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import os | |
import argparse | |
import json | |
from llava_phi.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) | |