Instructions to use hvbrt/GeoSynth-OSM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hvbrt/GeoSynth-OSM with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("hvbrt/GeoSynth-OSM") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
| library_name: diffusers | |
| base_model: stabilityai/stable-diffusion-2-1-base | |
| license: apache-2.0 | |
| widget: | |
| - src: osm_tile_18_42048_101323.jpeg | |
| prompt: Satellite image features a city neighborhood | |
| tags: | |
| - controlnet | |
| - stable-diffusion | |
| - satellite-imagery | |
| - OSM | |
| pipeline_tag: image-to-image | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| This is a ControlNet based model that synthesizes satellite images given OpenStreetMap Images. The base stable diffusion model used is [stable-diffusion-2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) (v2-1_512-ema-pruned.ckpt). | |
| * Use it with 🧨 [diffusers](#examples) | |
| * Use it with [controlnet](https://github.com/lllyasviel/ControlNet/tree/main?tab=readme-ov-file) repository | |
| ### Model Sources [optional] | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** [stable-diffusion](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) | |
| - **Paper:** [Adding Conditional Control to Text-to-Image Diffusion Models](https://arxiv.org/abs/2302.05543) | |
| ## Examples | |
| ```python | |
| from diffusers import StableDiffusionControlNetPipeline, ControlNetModel | |
| import torch | |
| from PIL import Image | |
| img = Image.open("osm_tile_18_42048_101323.jpeg") | |
| controlnet = ControlNetModel.from_pretrained("MVRL/GeoSynth-OSM") | |
| pipe = StableDiffusionControlNetPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", controlnet=controlnet) | |
| pipe = pipe.to("cuda:0") | |
| # generate image | |
| generator = torch.manual_seed(10345340) | |
| image = pipe( | |
| "Satellite image features a city neighborhood", | |
| generator=generator, | |
| image=img, | |
| ).images[0] | |
| image.save("generated_city.jpg") | |
| ``` | |
| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> | |
| ## Citation [optional] | |
| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> | |
| **BibTeX:** | |
| [More Information Needed] | |
| **APA:** | |
| [More Information Needed] | |
| ## More Information [optional] | |
| [More Information Needed] | |
| ## Model Card Authors [optional] | |
| [More Information Needed] | |
| ## Model Card Contact | |
| [More Information Needed] |