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README.md
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---
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library_name: lucid
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license: apache-2.0
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tags:
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- image-classification
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- xception
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- lucid
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datasets:
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- imagenet-1k
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pipeline_tag: image-classification
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model-index:
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- name: xception
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results:
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- task: { type: image-classification }
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dataset: { name: ImageNet-1k, type: imagenet-1k }
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metrics:
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- { type: acc@1, value: 79.0 }
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---
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# Xception
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> Chollet, 2017 — *Xception: Deep Learning with Depthwise Separable Convolutions* (arXiv:1610.02357)
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[Lucid](https://github.com/ChanLumerico/lucid) port of `timm/legacy_xception.tf_in1k`,
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converted to Lucid-native safetensors.
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## Available weights
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| Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
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|---|---|---|---|---|---|---|
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| `TF_IN1K` *(default)* | 79.0 | — | 22.9M | — | 87.42 MB | timm |
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## Usage
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```python
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import lucid.models as models
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from lucid.models.vision.resnet import XceptionWeights
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# default tag
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model = models.xception_cls(pretrained=True)
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# explicit tag (enum or string)
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model = models.xception_cls(weights=XceptionWeights.TF_IN1K)
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model = models.xception_cls(pretrained="TF_IN1K")
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# preprocessing travels with the weights
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weights = XceptionWeights.TF_IN1K
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preprocess = weights.transforms()
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logits = model(preprocess(image)[None]).logits
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```
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## Conversion
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Converted from `timm/legacy_xception.tf_in1k` via
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`python -m tools.convert_weights xception --tag TF_IN1K`.
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Key mapping + numerical parity verified against the source.
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## License
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`apache-2.0` — inherited from the original weights.
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## Citation
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```
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@inproceedings{chollet2017xception,
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title={Xception: Deep Learning with Depthwise Separable Convolutions},
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author={Chollet, Fran\c{c}ois},
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booktitle={CVPR}, year={2017}
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}
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```
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