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Backbone

A backbone is a model used for feature extraction for higher level computer vision tasks such as object detection and image classification. Transformers provides an [AutoBackbone] class for initializing a Transformers backbone from pretrained model weights, and two utility classes:

• [~backbone_utils.BackboneMixin] enables initializing a backbone from Transformers or timm and includes functions for returning the output features and indices.
• [~backbone_utils.BackboneConfigMixin] sets the output features and indices of the backbone configuration.

timm models are loaded with the [TimmBackbone] and [TimmBackboneConfig] classes.

Backbones are supported for the following models:

• BEiT
• BiT
• ConvNext
• ConvNextV2
• DiNAT
• DINOV2
• FocalNet
• MaskFormer
• NAT
• ResNet
• Swin Transformer
• Swin Transformer v2
• ViTDet

AutoBackbone

[[autodoc]] AutoBackbone

BackboneMixin

[[autodoc]] backbone_utils.BackboneMixin

BackboneConfigMixin

[[autodoc]] backbone_utils.BackboneConfigMixin

TimmBackbone

[[autodoc]] models.timm_backbone.TimmBackbone

TimmBackboneConfig

[[autodoc]] models.timm_backbone.TimmBackboneConfig