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