BEN Base

BEN SOA Benchmarks on Disk 5k Eval

Demo Results

BEN_Base + BEN_Refiner (commercial model please contact us for more information):

• MAE: 0.0270
• DICE: 0.8989
• IOU: 0.8506
• BER: 0.0496
• ACC: 0.9740

BEN_Base (94 million parameters):

• MAE: 0.0309
• DICE: 0.8806
• IOU: 0.8371
• BER: 0.0516
• ACC: 0.9718

MVANet (old SOTA):

• MAE: 0.0353
• DICE: 0.8676
• IOU: 0.8104
• BER: 0.0639
• ACC: 0.9660

BiRefNet(not tested in house):

• MAE: 0.038

InSPyReNet (not tested in house):

• MAE: 0.042

Features

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

Installation

1. Clone Repo
2. Install requirements.txt

--- license: apache-2.0 pipeline_tag: image-segmentation tags: - BEN - background-remove - mask-generation - Dichotomous image segmentation - background remove - foreground - background - remove background - pytorch --- ## Model Provided by ParmaLLC The base model is publicly available and free to use for commercial use on HuggingFace: - 🤗 [PramaLLC/BEN](https://huggingface.co/PramaLLC/BEN) ## Quick Start Code (Inside Cloned Repo) ```python import model from PIL import Image import torch device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') file = "./image.png" # input image model = model.BEN_Base().to(device).eval() #init pipeline model.loadcheckpoints("./BEN_Base.pth") image = Image.open(file) mask, foreground = model.inference(image) mask.save("./mask.png") foreground.save("./foreground.png") ``` # BEN SOA Benchmarks on Disk 5k Eval  ### BEN_Base + BEN_Refiner (commercial model please contact us for more information): - MAE: 0.0270 - DICE: 0.8989 - IOU: 0.8506 - BER: 0.0496 - ACC: 0.9740 ### BEN_Base (94 million parameters): - MAE: 0.0309 - DICE: 0.8806 - IOU: 0.8371 - BER: 0.0516 - ACC: 0.9718 ### MVANet (old SOTA): - MAE: 0.0353 - DICE: 0.8676 - IOU: 0.8104 - BER: 0.0639 - ACC: 0.9660 ### BiRefNet(not tested in house): - MAE: 0.038 ### InSPyReNet (not tested in house): - MAE: 0.042 ## Features - Background removal from images - Generates both binary mask and foreground image - CUDA support for GPU acceleration - Simple API for easy integration ## Installation 1. Clone Repo 2. Install requirements.txt