Image Segmentation
BEN2
ONNX
Safetensors
PyTorch
BEN2
background-remove
mask-generation
Dichotomous image segmentation
background remove
foreground
background
remove background
model_hub_mixin
pytorch_model_hub_mixin
background removal
background-removal
Instructions to use PramaLLC/BEN2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BEN2
How to use PramaLLC/BEN2 with BEN2:
import requests from PIL import Image from ben2 import AutoModel url = "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg" image = Image.open(requests.get(url, stream=True).raw) model = AutoModel.from_pretrained("PramaLLC/BEN2") model.to("cuda").eval() foreground = model.inference(image) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,6 +14,8 @@ tags:
|
|
| 14 |
- pytorch
|
| 15 |
- model_hub_mixin
|
| 16 |
- pytorch_model_hub_mixin
|
|
|
|
|
|
|
| 17 |
---
|
| 18 |
|
| 19 |
# BEN2: Background Erase Network
|
|
@@ -149,6 +151,4 @@ RMBG 2.0 did not preserve the DIS 5k validation dataset
|
|
| 149 |

|
| 150 |

|
| 151 |

|
| 152 |
-

|
| 153 |
-
|
| 154 |
-
|
|
|
|
| 14 |
- pytorch
|
| 15 |
- model_hub_mixin
|
| 16 |
- pytorch_model_hub_mixin
|
| 17 |
+
- background removal
|
| 18 |
+
- background-removal
|
| 19 |
---
|
| 20 |
|
| 21 |
# BEN2: Background Erase Network
|
|
|
|
| 151 |

|
| 152 |

|
| 153 |

|
| 154 |
+

|
|
|
|
|
|