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- # dataset settings
- _base_ = 'coco_instance.py'
- dataset_type = 'LVISV05Dataset'
- data_root = 'data/lvis_v0.5/'
- data = dict(
- samples_per_gpu=2,
- workers_per_gpu=2,
- train=dict(
- _delete_=True,
- type='ClassBalancedDataset',
- oversample_thr=1e-3,
- dataset=dict(
- type=dataset_type,
- ann_file=data_root + 'annotations/lvis_v0.5_train.json',
- img_prefix=data_root + 'train2017/')),
- val=dict(
- type=dataset_type,
- ann_file=data_root + 'annotations/lvis_v0.5_val.json',
- img_prefix=data_root + 'val2017/'),
- test=dict(
- type=dataset_type,
- ann_file=data_root + 'annotations/lvis_v0.5_val.json',
- img_prefix=data_root + 'val2017/'))
- evaluation = dict(metric=['bbox', 'segm'])
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