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