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A10G
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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)
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