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# model settings | |
norm_cfg = dict(type='SyncBN', eps=1e-03, requires_grad=True) | |
data_preprocessor = dict( | |
type='SegDataPreProcessor', | |
mean=[72.39239876, 82.90891754, 73.15835921], | |
std=[1, 1, 1], | |
bgr_to_rgb=True, | |
pad_val=0, | |
seg_pad_val=255) | |
model = dict( | |
type='EncoderDecoder', | |
data_preprocessor=data_preprocessor, | |
backbone=dict( | |
type='CGNet', | |
norm_cfg=norm_cfg, | |
in_channels=3, | |
num_channels=(32, 64, 128), | |
num_blocks=(3, 21), | |
dilations=(2, 4), | |
reductions=(8, 16)), | |
decode_head=dict( | |
type='FCNHead', | |
in_channels=256, | |
in_index=2, | |
channels=256, | |
num_convs=0, | |
concat_input=False, | |
dropout_ratio=0, | |
num_classes=19, | |
norm_cfg=norm_cfg, | |
loss_decode=dict( | |
type='CrossEntropyLoss', | |
use_sigmoid=False, | |
loss_weight=1.0, | |
class_weight=[ | |
2.5959933, 6.7415504, 3.5354059, 9.8663225, 9.690899, 9.369352, | |
10.289121, 9.953208, 4.3097677, 9.490387, 7.674431, 9.396905, | |
10.347791, 6.3927646, 10.226669, 10.241062, 10.280587, | |
10.396974, 10.055647 | |
])), | |
# model training and testing settings | |
train_cfg=dict(sampler=None), | |
test_cfg=dict(mode='whole')) | |