Image Segmentation
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 wefttechnologies/BiRefNet2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use wefttechnologies/BiRefNet2 with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("wefttechnologies/BiRefNet2", 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("wefttechnologies/BiRefNet2") - Notebooks
- Google Colab
- Kaggle
Update birefnet.py
Browse files- birefnet.py +2 -2
birefnet.py
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import os
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import math
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class Config():
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def __init__(self) -> None:
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# PATH settings
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self.sys_home_dir = os.getenv('HOME', os.getenv('USERPROFILE')) # Make up your file system as: SYS_HOME_DIR/codes/dis/BiRefNet, SYS_HOME_DIR/datasets/dis/xx, SYS_HOME_DIR/weights/xx
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import os
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import math
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from transformers import PretrainedConfig
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class Config(PretrainedConfig):
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def __init__(self) -> None:
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# PATH settings
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self.sys_home_dir = os.getenv('HOME', os.getenv('USERPROFILE')) # Make up your file system as: SYS_HOME_DIR/codes/dis/BiRefNet, SYS_HOME_DIR/datasets/dis/xx, SYS_HOME_DIR/weights/xx
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