hanluzhi0429@gmail.com
46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
import os
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import argparse
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import json
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from llava.eval.m4c_evaluator import EvalAIAnswerProcessor
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument("--annotation-file", type=str, required=True)
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parser.add_argument("--result-file", type=str, required=True)
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parser.add_argument("--result-upload-file", type=str, required=True)
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return parser.parse_args()
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if __name__ == "__main__":
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args = parse_args()
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os.makedirs(os.path.dirname(args.result_upload_file), exist_ok=True)
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results = []
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error_line = 0
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for line_idx, line in enumerate(open(args.result_file)):
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try:
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results.append(json.loads(line))
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except:
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error_line += 1
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results = {x["question_id"]: x["text"] for x in results}
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test_split = [json.loads(line) for line in open(args.annotation_file)]
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split_ids = set([x["question_id"] for x in test_split])
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print(f"total results: {len(results)}, total split: {len(test_split)}, error_line: {error_line}")
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all_answers = []
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answer_processor = EvalAIAnswerProcessor()
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for x in test_split:
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# import pdb; pdb.set_trace()
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assert x["question_id"] in results, print(x)
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all_answers.append({"image": x["image"], "answer": answer_processor(results[x["question_id"]])})
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with open(args.result_upload_file, "w") as f:
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json.dump(all_answers, f)
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