metadata
library_name: lucid
license: bsd-3-clause
tags:
- image-classification
- inception
- lucid
datasets:
- imagenet-1k
pipeline_tag: image-classification
model-index:
- name: inception-v3
results:
- task:
type: image-classification
dataset:
name: ImageNet-1K
type: imagenet-1k
metrics:
- type: acc@1
value: 77.294
- type: acc@5
value: 93.45
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
| Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
|---|---|---|---|---|---|---|
IMAGENET1K_V1 (default) |
77.294 | 93.45 | 23.8M | 5.713 | 91.11 MB | torchvision |
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}
}