segmentation from bbox instead of empty
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@ -323,20 +323,20 @@ def dataset_to_mmpose2d(coords_df, mmpose_json_file, img_size, markerset='custom
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coords_mk = coords.loc[coords.index.get_level_values(2)==marker]
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coords_list += coords_mk.tolist()+[2] if not np.isnan(coords_mk).any() else [0.0, 0.0, 0]
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num_keypoints = len(marker_list)
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# bbox
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x_coords = coords.loc[coords.index.get_level_values(3)=='x']
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y_coords = coords.loc[coords.index.get_level_values(3)=='y']
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min_x, min_y, max_x, max_y = np.nanmin(x_coords), np.nanmin(y_coords), np.nanmax(x_coords), np.nanmax(y_coords)
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bbox_width = max_x - min_x
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bbox_height = max_y - min_y
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# num_keypoints, id, category_id
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num_keypoints = len(marker_list)
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# bbox = [min_x, min_y, max_x, max_y]
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bbox = [min_x, min_y, bbox_width, bbox_height] # coco format
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id = person_ids[p]
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category_id = 1
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segmentation = [] # no segmentation
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segmentation = [[min_x, min_y, min_x, max_y, max_x, max_y, max_x, min_y]] # no segmentation
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area = bbox_width * bbox_height
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iscrowd = 0 # each annotation represents one single person
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