Created
February 16, 2021 22:55
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| def get_bbox(obj, max_x, max_y, padding=6): | |
| x0, y0 = obj['x'], obj['y'] | |
| x1, y1 = x0 + obj['w'], y0 + obj['h'] | |
| return max(x0-padding, 0), min(x1+padding, max_x), max(y0-padding, 0), min(y1+padding, max_y) | |
| def blur_context(img, sigma, bboxes): | |
| ksize = 0 | |
| img_blurred = cv2.GaussianBlur(img, (ksize, ksize), sigma) | |
| objs_mask = np.zeros_like(img) | |
| for bbox in bboxes: | |
| x0, x1, y0, y1 = bbox | |
| objs_mask[y0:y1, x0:x1:, :] = 255 | |
| objs_mask_blurred = cv2.GaussianBlur(objs_mask, (ksize, ksize), sigma) / 255 | |
| return (img_blurred * (1 - objs_mask_blurred) + objs_mask_blurred * img).round().clip(0, 255).astype('uint8') |
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