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import os |
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import argparse |
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import json |
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import re |
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from llava.eval.m4c_evaluator import STVQAANLSEvaluator |
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def get_args(): |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--annotation-file', type=str) |
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parser.add_argument('--result-file', type=str) |
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parser.add_argument('--result-dir', type=str) |
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parser.add_argument('--mid_result', type=str) |
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parser.add_argument('--output_result', type=str) |
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return parser.parse_args() |
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def eval_single(annotation_file, result_file): |
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experiment_name = os.path.splitext(os.path.basename(result_file))[0] |
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print(experiment_name) |
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annotations = [ |
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json.loads(q) for q in open(os.path.expanduser(annotation_file), "r") |
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] |
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annotations = {(annotation['question_id'], annotation['question'].lower()): annotation for annotation in annotations} |
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results = [json.loads(line) for line in open(result_file)] |
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pred_list = [] |
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mid_list = [] |
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for result in results: |
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annotation = annotations[(result['question_id'], result['prompt'].lower())] |
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pred_list.append({ |
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"pred_answer": result['text'], |
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"gt_answers": [annotation['answer']], |
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}) |
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mid_list.append(result) |
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mid_list[-1]["gt_answers"] = annotation['answer'] |
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evaluator = STVQAANLSEvaluator() |
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acc = evaluator.eval_pred_list(pred_list) |
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acc = 100. * acc |
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print('Samples: {}\nAccuracy: {:.2f}%\n'.format(len(pred_list), acc)) |
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return len(pred_list), acc, mid_list |
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if __name__ == "__main__": |
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args = get_args() |
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if args.result_file is not None: |
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samples, acc, mid_result = eval_single(args.annotation_file, args.result_file) |
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if args.result_dir is not None: |
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for result_file in sorted(os.listdir(args.result_dir)): |
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if not result_file.endswith('.jsonl'): |
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print(f'Skipping {result_file}') |
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continue |
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samples, acc, mid_result = eval_single(args.annotation_file, os.path.join(args.result_dir, result_file)) |
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