scripts/archived/convert_vizwiz_for_submission.py

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:
        # import pdb; pdb.set_trace()
        assert x["question_id"] in results, print(x)
        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)