BEN2 Local Deployment Full Process Guide
environmental preparation: Python 3.8+ environment required, NVIDIA graphics card recommended (CUDA acceleration supported)
- Getting the model::
git clone https://huggingface.co/PramaLLC/BEN2 cd BEN2
- Installation of dependencies: Implementation
pip install -r requirements.txt(Includes core libraries such as PyTorch) - Initialization Model::
from model import BEN_Base device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') model = BEN_Base().to(device).eval() - executive reasoning::
mask, foreground = model.inference(Image.open('test.jpg')) mask.save('result_mask.png')
caveat: 1.13GB model file will be downloaded automatically for the first run; at least 8GB video memory is recommended for 4K processing; CPU mode processing time is about 3-5 times that of GPU.
This answer comes from the articleBEN2: Deep learning model for fast background removal from images, videosThe
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