Image Segmentation
ONNX
BiRefNet
Chinese
background-removal
matting
rembg
sam
u2net
clipseg
vitmatte
Instructions to use jkyy/yang-pixelcut-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use jkyy/yang-pixelcut-models with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("jkyy/yang-pixelcut-models", 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("jkyy/yang-pixelcut-models") - Notebooks
- Google Colab
- Kaggle
File size: 378 Bytes
4676b1c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "ViTImageProcessor",
"image_std": [
0.229,
0.224,
0.225
],
"processor_class": "CLIPSegProcessor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 352,
"width": 352
}
}
|