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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 mmengine.dataset import DefaultSampler
from mmpretrain.datasets import (ImageNet21k, LoadImageFromFile, PackInputs,
RandomFlip, RandomResizedCrop)
# dataset settings
dataset_type = ImageNet21k
data_preprocessor = dict(
num_classes=21842,
# RGB format normalization parameters
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
# convert image from BGR to RGB
to_rgb=True,
)
train_pipeline = [
dict(type=LoadImageFromFile),
dict(type=RandomResizedCrop, scale=224),
dict(type=RandomFlip, prob=0.5, direction='horizontal'),
dict(type=PackInputs),
]
train_dataloader = dict(
batch_size=128,
num_workers=5,
dataset=dict(
type=dataset_type,
data_root='data/imagenet21k',
split='train',
pipeline=train_pipeline),
sampler=dict(type=DefaultSampler, shuffle=True),
)
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