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import argparse |
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import json |
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import time |
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from scipy.io import loadmat |
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def parse_args(): |
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parser = argparse.ArgumentParser( |
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description='Converting the predicted .mat file to .json file.') |
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parser.add_argument('pred_mat_file', help='input prediction mat file.') |
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parser.add_argument( |
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'gt_json_file', |
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help='input ground-truth json file to get the image name. ' |
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'Default: "data/mpii/mpii_val.json" ') |
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parser.add_argument('output_json_file', help='output converted json file.') |
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args = parser.parse_args() |
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return args |
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def save_json(list_file, path): |
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with open(path, 'w') as f: |
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json.dump(list_file, f, indent=4) |
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return 0 |
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def convert_mat(pred_mat_file, gt_json_file, output_json_file): |
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res = loadmat(pred_mat_file) |
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preds = res['preds'] |
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N = preds.shape[0] |
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with open(gt_json_file) as anno_file: |
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anno = json.load(anno_file) |
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assert len(anno) == N |
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instance = {} |
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for pred, ann in zip(preds, anno): |
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ann.pop('joints_vis') |
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ann['joints'] = pred.tolist() |
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instance['annotations'] = anno |
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instance['info'] = {} |
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instance['info']['description'] = 'Converted MPII prediction.' |
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instance['info']['year'] = time.strftime('%Y', time.localtime()) |
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instance['info']['date_created'] = time.strftime('%Y/%m/%d', |
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time.localtime()) |
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save_json(instance, output_json_file) |
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def main(): |
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args = parse_args() |
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convert_mat(args.pred_mat_file, args.gt_json_file, args.output_json_file) |
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if __name__ == '__main__': |
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main() |
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