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import argparse |
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import json |
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import os |
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import re |
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import random |
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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) |
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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}) |
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return fakecaps |
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def get_pred_idx(prediction, choices, options): |
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""" |
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Get the index (e.g. 2) from the prediction (e.g. 'C') |
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""" |
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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 |
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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] |
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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(): |
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if prob_id not in predictions: |
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pred = {'text': 'FAILED', 'prompt': 'Unknown'} |
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pred_text = 'FAILED' |
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else: |
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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 |
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elif len(pred_text) >= 3 and pred_text[0] in args.options and pred_text[1:3] == ". ": |
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answer = pred_text[0] |
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else: |
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pattern = re.compile(r'The answer is ([A-Z]).') |
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res = pattern.findall(pred_text) |
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if len(res) == 1: |
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answer = res[0] |
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else: |
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answer = "FAILED" |
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pred_idx = get_pred_idx(answer, prob['choices'], args.options) |
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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'], |
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} |
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sqa_results['results'][prob_id] = get_pred_idx(answer, prob['choices'], args.options) |
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sqa_results['outputs'][prob_id] = pred_text |
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if pred_idx == prob['answer']: |
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results['correct'].append(analysis) |
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else: |
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results['incorrect'].append(analysis) |
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correct = len(results['correct']) |
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total = len(results['correct']) + len(results['incorrect']) |
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multimodal_correct = len([x for x in results['correct'] if x['is_multimodal']]) |
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multimodal_incorrect = len([x for x in results['incorrect'] if x['is_multimodal']]) |
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multimodal_total = multimodal_correct + multimodal_incorrect |
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print(f'Total: {total}, Correct: {correct}, Accuracy: {correct / total * 100:.2f}%, IMG-Accuracy: {multimodal_correct / multimodal_total * 100:.2f}%') |
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sqa_results['acc'] = correct / total * 100 |
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sqa_results['correct'] = correct |
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sqa_results['count'] = total |
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with open(args.output_file, 'w') as f: |
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json.dump(results, f, indent=2) |
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with open(args.output_result, 'w') as f: |
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json.dump(sqa_results, f, indent=2) |
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