File size: 2,196 Bytes
b13b124 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
# model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
type='CascadeEncoderDecoder',
num_stages=2,
pretrained='open-mmlab://msra/hrnetv2_w18',
backbone=dict(
type='HRNet',
norm_cfg=norm_cfg,
norm_eval=False,
extra=dict(
stage1=dict(
num_modules=1,
num_branches=1,
block='BOTTLENECK',
num_blocks=(4, ),
num_channels=(64, )),
stage2=dict(
num_modules=1,
num_branches=2,
block='BASIC',
num_blocks=(4, 4),
num_channels=(18, 36)),
stage3=dict(
num_modules=4,
num_branches=3,
block='BASIC',
num_blocks=(4, 4, 4),
num_channels=(18, 36, 72)),
stage4=dict(
num_modules=3,
num_branches=4,
block='BASIC',
num_blocks=(4, 4, 4, 4),
num_channels=(18, 36, 72, 144)))),
decode_head=[
dict(
type='FCNHead',
in_channels=[18, 36, 72, 144],
channels=sum([18, 36, 72, 144]),
in_index=(0, 1, 2, 3),
input_transform='resize_concat',
kernel_size=1,
num_convs=1,
concat_input=False,
dropout_ratio=-1,
num_classes=19,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
dict(
type='OCRHead',
in_channels=[18, 36, 72, 144],
in_index=(0, 1, 2, 3),
input_transform='resize_concat',
channels=512,
ocr_channels=256,
dropout_ratio=-1,
num_classes=19,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
],
# model training and testing settings
train_cfg=dict(),
test_cfg=dict(mode='whole'))
|