res2net50_26w_4s#

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

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)[source]#

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