Instructions to use leonelhs/faceparser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leonelhs/faceparser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="leonelhs/faceparser")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("leonelhs/faceparser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 757 Bytes
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license: mit
tags:
- vision
- image-segmentation
- makeup
---
### This is an non official Face Parser model mirror.
Reasons of this copy is because AI models can be very fragmented, and its hard to keeping point to an official source.
Meanwhile this concern will be solved, the projects listed here, will be using this repo.
### [Face Shine](https://github.com/leonelhs/face-shine)
Face Shine Is a backend server for photo enhancement and restoration.
### [Super Face](https://github.com/leonelhs/SuperFace/)
Super Face is a Python QT frontend for Face Shine server.
<img src="https://drive.google.com/uc?export=view&id=1D7hpjQSlUkzfTba-E5Ul4Rb1c8lYkFj5"/>
<img src="https://drive.google.com/uc?export=view&id=1oKpJe-Ff3SeEekhGVRP1Ap3eIFqt0c8u"/> |