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ISNet Background Removal Model

This repository contains the ISNet (Image Segmentation Network) model for high-quality background removal.

Model Information

  • Architecture: ISNetDIS (ISNet for Image Segmentation)
  • Input: RGB images (3 channels)
  • Output: Segmentation masks (1 channel)
  • Model Size: ~168MB
  • Framework: PyTorch

Usage

from models import ISNetDIS
import torch

# Load model
model = ISNetDIS()
state_dict = torch.load("supplyswap_isnet.pth", map_location="cpu")
model.load_state_dict(state_dict)
model.eval()

# Use for inference
# See the Spaces demo for complete usage examples

Files

  • supplyswap_isnet.pth: Pre-trained model weights
  • models/: Model architecture implementation
    • isnet.py: ISNet model implementation
    • __init__.py: Model imports

Citation

If you use this model, please cite the original ISNet paper.

License

Please refer to the original model's license for usage terms.

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