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hub / github.com/FoundationVision/ByteTrack / get_data_loader

Method get_data_loader

yolox/exp/yolox_base.py:81–138  ·  view source on GitHub ↗
(self, batch_size, is_distributed, no_aug=False)

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79 return self.model
80
81 def get_data_loader(self, batch_size, is_distributed, no_aug=False):
82 from yolox.data import (
83 COCODataset,
84 DataLoader,
85 InfiniteSampler,
86 MosaicDetection,
87 TrainTransform,
88 YoloBatchSampler
89 )
90
91 dataset = COCODataset(
92 data_dir=None,
93 json_file=self.train_ann,
94 img_size=self.input_size,
95 preproc=TrainTransform(
96 rgb_means=(0.485, 0.456, 0.406),
97 std=(0.229, 0.224, 0.225),
98 max_labels=50,
99 ),
100 )
101
102 dataset = MosaicDetection(
103 dataset,
104 mosaic=not no_aug,
105 img_size=self.input_size,
106 preproc=TrainTransform(
107 rgb_means=(0.485, 0.456, 0.406),
108 std=(0.229, 0.224, 0.225),
109 max_labels=120,
110 ),
111 degrees=self.degrees,
112 translate=self.translate,
113 scale=self.scale,
114 shear=self.shear,
115 perspective=self.perspective,
116 enable_mixup=self.enable_mixup,
117 )
118
119 self.dataset = dataset
120
121 if is_distributed:
122 batch_size = batch_size // dist.get_world_size()
123
124 sampler = InfiniteSampler(len(self.dataset), seed=self.seed if self.seed else 0)
125
126 batch_sampler = YoloBatchSampler(
127 sampler=sampler,
128 batch_size=batch_size,
129 drop_last=False,
130 input_dimension=self.input_size,
131 mosaic=not no_aug,
132 )
133
134 dataloader_kwargs = {"num_workers": self.data_num_workers, "pin_memory": True}
135 dataloader_kwargs["batch_sampler"] = batch_sampler
136 train_loader = DataLoader(self.dataset, **dataloader_kwargs)
137
138 return train_loader

Callers 1

before_trainMethod · 0.45

Calls 5

TrainTransformClass · 0.90
MosaicDetectionClass · 0.90
InfiniteSamplerClass · 0.90
YoloBatchSamplerClass · 0.90
DataLoaderClass · 0.90

Tested by

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