Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
English
segformer
vision
nvidia/mit-b5
Instructions to use jonathandinu/face-parsing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonathandinu/face-parsing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="jonathandinu/face-parsing")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("jonathandinu/face-parsing") model = SegformerForSemanticSegmentation.from_pretrained("jonathandinu/face-parsing", device_map="auto") - Transformers.js
How to use jonathandinu/face-parsing with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'jonathandinu/face-parsing'); - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
89b2b7c
1
Parent(s): da0f6f3
add model
Browse files- preprocessor_config.json +0 -1
preprocessor_config.json
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"do_random_crop": false,
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "SegformerFeatureExtractor",
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "SegformerFeatureExtractor",
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