PLONK_YFCC / README.md
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---
license: mit
tags:
- model_hub_mixin
- plonk
- geolocalization
- diffusion
- pytorch_model_hub_mixin
- yfcc
---
This is a model of the approach described in the paper ["Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation"](https://arxiv.org/abs/2412.06781)
```
@misc{dufour2024world80timestepsgenerative,
title={Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation},
author={Nicolas Dufour and David Picard and Vicky Kalogeiton and Loic Landrieu},
year={2024},
eprint={2412.06781},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2412.06781},
}
```
- Code: https://github.com/nicolas-dufour/plonk
- Docs:
The model can be simply run by doing:
```bash
pip install diff-plonk
```
```python
from plonk import PLONKPipeline
pipeline = PLONKPipeline.from_pretrained("nicolas-dufour/PLONK_YFCC")
gps_coords = pipeline(images, batch_size=1024)
```