- class mmcls.models.TIMMBackbone(model_name, features_only=False, pretrained=False, checkpoint_path='', in_channels=3, init_cfg=None, **kwargs)¶
Wrapper to use backbones from timm library.
model_name (str) – Name of timm model to instantiate.
features_only (bool) – Whether to extract feature pyramid (multi-scale feature maps from the deepest layer at each stride). For Vision Transformer models that do not support this argument, set this False. Defaults to False.
pretrained (bool) – Whether to load pretrained weights. Defaults to False.
checkpoint_path (str) – Path of checkpoint to load at the last of
timm.create_model. Defaults to empty string, which means not loading.
in_channels (int) – Number of input image channels. Defaults to 3.
**kwargs – Other timm & model specific arguments.