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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 weightsmodels/: Model architecture implementationisnet.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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