This model has been pushed to the Hub using the PytorchModelHubMixin integration.

Library: nobg

Blog : feynobg blogpost HF blogpost

how to use the model

pip install nobg>=0.2.5

import torch
from loadimg import load_img
from nobg import AutoModel, AutoProcessor

model = AutoModel.from_pretrained("feyninc/FeyNobg").eval()
processor = AutoProcessor.from_pretrained("feyninc/FeyNobg")

image = load_img("input.jpg").convert("RGB")
inputs = processor(image, return_tensors="pt")

with torch.no_grad():
    outputs = model(pixel_values=inputs["pixel_values"])

alpha = processor.post_process_alpha_matting(
    outputs, target_sizes=[(image.height, image.width)]
)[0]
processor.cutout(image, alpha).save("output.png")

Citation

If you use this model, please cite:

@article{zheng2024birefnet,
  title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
  author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
  journal={CAAI Artificial Intelligence Research},
  volume={3},
  pages={9150038},
  year={2024},
  url={https://arxiv.org/abs/2401.03407},
}

Contributions

Any contributions are welcome at https://github.com/feyninc/nobg