57 lines
2.2 KiB
Python
57 lines
2.2 KiB
Python
import numpy as np
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from lib.test.evaluation.data import Sequence, BaseDataset, SequenceList
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from lib.test.utils.load_text import load_text
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import os
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class GOT10KDataset(BaseDataset):
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""" GOT-10k dataset.
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Publication:
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GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild
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Lianghua Huang, Xin Zhao, and Kaiqi Huang
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arXiv:1810.11981, 2018
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https://arxiv.org/pdf/1810.11981.pdf
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Download dataset from http://got-10k.aitestunion.com/downloads
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"""
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def __init__(self, split):
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super().__init__()
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# Split can be test, val, or ltrval (a validation split consisting of videos from the official train set)
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if split == 'test' or split == 'val':
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self.base_path = os.path.join(self.env_settings.got10k_path, split)
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else:
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self.base_path = os.path.join(self.env_settings.got10k_path, 'train')
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self.sequence_list = self._get_sequence_list(split)
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self.split = split
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def get_sequence_list(self):
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return SequenceList([self._construct_sequence(s) for s in self.sequence_list])
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def _construct_sequence(self, sequence_name):
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anno_path = '{}/{}/groundtruth.txt'.format(self.base_path, sequence_name)
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ground_truth_rect = load_text(str(anno_path), delimiter=',', dtype=np.float64)
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frames_path = '{}/{}'.format(self.base_path, sequence_name)
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frame_list = [frame for frame in os.listdir(frames_path) if frame.endswith(".jpg")]
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frame_list.sort(key=lambda f: int(f[:-4]))
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frames_list = [os.path.join(frames_path, frame) for frame in frame_list]
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return Sequence(sequence_name, frames_list, 'got10k', ground_truth_rect.reshape(-1, 4))
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def __len__(self):
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return len(self.sequence_list)
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def _get_sequence_list(self, split):
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with open('{}/list.txt'.format(self.base_path)) as f:
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sequence_list = f.read().splitlines()
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if split == 'ltrval':
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with open('{}/got10k_val_split.txt'.format(self.env_settings.dataspec_path)) as f:
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seq_ids = f.read().splitlines()
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sequence_list = [sequence_list[int(x)] for x in seq_ids]
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return sequence_list
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