inception-v3

Inception v3

Szegedy et al., 2015 — Rethinking the Inception Architecture for Computer Vision (arXiv:1512.00567)

Lucid port of torchvision/Inception_V3_Weights.IMAGENET1K_V1, converted to Lucid-native safetensors.

Available weights

Usage

import lucid.models as models
from lucid.models.weights import InceptionV3Weights

# default tag
model = models.inception_v3_cls(pretrained=True)

# explicit tag (enum or string)
model = models.inception_v3_cls(weights=InceptionV3Weights.IMAGENET1K_V1)
model = models.inception_v3_cls(pretrained="IMAGENET1K_V1")

# preprocessing travels with the weights
weights = InceptionV3Weights.IMAGENET1K_V1
preprocess = weights.transforms()
logits = model(preprocess(image)[None]).logits

Conversion

Converted from torchvision/Inception_V3_Weights.IMAGENET1K_V1 via python -m tools.convert_weights inception_v3 --tag IMAGENET1K_V1. Key mapping + numerical parity verified against the source.

License

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

Citation

@inproceedings{szegedy2016rethinking,
  title={Rethinking the Inception Architecture for Computer Vision},
  author={Szegedy, Christian and Vanhoucke, Vincent and Ioffe, Sergey and Shlens, Jon and Wojna, Zbigniew},
  booktitle={CVPR}, year={2016}
}