Instructions to use RyanHangZhou/PICS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RyanHangZhou/PICS with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RyanHangZhou/PICS", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| datasets: | |
| - Heatmob-Research/VITON-HD | |
| - Voxel51/LVIS | |
| - jxu124/objects365 | |
| - Oursel/cityscapes | |
| - paidaixing/Image_mapillary_Street_level | |
| - dgural/bdd100k | |
| language: | |
| - en | |
| pipeline_tag: image-to-image | |
| library_name: diffusers | |
| tags: | |
| - art | |
| # PICS: Pairwise Image Compositing with Spatial Interactions | |
| <table align="center"> | |
| <tr> | |
| <td align="center"> | |
| <img src="https://github.com/RyanHangZhou/PICS/raw/main/assets/figure.jpg" alt="PICS Teaser" width="100%"> | |
| </td> | |
| </tr> | |
| </table> | |
| [Project page](https://ryanhangzhou.github.io/pics/) | [Paper](https://openreview.net/pdf?id=zNCNEOhKps) | |