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| # Process data | |
| import argparse | |
| from compute_softscore import compute_softscore | |
| from create_dictionary import create_dictionary | |
| from detection_features_converter import detection_features_converter | |
| if __name__ == '__main__': | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--dataroot', type=str, default='../data/') | |
| parser.add_argument('--ver', type=str, default='clean', help='version of the VQAv2 dataset to process. "clean" for the original data. default: clean') | |
| parser.add_argument('--detector', type=str, default='R-50') | |
| parser.add_argument('--feat', type=int, default=1024, help='feature size') | |
| parser.add_argument('--nb', type=int, default=36) | |
| parser.add_argument('--emb_dim', type=int, default=300) | |
| args = parser.parse_args() | |
| create_dictionary(args.dataroot, args.emb_dim) | |
| compute_softscore(args.dataroot, args.ver) | |
| detection_features_converter(args.dataroot, args.ver, args.detector, args.feat, args.nb) |