mmselfsup/configs/selfsup/_base_/datasets/imagenet_simmim.py
2022-07-28 16:11:41 +08:00

42 lines
1018 B
Python

# dataset settings
data_source = 'ImageNet'
dataset_type = 'SingleViewDataset'
img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_pipeline = [
dict(
type='RandomResizedCrop',
size=192,
scale=(0.67, 1.0),
ratio=(3. / 4., 4. / 3.)),
dict(type='RandomHorizontalFlip')
]
# prefetch
prefetch = False
if not prefetch:
train_pipeline.extend(
[dict(type='ToTensor'),
dict(type='Normalize', **img_norm_cfg)])
train_pipeline.append(
dict(
type='SimMIMMaskGenerator',
input_size=192,
mask_patch_size=32,
model_patch_size=4,
mask_ratio=0.6))
# dataset summary
data = dict(
samples_per_gpu=256,
workers_per_gpu=8,
train=dict(
type=dataset_type,
data_source=dict(
type=data_source,
data_prefix='data/imagenet/train',
ann_file='data/imagenet/meta/train.txt',
),
pipeline=train_pipeline,
prefetch=prefetch))