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license: apache-2.0
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# 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")