size=375): |
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pos_points = coords[labels == 1] |
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neg_points = coords[labels == 0] |
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ax.scatter( |
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pos_points[:, 0], |
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pos_points[:, 1], |
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color="green", |
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marker="*", |
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s=marker_size, |
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edgecolor="white", |
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linewidth=1.25, |
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) |
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ax.scatter( |
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neg_points[:, 0], |
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neg_points[:, 1], |
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color="red", |
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marker="*", |
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s=marker_size, |
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edgecolor="white", |
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linewidth=1.25, |
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) |
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def show_box(box, ax): |
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x0, y0 = box[0], box[1] |
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w, h = box[2] - box[0], box[3] - box[1] |
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ax.add_patch( |
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plt.Rectangle((x0, y0), w, h, edgecolor="green", facecolor=(0, 0, 0, 0), lw=2) |
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) |
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def show_masks( |
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image, |
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masks, |
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scores, |
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point_coords=None, |
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box_coords=None, |
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input_labels=None, |
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borders=True, |
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): |
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num_masks = len(masks) |
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num_cols = num_masks |
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fig, axes = plt.subplots(1, num_cols, figsize=(5 * num_cols, 5)) |
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if num_masks == 1: |
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axes = [axes] |
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for i, (mask, score) in enumerate(zip(masks, scores)): |
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ax = axes[i] |
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ax.imshow(image) |
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show_mask(mask, ax, borders=borders) |
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if point_coords is not None: |
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assert input_labels is not None |
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show_points(point_coords, input_labels, ax) |
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if box_coords is not None: |
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show_box(box_coords, ax) |
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if len(scores) > 1: |
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ax.set_title(f"Mask {i+1}, Score: {score:.3f}", fontsize=18) |
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ax.axis("off") |
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plt.tight_layout() |
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return plt |
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