33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
|
_base_ = [
|
||
|
|
'../_base_/models/segmenter_vit-b16_mask.py',
|
||
|
'../_base_/datasets/ade20k_640x640.py', '../_base_/default_runtime.py',
|
||
|
|
'../_base_/schedules/schedule_160k.py'
|
||
|
|
]
|
||
|
|
crop_size = (640, 640)
|
||
|
data_preprocessor = dict(size=crop_size)
|
||
|
checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/segmenter/vit_large_p16_384_20220308-d4efb41d.pth' # noqa
|
||
|
|
|
||
|
|
model = dict(
|
||
|
|
data_preprocessor=data_preprocessor,
|
||
|
|
pretrained=checkpoint,
|
||
|
|
backbone=dict(
|
||
|
|
type='VisionTransformer',
|
||
|
|
img_size=(640, 640),
|
||
|
|
embed_dims=1024,
|
||
|
|
num_layers=24,
|
||
|
|
num_heads=16),
|
||
|
|
decode_head=dict(
|
||
|
|
type='SegmenterMaskTransformerHead',
|
||
|
|
in_channels=1024,
|
||
|
|
channels=1024,
|
||
|
|
num_heads=16,
|
||
|
|
embed_dims=1024),
|
||
|
|
test_cfg=dict(mode='slide', crop_size=(640, 640), stride=(608, 608)))
|
||
|
|
|
||
|
|
optimizer = dict(lr=0.001, weight_decay=0.0)
|
||
|
optim_wrapper = dict(type='OptimWrapper', optimizer=optimizer)
|
||
|
train_dataloader = dict(
|
||
|
|
# num_gpus: 8 -> batch_size: 8
|
||
|
|
batch_size=1)
|
||
|
|
val_dataloader = dict(batch_size=1)
|