bob.ip.binseg.models.backbones.resnet¶
Functions
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ResNet-50 model from “Deep Residual Learning for Image Recognition” |
Classes
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Adaptation of base ResNet functionality to U-Net style segmentation |
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class
bob.ip.binseg.models.backbones.resnet.ResNet4Segmentation(*args, **kwargs)[source]¶ Bases:
torchvision.models.resnet.ResNetAdaptation of base ResNet functionality to U-Net style segmentation
This version of ResNet is slightly modified so it can be used through torchvision’s API. It outputs intermediate features which are normally not output by the base ResNet implementation, but are required for segmentation operations.
- Parameters
return_features (
list, Optional) – A list of integers indicating the feature layers to be returned from the original module.
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forward(x)[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Moduleinstance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
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bob.ip.binseg.models.backbones.resnet.resnet50_for_segmentation(pretrained=False, progress=True, **kwargs)[source]¶ ResNet-50 model from “Deep Residual Learning for Image Recognition”