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--- |
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license: apache-2.0 |
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tags: |
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- controlnet |
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- stable-diffusion |
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- satellite-imagery |
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- osm |
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- image-to-image |
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- diffusers |
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base_model: stabilityai/stable-diffusion-2-1-base |
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pipeline_tag: image-to-image |
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library_name: diffusers |
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--- |
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# VectorSynth |
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**VectorSynth** is a ControlNet model that generates satellite imagery from OpenStreetMap (OSM) vector data embeddings. It conditions [Stable Diffusion 2.1 Base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) on rendered OSM text to synthesize realistic aerial imagery. |
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## Model Description |
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VectorSynth uses a two-stage pipeline: |
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1. **RenderEncoder**: Projects 768-dim CLIP text embeddings of OSM text to 3-channel control images |
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2. **ControlNet**: Conditions Stable Diffusion 2.1 on the rendered control images |
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This model uses standard CLIP embeddings. For the COSA embedding variant, see [VectorSynth-COSA](https://huggingface.co/MVRL/VectorSynth-COSA). |
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## Files |
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- `config.json` - ControlNet configuration |
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- `diffusion_pytorch_model.safetensors` - ControlNet weights |
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- `render_encoder/clip-render_encoder.pth` - RenderEncoder weights |
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- `render.py` - RenderEncoder class definition |
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## Citation |
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```bibtex |
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@inproceedings{cher2025vectorsynth, |
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title={VectorSynth: Fine-Grained Satellite Image Synthesis with Structured Semantics}, |
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author={Cher, Daniel and Wei, Brian and Sastry, Srikumar and Jacobs, Nathan}, |
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year={2025}, |
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eprint={arXiv:2511.07744}, |
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note={arXiv preprint} |
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} |
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``` |
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## Related Models |
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- [VectorSynth-COSA](https://huggingface.co/MVRL/VectorSynth-COSA) - COSA embedding variant |
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- [GeoSynth](https://huggingface.co/MVRL/GeoSynth) - Text-to-satellite image generation |
