| import argparse
|
| import json
|
| import os
|
| import re
|
| import random
|
|
|
|
|
| def get_args():
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| parser = argparse.ArgumentParser()
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| parser.add_argument('--base-dir', type=str)
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| parser.add_argument('--result-file', type=str)
|
| parser.add_argument('--output-file', type=str)
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| parser.add_argument('--output-result', type=str)
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| parser.add_argument('--split', type=str, default='test')
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| parser.add_argument('--options', type=list, default=["A", "B", "C", "D", "E"])
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| return parser.parse_args()
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|
|
|
|
| def convert_caps(results):
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| fakecaps = []
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| for result in results:
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| image_id = result['question_id']
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| caption = result['text']
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| fakecaps.append({"image_id": int(image_id), "caption": caption})
|
| return fakecaps
|
|
|
|
|
| def get_pred_idx(prediction, choices, options):
|
| """
|
| Get the index (e.g. 2) from the prediction (e.g. 'C')
|
| """
|
| if prediction in options[:len(choices)]:
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| return options.index(prediction)
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| else:
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| return -1
|
| return random.choice(range(len(choices)))
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|
|
|
|
| if __name__ == "__main__":
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| args = get_args()
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|
|
| base_dir = args.base_dir
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| split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[args.split]
|
| problems = json.load(open(os.path.join(base_dir, "problems.json")))
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| predictions = [json.loads(line) for line in open(args.result_file)]
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| predictions = {pred['question_id']: pred for pred in predictions}
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| split_problems = {idx: problems[idx] for idx in split_indices}
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|
|
| results = {'correct': [], 'incorrect': []}
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| sqa_results = {}
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| sqa_results['acc'] = None
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| sqa_results['correct'] = None
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| sqa_results['count'] = None
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| sqa_results['results'] = {}
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| sqa_results['outputs'] = {}
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|
|
| for prob_id, prob in split_problems.items():
|
| if prob_id not in predictions:
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| pred = {'text': 'FAILED', 'prompt': 'Unknown'}
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| pred_text = 'FAILED'
|
| else:
|
| pred = predictions[prob_id]
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| pred_text = pred['text']
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|
|
| if pred_text in args.options:
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| answer = pred_text
|
| elif len(pred_text) >= 3 and pred_text[0] in args.options and pred_text[1:3] == ". ":
|
| answer = pred_text[0]
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| else:
|
| pattern = re.compile(r'The answer is ([A-Z]).')
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| res = pattern.findall(pred_text)
|
| if len(res) == 1:
|
| answer = res[0]
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| else:
|
| answer = "FAILED"
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|
|
| pred_idx = get_pred_idx(answer, prob['choices'], args.options)
|
|
|
| analysis = {
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| 'question_id': prob_id,
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| 'parsed_ans': answer,
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| 'ground_truth': args.options[prob['answer']],
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| 'question': pred['prompt'],
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| 'pred': pred_text,
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| 'is_multimodal': '<image>' in pred['prompt'],
|
| }
|
|
|
| sqa_results['results'][prob_id] = get_pred_idx(answer, prob['choices'], args.options)
|
| sqa_results['outputs'][prob_id] = pred_text
|
|
|
| if pred_idx == prob['answer']:
|
| results['correct'].append(analysis)
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| else:
|
| results['incorrect'].append(analysis)
|
|
|
| correct = len(results['correct'])
|
| total = len(results['correct']) + len(results['incorrect'])
|
|
|
|
|
| multimodal_correct = len([x for x in results['correct'] if x['is_multimodal']])
|
| multimodal_incorrect = len([x for x in results['incorrect'] if x['is_multimodal']])
|
| multimodal_total = multimodal_correct + multimodal_incorrect
|
|
|
|
|
| print(f'Total: {total}, Correct: {correct}, Accuracy: {correct / total * 100:.2f}%, IMG-Accuracy: {multimodal_correct / multimodal_total * 100:.2f}%')
|
|
|
| sqa_results['acc'] = correct / total * 100
|
| sqa_results['correct'] = correct
|
| sqa_results['count'] = total
|
|
|
| with open(args.output_file, 'w') as f:
|
| json.dump(results, f, indent=2)
|
| with open(args.output_result, 'w') as f:
|
| json.dump(sqa_results, f, indent=2)
|
|
|
