Image Segmentation
Transformers.js
ONNX
swin
background-removal
matting
alpha-matting
image-matting
webgpu
client-side
in-browser
fp16
Instructions to use imquentinn/birefnet-lite-1024-webgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use imquentinn/birefnet-lite-1024-webgpu with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'imquentinn/birefnet-lite-1024-webgpu');
Download preprocessor_config.json from imquentinn/birefnet-lite-1024-webgpu: direct link, hf CLI and curl.
- Browser
- Download file 391 Bytes
-
https://huggingface.co/imquentinn/birefnet-lite-1024-webgpu/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://imquentinn/birefnet-lite-1024-webgpu/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/imquentinn/birefnet-lite-1024-webgpu/resolve/main/preprocessor_config.json
391 Bytes
| { | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "ViTFeatureExtractor", | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "ViTFeatureExtractor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 1024, | |
| "width": 1024 | |
| } | |
| } |