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Temporarily use IntermediateLayerGetter on segmentation #5298

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Merged
merged 2 commits into from
Jan 27, 2022
Merged

Temporarily use IntermediateLayerGetter on segmentation #5298

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160e564
Add IntermediateLayerGetter on segmentation.
datumbox Jan 27, 2022
ef7c337
Merge branch 'main' into segmentation/intermedia_layer
datumbox Jan 27, 2022
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6 changes: 3 additions & 3 deletions torchvision/models/segmentation/deeplabv3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@

from .. import mobilenetv3
from .. import resnet
from ..feature_extraction import create_feature_extractor
from .._utils import IntermediateLayerGetter
from ._utils import _SimpleSegmentationModel, _load_weights
from .fcn import FCNHead

Expand Down Expand Up @@ -121,7 +121,7 @@ def _deeplabv3_resnet(
return_layers = {"layer4": "out"}
if aux:
return_layers["layer3"] = "aux"
backbone = create_feature_extractor(backbone, return_layers)
backbone = IntermediateLayerGetter(backbone, return_layers=return_layers)

aux_classifier = FCNHead(1024, num_classes) if aux else None
classifier = DeepLabHead(2048, num_classes)
Expand All @@ -144,7 +144,7 @@ def _deeplabv3_mobilenetv3(
return_layers = {str(out_pos): "out"}
if aux:
return_layers[str(aux_pos)] = "aux"
backbone = create_feature_extractor(backbone, return_layers)
backbone = IntermediateLayerGetter(backbone, return_layers=return_layers)

aux_classifier = FCNHead(aux_inplanes, num_classes) if aux else None
classifier = DeepLabHead(out_inplanes, num_classes)
Expand Down
4 changes: 2 additions & 2 deletions torchvision/models/segmentation/fcn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
from torch import nn

from .. import resnet
from ..feature_extraction import create_feature_extractor
from .._utils import IntermediateLayerGetter
from ._utils import _SimpleSegmentationModel, _load_weights


Expand Down Expand Up @@ -57,7 +57,7 @@ def _fcn_resnet(
return_layers = {"layer4": "out"}
if aux:
return_layers["layer3"] = "aux"
backbone = create_feature_extractor(backbone, return_layers)
backbone = IntermediateLayerGetter(backbone, return_layers=return_layers)

aux_classifier = FCNHead(1024, num_classes) if aux else None
classifier = FCNHead(2048, num_classes)
Expand Down
4 changes: 2 additions & 2 deletions torchvision/models/segmentation/lraspp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@

from ...utils import _log_api_usage_once
from .. import mobilenetv3
from ..feature_extraction import create_feature_extractor
from .._utils import IntermediateLayerGetter
from ._utils import _load_weights


Expand Down Expand Up @@ -90,7 +90,7 @@ def _lraspp_mobilenetv3(backbone: mobilenetv3.MobileNetV3, num_classes: int) ->
high_pos = stage_indices[-1] # use C5 which has output_stride = 16
low_channels = backbone[low_pos].out_channels
high_channels = backbone[high_pos].out_channels
backbone = create_feature_extractor(backbone, {str(low_pos): "low", str(high_pos): "high"})
backbone = IntermediateLayerGetter(backbone, return_layers={str(low_pos): "low", str(high_pos): "high"})

return LRASPP(backbone, low_channels, high_channels, num_classes)

Expand Down