Image Segmentation
BEN2
ONNX
Safetensors
PyTorch
BEN2
background-remove
mask-generation
Dichotomous image segmentation
background remove
foreground
background
remove background
model_hub_mixin
pytorch_model_hub_mixin
background removal
background-removal
Instructions to use PramaLLC/BEN2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BEN2
How to use PramaLLC/BEN2 with BEN2:
import requests from PIL import Image from ben2 import AutoModel url = "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg" image = Image.open(requests.get(url, stream=True).raw) model = AutoModel.from_pretrained("PramaLLC/BEN2") model.to("cuda").eval() foreground = model.inference(image) - Notebooks
- Google Colab
- Kaggle
Update inference.py
Browse files- inference.py +1 -2
inference.py
CHANGED
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@@ -11,7 +11,6 @@ model = BEN2.BEN_Base().to(device).eval() #init pipeline
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model.loadcheckpoints("./BEN2_Base.pth")
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image = Image.open(file)
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mask.save("./mask.png")
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foreground.save("./foreground.png")
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model.loadcheckpoints("./BEN2_Base.pth")
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image = Image.open(file)
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foreground = model.inference(image)
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foreground.save("./foreground.png")
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