349 lines
12 KiB
Python
349 lines
12 KiB
Python
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from typing import Union, TextIO
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import numpy as np
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from numba import jit
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from lib.test.evaluation.data import SequenceList, BaseDataset, Sequence
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class VOTDataset(BaseDataset):
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"""
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VOT2018 dataset
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Publication:
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The sixth Visual Object Tracking VOT2018 challenge results.
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Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman Pfugfelder, Luka Cehovin Zajc, Tomas Vojir,
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Goutam Bhat, Alan Lukezic et al.
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ECCV, 2018
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https://prints.vicos.si/publications/365
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Download the dataset from http://www.votchallenge.net/vot2018/dataset.html
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"""
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def __init__(self, year=18):
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super().__init__()
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self.year = year
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if year == 18:
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self.base_path = self.env_settings.vot18_path
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elif year == 20:
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self.base_path = self.env_settings.vot20_path
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elif year == 22:
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self.base_path = self.env_settings.vot22_path
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self.sequence_list = self._get_sequence_list(year)
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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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sequence_path = sequence_name
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nz = 8
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ext = 'jpg'
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start_frame = 1
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anno_path = '{}/{}/groundtruth.txt'.format(self.base_path, sequence_name)
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if self.year == 18 or self.year == 22:
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try:
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ground_truth_rect = np.loadtxt(str(anno_path), dtype=np.float64)
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except:
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ground_truth_rect = np.loadtxt(str(anno_path), delimiter=',', dtype=np.float64)
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end_frame = ground_truth_rect.shape[0]
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frames = ['{base_path}/{sequence_path}/color/{frame:0{nz}}.{ext}'.format(base_path=self.base_path,
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sequence_path=sequence_path, frame=frame_num, nz=nz, ext=ext)
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for frame_num in range(start_frame, end_frame+1)]
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# Convert gt
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if ground_truth_rect.shape[1] > 4:
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gt_x_all = ground_truth_rect[:, [0, 2, 4, 6]]
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gt_y_all = ground_truth_rect[:, [1, 3, 5, 7]]
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x1 = np.amin(gt_x_all, 1).reshape(-1,1)
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y1 = np.amin(gt_y_all, 1).reshape(-1,1)
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x2 = np.amax(gt_x_all, 1).reshape(-1,1)
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y2 = np.amax(gt_y_all, 1).reshape(-1,1)
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ground_truth_rect = np.concatenate((x1, y1, x2-x1, y2-y1), 1)
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elif self.year == 20:
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ground_truth_rect = read_file(str(anno_path))
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ground_truth_rect = np.array(ground_truth_rect, dtype=np.float64)
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end_frame = ground_truth_rect.shape[0]
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frames = ['{base_path}/{sequence_path}/color/{frame:0{nz}}.{ext}'.format(base_path=self.base_path,
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sequence_path=sequence_path,
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frame=frame_num, nz=nz, ext=ext)
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for frame_num in range(start_frame, end_frame + 1)]
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else:
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raise NotImplementedError
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return Sequence(sequence_name, frames, 'vot', ground_truth_rect)
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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, year):
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if year == 18:
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sequence_list= ['ants1',
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'ants3',
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'bag',
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'ball1',
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'ball2',
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'basketball',
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'birds1',
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'blanket',
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'bmx',
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'bolt1',
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'bolt2',
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'book',
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'butterfly',
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'car1',
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'conduction1',
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'crabs1',
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'crossing',
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'dinosaur',
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'drone_across',
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'drone_flip',
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'drone1',
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'fernando',
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'fish1',
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'fish2',
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'fish3',
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'flamingo1',
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'frisbee',
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'girl',
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'glove',
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'godfather',
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'graduate',
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'gymnastics1',
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'gymnastics2',
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'gymnastics3',
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'hand',
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'handball1',
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'handball2',
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'helicopter',
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'iceskater1',
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'iceskater2',
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'leaves',
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'matrix',
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'motocross1',
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'motocross2',
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'nature',
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'pedestrian1',
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'rabbit',
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'racing',
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'road',
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'shaking',
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'sheep',
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'singer2',
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'singer3',
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'soccer1',
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'soccer2',
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'soldier',
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'tiger',
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'traffic',
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'wiper',
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'zebrafish1']
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elif year == 20:
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sequence_list= ['agility',
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'ants1',
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'ball2',
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'ball3',
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'basketball',
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'birds1',
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'bolt1',
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'book',
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'butterfly',
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'car1',
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'conduction1',
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'crabs1',
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'dinosaur',
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'dribble',
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'drone1',
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'drone_across',
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'drone_flip',
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'fernando',
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'fish1',
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'fish2',
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'flamingo1',
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'frisbee',
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'girl',
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'glove',
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'godfather',
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'graduate',
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'gymnastics1',
