bob.ip.binseg.models.backbones.resnet

Functions

resnet50_for_segmentation([pretrained, progress])

ResNet-50 model from "Deep Residual Learning for Image Recognition".

Classes

ResNet4Segmentation(*args, **kwargs)

Adaptation of base ResNet functionality to U-Net style segmentation

class bob.ip.binseg.models.backbones.resnet.ResNet4Segmentation(*args, **kwargs)

Bases: torchvision.models.resnet.ResNet

Adaptation 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.

forward(x)

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 Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

training: bool

bob.ip.binseg.models.backbones.resnet.resnet50_for_segmentation(pretrained=False, progress=True, **kwargs)

ResNet-50 model from “Deep Residual Learning for Image Recognition”.

Parameters

• pretrained (bool) – If True, returns a model pre-trained on ImageNet

• progress (bool) – If True, displays a progress bar of the download to stderr