mmpretrain/configs/efficientnet/efficientnet-b8_8xb32-01norm_in1k.py
Ma Zerun a05c79e806
[Refactor] Move transforms in mmselfsup to mmpretrain. (#1396)
* [Refactor] Move transforms in mmselfsup to mmpretrain.

* Update transform docs and configs. And register some mmcv transforms in
mmpretrain.

* Fix missing transform wrapper.

* update selfsup transforms

* Fix UT

* Fix UT

* update gaussianblur inconfigs

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Co-authored-by: fangyixiao18 <fangyx18@hotmail.com>
2023-03-03 15:01:11 +08:00

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Python

_base_ = [
'../_base_/models/efficientnet_b8.py',
'../_base_/datasets/imagenet_bs32.py',
'../_base_/schedules/imagenet_bs256.py',
'../_base_/default_runtime.py',
]
# dataset settings
data_preprocessor = dict(
mean=[127.5, 127.5, 127.5],
std=[127.5, 127.5, 127.5],
# convert image from BGR to RGB
to_rgb=True,
)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='EfficientNetRandomCrop', scale=672),
dict(type='RandomFlip', prob=0.5, direction='horizontal'),
dict(type='PackInputs'),
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='EfficientNetCenterCrop', crop_size=672),
dict(type='PackInputs'),
]
train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
val_dataloader = dict(dataset=dict(pipeline=test_pipeline))
test_dataloader = dict(dataset=dict(pipeline=test_pipeline))