cspdarknet53#

holocron.models.cspdarknet53(pretrained: bool = False, checkpoint: Checkpoint | None = None, progress: bool = True, **kwargs: Any) → DarknetV4[source]#

CSP-Darknet-53 from “CSPNet: A New Backbone that can Enhance Learning Capability of CNN”

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 _darknet

Returns:

classification model

Return type:

torch.nn.Module

class holocron.models.CSPDarknet53_Checkpoint(value)[source]#

The model builder above accepts the following values as the checkpoint parameter. CSPDarknet53_Checkpoint.DEFAULT is equivalent to CSPDarknet53_Checkpoint.IMAGENETTE

CSPDarknet53_Checkpoint.IMAGENETTE:

Also available as CSPDarknet53_Checkpoint.DEFAULT.

dataset	imagenette
top1-accuracy	0.945
top5-accuracy	0.9964
url	link
sha256	7a69463a4bd445be
size	101.8MB
num_params	26.6M
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