Image Segmentation
BEN2
ONNX
Safetensors
PyTorch
BEN2
background-remove
mask-generation
Dichotomous image segmentation
background remove
foreground
background
remove background
model_hub_mixin
pytorch_model_hub_mixin
background removal
background-removal
Instructions to use PramaLLC/BEN2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BEN2
How to use PramaLLC/BEN2 with BEN2:
import requests from PIL import Image from ben2 import AutoModel url = "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg" image = Image.open(requests.get(url, stream=True).raw) model = AutoModel.from_pretrained("PramaLLC/BEN2") model.to("cuda").eval() foreground = model.inference(image) - Notebooks
- Google Colab
- Kaggle
integrate with huggingface
#3
by not-lain - opened
This pr will add the necessary metadata to your repository
you can test these changes before merging using the following code
pip install -e "git+https://github.com/PramaLLC/BEN2.git#egg=ben2"
(if you're in colab or a jupyter notebook you need to restart your runtime)
from ben2 import BEN_Base
model = BEN_Base.from_pretrained("PramaLLC/BEN2", revision="refs/pr/3") # revision is used to load from a pull request or a previous commit
I also updated your readme file to include the latest changes.
MaxwellMeyer changed pull request status to merged
Hi, thank you! We were in the process of adding the safe tensors. We really appreciate your help.
Any plans on adding onnx?
@jtsanborn there's an ONNX variant under https://huggingface.co/onnx-community/BEN2-ONNX
Kudos to Xenova for his awesome work π