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| # Copyright (c) OpenMMLab. All rights reserved. | |
| # This is a BETA new format config file, and the usage may change recently. | |
| from mmcv.transforms import (LoadImageFromFile, RandomApply, RandomFlip, | |
| RandomGrayscale) | |
| from mmengine.dataset import DefaultSampler, default_collate | |
| from mmpretrain.datasets import (ColorJitter, GaussianBlur, ImageNet, | |
| MultiView, PackInputs, RandomResizedCrop) | |
| from mmpretrain.models import SelfSupDataPreprocessor | |
| # dataset settings | |
| dataset_type = 'ImageNet' | |
| data_root = 'data/imagenet/' | |
| data_preprocessor = dict( | |
| type=SelfSupDataPreprocessor, | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True) | |
| view_pipeline = [ | |
| dict(type=RandomResizedCrop, scale=224, backend='pillow'), | |
| dict(type=RandomFlip, prob=0.5), | |
| dict( | |
| type=RandomApply, | |
| transforms=[ | |
| dict( | |
| type=ColorJitter, | |
| brightness=0.8, | |
| contrast=0.8, | |
| saturation=0.8, | |
| hue=0.2) | |
| ], | |
| prob=0.8), | |
| dict( | |
| type=RandomGrayscale, | |
| prob=0.2, | |
| keep_channels=True, | |
| channel_weights=(0.114, 0.587, 0.2989)), | |
| dict( | |
| type=GaussianBlur, | |
| magnitude_range=(0.1, 2.0), | |
| magnitude_std='inf', | |
| prob=0.5), | |
| ] | |
| train_pipeline = [ | |
| dict(type=LoadImageFromFile), | |
| dict(type=MultiView, num_views=2, transforms=[view_pipeline]), | |
| dict(type=PackInputs) | |
| ] | |
| train_dataloader = dict( | |
| batch_size=32, | |
| num_workers=4, | |
| persistent_workers=True, | |
| sampler=dict(type=DefaultSampler, shuffle=True), | |
| collate_fn=dict(type=default_collate), | |
| dataset=dict( | |
| type=ImageNet, | |
| data_root=data_root, | |
| ann_file='meta/train.txt', | |
| data_prefix=dict(img_path='train/'), | |
| pipeline=train_pipeline)) | |