---
library_name: lucid
license: apache-2.0
tags:
  - image-classification
  - xception
  - lucid
datasets:
  - imagenet-1k
pipeline_tag: image-classification
model-index:
  - name: xception
    results:
      - task: { type: image-classification }
        dataset: { name: ImageNet-1k, type: imagenet-1k }
        metrics:
          - { type: acc@1, value: 79.0 }
---

# Xception

> Chollet, 2017 — *Xception: Deep Learning with Depthwise Separable Convolutions* (arXiv:1610.02357)

[Lucid](https://github.com/ChanLumerico/lucid) port of `timm/legacy_xception.tf_in1k`,
converted to Lucid-native safetensors.

## Available weights

| Tag | acc@1 | acc@5 | Params | GFLOPs | Size | Source |
|---|---|---|---|---|---|---|
| `TF_IN1K` *(default)* | 79.0 | — | 22.9M | — | 87.42 MB | timm |

## Usage

```python
import lucid.models as models
from lucid.models.weights import XceptionWeights

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

# explicit tag (enum or string)
model = models.xception_cls(weights=XceptionWeights.TF_IN1K)
model = models.xception_cls(pretrained="TF_IN1K")

# preprocessing travels with the weights
weights = XceptionWeights.TF_IN1K
preprocess = weights.transforms()
logits = model(preprocess(image)[None]).logits
```

## Conversion

Converted from `timm/legacy_xception.tf_in1k` via
`python -m tools.convert_weights xception --tag TF_IN1K`.
Key mapping + numerical parity verified against the source.

## License

`apache-2.0` — inherited from the original weights.

## Citation

```
@inproceedings{chollet2017xception,
  title={Xception: Deep Learning with Depthwise Separable Convolutions},
  author={Chollet, Fran\c{c}ois},
  booktitle={CVPR}, year={2017}
}
```