40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
_base_ = './ocrnet_hr18_512x1024_80k_cityscapes.py'
|
|
norm_cfg = dict(type='SyncBN', requires_grad=True)
|
|
model = dict(
|
|
pretrained='open-mmlab://msra/hrnetv2_w48',
|
|
backbone=dict(
|
|
extra=dict(
|
|
stage2=dict(num_channels=(48, 96)),
|
|
stage3=dict(num_channels=(48, 96, 192)),
|
|
stage4=dict(num_channels=(48, 96, 192, 384)))),
|
|
decode_head=[
|
|
dict(
|
|
type='FCNHead',
|
|
in_channels=[48, 96, 192, 384],
|
|
channels=sum([48, 96, 192, 384]),
|
|
input_transform='resize_concat',
|
|
in_index=(0, 1, 2, 3),
|
|
kernel_size=1,
|
|
num_convs=1,
|
|
norm_cfg=norm_cfg,
|
|
concat_input=False,
|
|
dropout_ratio=-1,
|
|
num_classes=19,
|
|
align_corners=False,
|
|
loss_decode=dict(
|
|
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
|
|
dict(
|
|
type='OCRHead',
|
|
in_channels=[48, 96, 192, 384],
|
|
channels=512,
|
|
ocr_channels=256,
|
|
input_transform='resize_concat',
|
|
in_index=(0, 1, 2, 3),
|
|
norm_cfg=norm_cfg,
|
|
dropout_ratio=-1,
|
|
num_classes=19,
|
|
align_corners=False,
|
|
loss_decode=dict(
|
|
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
|
|
])
|