| --- |
| license: apache-2.0 |
| library_name: diffusers |
| pipeline_tag: text-to-image |
| widget: |
| - text: city neighborhood |
| output: |
| url: 7d3aebe3-a08d-4a31-b5ac-06408e0c835a.jpeg |
| - text: resort in hawaii |
| output: |
| url: a983aca6-9deb-41f5-8e8a-b7932cc83ff4.jpeg |
| - text: factory |
| output: |
| url: be2fb507-af99-4258-a90f-c0df2bbab3ce.jpeg |
| - text: university campus |
| output: |
| url: 12bbc23c-850a-484b-99a6-478c19417993.jpeg |
| --- |
| |
| # Model Card for Model ID |
|
|
| <!-- Provide a quick summary of what the model is/does. --> |
| This is a StableDiffusion based model that synthesizes satellite images given text prompts. 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 [stablediffusion](https://github.com/Stability-AI/stablediffusion) repository |
| |
| ### Model Sources [optional] |
| |
| <!-- Provide the basic links for the model. --> |
| |
| - **Repository:** [stable-diffusion](https://huggingface.co/stabilityai/stable-diffusion-2-1-base) |
| |
| ## Examples |
| |
| ```python |
| from diffusers import StableDiffusionPipeline |
| |
| pipe = StableDiffusionPipeline.from_pretrained("MVRL/GeoSynth") |
| pipe = pipe.to("cuda:0") |
|
|
| image = pipe( |
| "Satellite image features a city neighborhood", |
| ).images[0] |
| |
| image.save("generated_city.jpg") |
| ``` |
