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---
tags:
- huggan
- gan
datasets:
- huggan/maps
# See a list of available tags here:
# https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts#L12
# task: unconditional-image-generation or conditional-image-generation or image-to-image
license: mit
---
# Pix2Pix trained on the maps dataset
## Model description
This model is a [Pix2Pix](https://arxiv.org/abs/1611.07004) model trained on the [huggan/maps](https://huggingface.co/datasets/huggan/maps) dataset. The goal for the model is to turn a satellite map into a geographic map à la Google Maps, and the other way around.
The model was trained using the [example script](https://github.com/huggingface/community-events/tree/main/huggan/pytorch/pix2pix) provided by HuggingFace as part of the [HugGAN sprint](https://github.com/huggingface/community-events/tree/main/huggan).
## Intended uses & limitations
#### How to use
```python
from huggan.pytorch.pix2pix.modeling_pix2pix import GeneratorUNet
from PIL import Image
from torchvision.utils import save_image
image = Image.open("...")
generator = GeneratorUNet.from_pretrained("huggan/pix2pix-maps")
pixel_values = transform(image).unsqueeze(0)
output = generator(pixel_values)
save_image(output, 'output.png', normalize=True)
```
#### Limitations and bias
Provide examples of latent issues and potential remediations.
## Training data
The data used was huggan/maps.
## Training procedure
The following command was used:
```bash
accelerate launch train.py --dataset huggan/maps --push_to_hub --model_name pix2pix-maps --checkpoint_interval 1
```
## Eval results
## Generated Images
You can embed local or remote images using ``
### BibTeX entry and citation info
```bibtex
@article{DBLP:journals/corr/IsolaZZE16,
author = {Phillip Isola and
Jun{-}Yan Zhu and
Tinghui Zhou and
Alexei A. Efros},
title = {Image-to-Image Translation with Conditional Adversarial Networks},
journal = {CoRR},
volume = {abs/1611.07004},
year = {2016},
url = {http://arxiv.org/abs/1611.07004},
eprinttype = {arXiv},
eprint = {1611.07004},
timestamp = {Mon, 13 Aug 2018 16:49:05 +0200},
biburl = {https://dblp.org/rec/journals/corr/IsolaZZE16.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
``` |