Image Segmentation
BiRefNet
Safetensors
Transformers
background-removal
mask-generation
Dichotomous Image Segmentation
Camouflaged Object Detection
Salient Object Detection
pytorch_model_hub_mixin
model_hub_mixin
custom_code
Instructions to use ZhengPeng7/BiRefNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use ZhengPeng7/BiRefNet with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet", trust_remote_code=True)# Option 2: use with BiRefNet # Install from https://github.com/ZhengPeng7/BiRefNet from models.birefnet import BiRefNet model = BiRefNet.from_pretrained("ZhengPeng7/BiRefNet") - Transformers
How to use ZhengPeng7/BiRefNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ZhengPeng7/BiRefNet", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update the citation to the complete version.
Browse files
README.md
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## Citation
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```
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@article{
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title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
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author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
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journal={CAAI Artificial Intelligence Research},
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year={2024}
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}
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```
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## Citation
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```
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@article{zheng2024birefnet,
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title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
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author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
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journal={CAAI Artificial Intelligence Research},
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volume = {3},
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pages = {9150038},
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year={2024}
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}
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```
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