res2net50_26w_4s

holocron.models.res2net50_26w_4s(pretrained: bool = False, checkpoint: Checkpoint | None = None, progress: bool = True, **kwargs: Any) → ResNet

Res2Net-50 26wx4s from “Res2Net: A New Multi-scale Backbone Architecture”

Parameters:

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

• checkpoint – If specified, the model’s parameters will be set to the checkpoint’s values

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

• kwargs – keyword args of _res2net

Returns:

classification model

Return type:

torch.nn.Module

class holocron.models.Res2Net50_26w_4s_Checkpoint(value)

The model builder above accepts the following values as the checkpoint parameter. Res2Net50_26w_4s_Checkpoint.DEFAULT is equivalent to Res2Net50_26w_4s_Checkpoint.IMAGENETTE

Res2Net50_26w_4s_Checkpoint.IMAGENETTE:

Also available as Res2Net50_26w_4s_Checkpoint.DEFAULT.

dataset	imagenette
top1-accuracy	0.9394
top5-accuracy	0.9941
url	link
sha256	345170e8ff75d103
size	90.6MB
num_params	23.7M
categories	tench, English springer, cassette player, … (7 omitted)
input_shape	(3, 224, 224)
mean	(0.485, 0.456, 0.406)
std	(0.229, 0.224, 0.225)
interpolation	InterpolationMode.BILINEAR
commit	6e32c5b