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| # -------------------------------------------------------- | |
| # Python Single Object Tracking Evaluation | |
| # Licensed under The MIT License [see LICENSE for details] | |
| # Written by Fangyi Zhang | |
| # @author fangyi.zhang@vipl.ict.ac.cn | |
| # @project https://github.com/StrangerZhang/pysot-toolkit.git | |
| # Revised for SiamMask by foolwood | |
| # -------------------------------------------------------- | |
| import argparse | |
| import glob | |
| from os.path import join, realpath, dirname | |
| from tqdm import tqdm | |
| from multiprocessing import Pool | |
| from utils.pysot.datasets import VOTDataset | |
| from utils.pysot.evaluation import AccuracyRobustnessBenchmark, EAOBenchmark | |
| if __name__ == '__main__': | |
| parser = argparse.ArgumentParser(description='VOT Evaluation') | |
| parser.add_argument('--dataset', type=str, help='dataset name') | |
| parser.add_argument('--result_dir', type=str, help='tracker result root') | |
| parser.add_argument('--tracker_prefix', type=str, help='tracker prefix') | |
| parser.add_argument('--show_video_level', action='store_true') | |
| parser.add_argument('--num', type=int, help='number of processes to eval', default=1) | |
| args = parser.parse_args() | |
| root = join(realpath(dirname(__file__)), '../data') | |
| tracker_dir = args.result_dir | |
| trackers = glob.glob(join(tracker_dir, args.tracker_prefix+'*')) | |
| trackers = [t.split('/')[-1] for t in trackers] | |
| assert len(trackers) > 0 | |
| args.num = min(args.num, len(trackers)) | |
| if args.dataset in ['VOT2016', 'VOT2018', 'VOT2019']: | |
| dataset = VOTDataset(args.dataset, root) | |
| dataset.set_tracker(tracker_dir, trackers) | |
| ar_benchmark = AccuracyRobustnessBenchmark(dataset) | |
| ar_result = {} | |
| with Pool(processes=args.num) as pool: | |
| for ret in tqdm(pool.imap_unordered(ar_benchmark.eval, | |
| trackers), desc='eval ar', total=len(trackers), ncols=100): | |
| ar_result.update(ret) | |
| benchmark = EAOBenchmark(dataset) | |
| eao_result = {} | |
| with Pool(processes=args.num) as pool: | |
| for ret in tqdm(pool.imap_unordered(benchmark.eval, | |
| trackers), desc='eval eao', total=len(trackers), ncols=100): | |
| eao_result.update(ret) | |
| ar_benchmark.show_result(ar_result, eao_result, show_video_level=args.show_video_level) | |