resnet50

holocron.models.resnet50(pretrained: bool = False, checkpoint: Checkpoint | None = None, progress: bool = True, **kwargs: Any) → ResNet

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

Parameters:

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

• checkpoint – If specified, load that checkpoint on the model

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

• kwargs – keyword args of _resnet

Returns:

classification model

Return type:

torch.nn.Module

class holocron.models.ResNet50_Checkpoint(value)

The model builder above accepts the following values as the checkpoint parameter. ResNet50_Checkpoint.DEFAULT is equivalent to ResNet50_Checkpoint.IMAGENETTE

ResNet50_Checkpoint.IMAGENETTE:

Also available as ResNet50_Checkpoint.DEFAULT.

dataset	imagenette
top1-accuracy	0.9378
top5-accuracy	0.9954
url	link
sha256	5b913f0b8148b483
size	90.0MB
num_params	23.5M
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