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| title: facetorch-app | |
| emoji: 🧑🦲 | |
| colorFrom: red | |
| colorTo: black | |
| sdk: gradio | |
| sdk_version: 3.8.2 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| #  facetorch | |
|  | |
|  | |
| [](https://pypi.org/project/facetorch/) | |
| [](https://anaconda.org/conda-forge/facetorch) | |
| [](https://raw.githubusercontent.com/tomas-gajarsky/facetorch/main/LICENSE) | |
| <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> | |
| [Documentation](https://tomas-gajarsky.github.io/facetorch/facetorch/index.html), [Docker Hub](https://hub.docker.com/repository/docker/tomasgajarsky/facetorch) [(GPU)](https://hub.docker.com/repository/docker/tomasgajarsky/facetorch-gpu) | |
| Facetorch is a Python library that can detect faces and analyze facial features using deep neural networks. The goal is to gather open sourced face analysis models from the community, optimize them for performance using TorchScript and combine them to create a face analysis tool that one can: | |
| 1. configure using [Hydra](https://hydra.cc/docs/intro/) (OmegaConf) | |
| 2. reproduce with [conda-lock](https://github.com/conda-incubator/conda-lock) and [Docker](https://docs.docker.com/get-docker/) | |
| 3. accelerate on CPU and GPU with [TorchScript](https://pytorch.org/docs/stable/jit.html) | |
| 4. extend by uploading a model file to Google Drive and adding a config yaml file to the repository | |
| Please, use the library responsibly with caution and follow the | |
| [ethics guidelines for Trustworthy AI from European Commission](https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html). | |
| The models are not perfect and may be biased. |