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'gymnastics2',
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'gymnastics3',
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'hand',
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'hand02',
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'hand2',
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'handball1',
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'handball2',
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'helicopter',
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'iceskater1',
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'iceskater2',
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'lamb',
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'leaves',
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'marathon',
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'matrix',
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'monkey',
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'motocross1',
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'nature',
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'polo',
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'rabbit',
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'rabbit2',
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'road',
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'rowing',
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'shaking',
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'singer2',
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'singer3',
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'soccer1',
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'soccer2',
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'soldier',
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'surfing',
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'tiger',
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'wheel',
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'wiper',
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'zebrafish1']
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elif year == 22:
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sequence_list= ['agility',
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'animal',
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'ants1',
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'bag',
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'ball2',
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'ball3',
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'basketball',
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'birds1',
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'birds2',
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'bolt1',
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'book',
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'bubble',
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'butterfly',
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'car1',
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'conduction1',
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'crabs1',
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'dinosaur',
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'diver',
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'drone1',
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'drone_across',
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'fernando',
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'fish1',
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'fish2',
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'flamingo1',
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'frisbee',
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'girl',
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'graduate',
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'gymnastics1',
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'gymnastics2',
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'gymnastics3',
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'hand',
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'hand2',
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'handball1',
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'handball2',
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'helicopter',
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'iceskater1',
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'iceskater2',
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'kangaroo',
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'lamb',
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'leaves',
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'marathon',
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'matrix',
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'monkey',
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'motocross1',
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'nature',
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'polo',
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'rabbit',
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'rabbit2',
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'rowing',
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'shaking',
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'singer2',
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'singer3',
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'snake',
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'soccer1',
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'soccer2',
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'soldier',
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'surfing',
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'tennis',
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'tiger',
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'wheel',
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'wiper',
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'zebrafish1']
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else:
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raise NotImplementedError
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return sequence_list
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def parse(string):
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"""
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parse string to the appropriate region format and return region object
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"""
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from vot.region.shapes import Rectangle, Polygon, Mask
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if string[0] == 'm':
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# input is a mask - decode it
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m_, offset_, region = create_mask_from_string(string[1:].split(','))
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# return Mask(m_, offset=offset_)
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return region
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else:
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# input is not a mask - check if special, rectangle or polygon
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raise NotImplementedError
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print('Unknown region format.')
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return None
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def read_file(fp: Union[str, TextIO]):
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if isinstance(fp, str):
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with open(fp) as file:
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lines = file.readlines()
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else:
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lines = fp.readlines()
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regions = []
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# iterate over all lines in the file
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for i, line in enumerate(lines):
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regions.append(parse(line.strip()))
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return regions
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def create_mask_from_string(mask_encoding):
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"""
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mask_encoding: a string in the following format: x0, y0, w, h, RLE
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output: mask, offset
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mask: 2-D binary mask, size defined in the mask encoding
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offset: (x, y) offset of the mask in the image coordinates
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"""
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elements = [int(el) for el in mask_encoding]
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tl_x, tl_y, region_w, region_h = elements[:4]
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rle = np.array([el for el in elements[4:]], dtype=np.int32)
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# create mask from RLE within target region
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mask = rle_to_mask(rle, region_w, region_h)
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region = [tl_x, tl_y, region_w, region_h]
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return mask, (tl_x, tl_y), region
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@jit(nopython=True)
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def rle_to_mask(rle, width, height):
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"""
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rle: input rle mask encoding
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each evenly-indexed element represents number of consecutive 0s
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each oddly indexed element represents number of consecutive 1s
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width and height are dimensions of the mask
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output: 2-D binary mask
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"""
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# allocate list of zeros
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v = [0] * (width * height)
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# set id of the last different element to the beginning of the vector
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idx_ = 0
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for i in range(len(rle)):
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if i % 2 != 0:
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# write as many 1s as RLE says (zeros are already in the vector)
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for j in range(rle[i]):
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v[idx_+j] = 1
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idx_ += rle[i]
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