Image Segmentation
BiRefNet
Safetensors
Transformers
background-removal
mask-generation
Dichotomous Image Segmentation
Camouflaged Object Detection
Salient Object Detection
pytorch_model_hub_mixin
model_hub_mixin
custom_code
Instructions to use ZhengPeng7/BiRefNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use ZhengPeng7/BiRefNet with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet", trust_remote_code=True)# Option 2: use with BiRefNet # Install from https://github.com/ZhengPeng7/BiRefNet from models.birefnet import BiRefNet model = BiRefNet.from_pretrained("ZhengPeng7/BiRefNet") - Transformers
How to use ZhengPeng7/BiRefNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ZhengPeng7/BiRefNet", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
79a6660
1
Parent(s): 45e89f1
Move all BiRefNet github codes to the first level directory.
Browse files- BiRefNet_pipe.py +0 -1
- __init__.py +0 -0
BiRefNet_pipe.py
CHANGED
|
@@ -7,4 +7,3 @@ class BiRefNetPipe(Pipeline):
|
|
| 7 |
Pipeline.__init__(self, **kwargs)
|
| 8 |
self.model.to(['cpu', 0][torch.cuda.is_available()])
|
| 9 |
self.model.eval()
|
| 10 |
-
|
|
|
|
| 7 |
Pipeline.__init__(self, **kwargs)
|
| 8 |
self.model.to(['cpu', 0][torch.cuda.is_available()])
|
| 9 |
self.model.eval()
|
|
|
__init__.py
ADDED
|
File without changes
|