DenseNet-201

Huang et al., 2017 — Densely Connected Convolutional Networks (arXiv:1608.06993)

Lucid port of torchvision/DenseNet201_Weights.IMAGENET1K_V1, converted to Lucid-native safetensors.

Available weights

Tag	acc@1	acc@5	Params	GFLOPs	Size	Source
IMAGENET1K_V1 (default)	76.896	93.37	20.0M	4.291	77.37 MB	torchvision

Usage

import lucid.models as models
from lucid.models.weights import DenseNet201Weights

# default tag
model = models.densenet_201_cls(pretrained=True)

# explicit tag (enum or string)
model = models.densenet_201_cls(weights=DenseNet201Weights.IMAGENET1K_V1)
model = models.densenet_201_cls(pretrained="IMAGENET1K_V1")

# preprocessing travels with the weights
weights = DenseNet201Weights.IMAGENET1K_V1
preprocess = weights.transforms()
logits = model(preprocess(image)[None]).logits

Conversion

Converted from torchvision/DenseNet201_Weights.IMAGENET1K_V1 via python -m tools.convert_weights densenet_201 --tag IMAGENET1K_V1. Key mapping + numerical parity verified against the source.

License

bsd-3-clause — inherited from the original weights.

Citation

@inproceedings{huang2017densely,
  title={Densely Connected Convolutional Networks},
  author={Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and Weinberger, Kilian Q.},
  booktitle={CVPR}, year={2017}
}