Image Segmentation
BiRefNet
Safetensors
background-removal
mask-generation
Dichotomous Image Segmentation
pytorch_model_hub_mixin
model_hub_mixin
custom_code
Instructions to use ZhengPeng7/BiRefNet-legacy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use ZhengPeng7/BiRefNet-legacy with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet-legacy", 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-legacy") - Notebooks
- Google Colab
- Kaggle
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> This BiRefNet is trained on massive data: **DIS-TR+DIS-TEs, TR-HRS10K+TE-HRS10K, TR-HRSOD+TE-HRSOD, TR-UHRSD+TE-UHRSD** and validated on **DIS-VD**.
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## This repo holds the official model weights of "[<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>](https://arxiv.org/pdf/2401.03407.pdf)" (_arXiv 2024_).
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> This BiRefNet for **general foreground object extraction** is trained on massive data: **DIS-TR+DIS-TEs, TR-HRS10K+TE-HRS10K, TR-HRSOD+TE-HRSOD, TR-UHRSD+TE-UHRSD** and validated on **DIS-VD**.
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## This repo holds the official model weights of "[<ins>Bilateral Reference for High-Resolution Dichotomous Image Segmentation</ins>](https://arxiv.org/pdf/2401.03407.pdf)" (_arXiv 2024_).
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