BEN / README.md
Max Meyer
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license: apache-2.0

BEN - Background Erase Network

BEN is a deep learning model designed to automatically remove backgrounds from images, producing both a mask and a foreground image.

BEN SOA Benchmarks on Disk 5k Eval

BEN_Base + BEN_Refiner (commerical model please contanct us for more information): MAE-0.0283 DICE-0.8976 IOU-0.8430 BER-0.0542 ACC-0.9725

BEN_Base: MAE-0.0331 DICE-0.8743 IOU-0.8301 BER-0.0560 ACC-0.9700

MVANet (old SOA): MAE-0.0353 DICE-0.8676 IOU-0.8104 BER-0.0639 ACC-0.9660

Features

  • Background removal from images
  • Generates both binary mask and foreground image
  • CUDA support for GPU acceleration
  • Simple API for easy integration

Installation

  • Clone Repo
  • Install requirements.txt

Quick Start Code

from BEN import BEN_Base from PIL import Image import torch

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

model = BEN_Base().to(device).eval() model.loadcheckpoints("./BEN/BEN_Base.pth")

image = Image.open("./image2.jpg") mask, foreground = model.inference(image)

mask.save("./mask.png") foreground.save("./foreground.png")