Instructions to use yisol/IDM-VTON with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yisol/IDM-VTON 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("yisol/IDM-VTON", 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
Using a VTON model for real time production purpose
I am searching a way, in which I can use the VTON model inside an app for real-time production purpose. I came to know that to do this, I have to pre-process my images with model image, cloth image, segmentation masks, pose estimation key points etc. However, the client wants if I can use any pre-trained model on my images and test the result on 10 images.
How can I do that without any UIs like ComfyUI or Stable Diffusion WebUI. I am not finding any concrete source of creating this model in my local system. I have tried to use Pose estimation + key points detection + Grounded SAM + Thin Plate Spline algorithm to achive the result. But, I am not successful in this yet.
Any advice/code/reference you can provide or suggest will help me a lot