Image-to-Image
BiRefNet
Safetensors
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 not-lain/BiRefNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use not-lain/BiRefNet with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("not-lain/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("not-lain/BiRefNet") - Notebooks
- Google Colab
- Kaggle
| from transformers import PretrainedConfig | |
| class BiRefNetConfig(PretrainedConfig): | |
| model_type = "SegformerForSemanticSegmentation" | |
| def __init__( | |
| self, | |
| bb_pretrained=False, | |
| **kwargs | |
| ): | |
| self.bb_pretrained = bb_pretrained | |
| super().__init__(**kwargs) | |