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import cv2 |
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import numpy as np |
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def mask2bbox(mask): |
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if len(np.where(mask > 0)[0]) == 0: |
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print(f'not mask') |
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return np.array([[0, 0], [0, 0]]).astype(np.int64) |
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x_ = np.sum(mask, axis=0) |
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y_ = np.sum(mask, axis=1) |
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x0 = np.min(np.nonzero(x_)[0]) |
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x1 = np.max(np.nonzero(x_)[0]) |
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y0 = np.min(np.nonzero(y_)[0]) |
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y1 = np.max(np.nonzero(y_)[0]) |
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return np.array([[x0, y0], [x1, y1]]).astype(np.int64) |
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def draw_outline(mask, frame): |
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_, binary_mask = cv2.threshold(mask, 0, 255, cv2.THRESH_BINARY) |
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contours, _ = cv2.findContours(binary_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
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cv2.drawContours(frame, contours, -1, (0, 0, 255), 2) |
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return frame |
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def draw_points(points, modes, frame): |
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neg_points = points[np.argwhere(modes==0)[:, 0]] |
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pos_points = points[np.argwhere(modes==1)[:, 0]] |
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for i in range(len(neg_points)): |
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point = neg_points[i] |
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cv2.circle(frame, (point[0], point[1]), 8, (255, 80, 80), -1) |
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for i in range(len(pos_points)): |
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point = pos_points[i] |
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cv2.circle(frame, (point[0], point[1]), 8, (0, 153, 255), -1) |
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return frame |
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if __name__ == '__main__': |
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mask = cv2.imread('./debug/mask.jpg', cv2.IMREAD_GRAYSCALE) |
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frame = cv2.imread('./debug/frame.jpg') |
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draw_frame = draw_outline(mask, frame) |
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cv2.imwrite('./debug/outline.jpg', draw_frame) |
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