can you tell me the mean of decode_head and auxiliary_head? about mmsegmentation

[xvjiarui]

Hi @zhujiesuper
decode_head is for decoding semantic segmentation output.
auxiliary_head is just adding an auxiliary loss.

[zhujiesuper]

thank you! but if all the model need auxiliary_head? i find it in all model,but in papers do not all have ,i know pspnet have an auxiliary loss,but others do not have,can you tell me how to handle this

[xvjiarui]

Hi @zhujiesuper
For fair comparison, we use auxiliary loss for all methods.
Note that, there are many implementation details in our repo that differ from the official repo.

[baibaidj]

thank you! but if all the model need auxiliary_head? i find it in all model,but in papers do not all have ,i know pspnet have an auxiliary loss,but others do not have,can you tell me how to handle this

The auxilliary_head is modular and optional, which means that you can remove it if you don't want it.

model = dict(
type='EncoderDecoder', # tells registery to use which module to build this model
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=(1, 2, 1, 1),
norm_cfg=norm_cfg,
norm_eval=False,
style='pytorch',
contract_dilation=True),
decode_head=dict(
type='PSPHead', # type can be seen as the surrogates for python classes to call from
in_channels=2048,
in_index=3,
channels=512,
pool_scales=(1, 2, 3, 6),
dropout_ratio=0.1,
num_classes=19,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
auxiliary_head=dict(
type='FCNHead',
in_channels=1024,
in_index=2,
channels=256,
num_convs=1,
concat_input=False,
dropout_ratio=0.1,
num_classes=19,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4))
)

For the config of PSPNet as shown above, you just need to remove all the content of auxiliary_head variable. Then the model won't compute the auxiliary loss any more.

[zhujiesuper]

does it mean i delete

auxiliary_head=dict(
type='FCNHead',
in_channels=1024,
in_index=2,
channels=256,
num_convs=1,
concat_input=False,
dropout_ratio=0.1,
num_classes=19,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4))
)

and it work?

[xvjiarui]

Hi @zhujiesuper
Yes. Deleting auxilary_head in cfg will remove auxiliary head in the model.