Views
No views yet
Wang et al., 2020 — CSPNet: A New Backbone that can Enhance Learning Capability of CNN (arXiv:1911.11929)
timm/cspresnet50.ra_in1k,
converted to Lucid-native safetensors.| Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
|---|---|---|---|---|---|---|
RA_IN1K (default) | 76.74 | — | 21.6M | — | 82.65 MB | timm |
1import lucid.models as models
2from lucid.models.weights import CSPResNet50Weights
3
4# default tag
5model = models.cspresnet_50_cls(pretrained=True)
6
7# explicit tag (enum or string)
8model = models.cspresnet_50_cls(weights=CSPResNet50Weights.RA_IN1K)
9model = models.cspresnet_50_cls(pretrained="RA_IN1K")
10
11# preprocessing travels with the weights
12weights = CSPResNet50Weights.RA_IN1K
13preprocess = weights.transforms()
14logits = model(preprocess(image)[None]).logitstimm/cspresnet50.ra_in1k via
python -m tools.convert_weights cspresnet_50 --tag RA_IN1K.
Key mapping + numerical parity verified against the source.apache-2.0 — inherited from the original weights.@inproceedings{wang2020cspnet,
title={CSPNet: A New Backbone that can Enhance Learning Capability of CNN},
author={Wang, Chien-Yao and Liao, Hong-Yuan Mark and Wu, Yueh-Hua and Chen, Ping-Yang and Hsieh, Jun-Wei and Yeh, I-Hau},
booktitle={CVPR Workshops}, year={2020}
}