Instructions to use onnx-community/ISNet-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use onnx-community/ISNet-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'onnx-community/ISNet-ONNX');
Download preprocessor_config.json from onnx-community/ISNet-ONNX: direct link, hf CLI and curl.
- Browser
- Download file 339 Bytes
-
https://huggingface.co/onnx-community/ISNet-ONNX/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://onnx-community/ISNet-ONNX/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/onnx-community/ISNet-ONNX/resolve/main/preprocessor_config.json
339 Bytes
| { | |
| "do_normalize": true, | |
| "do_rescale": false, | |
| "do_resize": true, | |
| "feature_extractor_type": "ViTFeatureExtractor", | |
| "image_mean": [ | |
| 128, | |
| 128, | |
| 128 | |
| ], | |
| "image_processor_type": "ViTFeatureExtractor", | |
| "image_std": [ | |
| 256, | |
| 256, | |
| 256 | |
| ], | |
| "resample": 2, | |
| "size": { | |
| "height": 1024, | |
| "width": 1024 | |
| } | |
| } |