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- # dataset settings
- dataset_type = 'ReIDDataset'
- data_root = 'data/MOT17/'
- backend_args = None
- # data pipeline
- train_pipeline = [
- dict(
- type='TransformBroadcaster',
- share_random_params=False,
- transforms=[
- dict(
- type='LoadImageFromFile',
- backend_args=backend_args,
- to_float32=True),
- dict(
- type='Resize',
- scale=(128, 256),
- keep_ratio=False,
- clip_object_border=False),
- dict(type='RandomFlip', prob=0.5, direction='horizontal'),
- ]),
- dict(type='PackReIDInputs', meta_keys=('flip', 'flip_direction'))
- ]
- test_pipeline = [
- dict(type='LoadImageFromFile', backend_args=backend_args, to_float32=True),
- dict(type='Resize', scale=(128, 256), keep_ratio=False),
- dict(type='PackReIDInputs')
- ]
- # dataloader
- train_dataloader = dict(
- batch_size=1,
- num_workers=2,
- persistent_workers=True,
- sampler=dict(type='DefaultSampler', shuffle=True),
- dataset=dict(
- type=dataset_type,
- data_root=data_root,
- triplet_sampler=dict(num_ids=8, ins_per_id=4),
- data_prefix=dict(img_path='reid/imgs'),
- ann_file='reid/meta/train_80.txt',
- pipeline=train_pipeline))
- val_dataloader = dict(
- batch_size=1,
- num_workers=2,
- persistent_workers=True,
- drop_last=False,
- sampler=dict(type='DefaultSampler', shuffle=False),
- dataset=dict(
- type=dataset_type,
- data_root=data_root,
- triplet_sampler=None,
- data_prefix=dict(img_path='reid/imgs'),
- ann_file='reid/meta/val_20.txt',
- pipeline=test_pipeline))
- test_dataloader = val_dataloader
- # evaluator
- val_evaluator = dict(type='ReIDMetrics', metric=['mAP', 'CMC'])
- test_evaluator = val_evaluator
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