Basic face library
Project description
FaceXLib
English | 简体中文 GitHub | Gitee码云
facexlib is a pytorch-based library for face-related functions, such as detection, alignment, recognition, tracking, utils for face restorations, etc.
It only provides inference (without training).
This repo is based current STOA open-source methods (see more details).
:eyes: Demo
:wrench: Dependencies and Installation
- Python >= 3.7 (Recommend to use Anaconda or Miniconda)
- PyTorch >= 1.3
- NVIDIA GPU + CUDA
:sparkles: Functions
| Function | Description | Reference |
|---|---|---|
| Detection | (More details | Pytorch_Retinaface |
| Alignment | (More details | AdaptiveWingLoss |
| Recognition | (More details | InsightFace_Pytorch |
| Tracking | (More details | SORT |
| Utils | (More details) |
:scroll: License and Acknowledgement
This project is released under the MIT license.
:e-mail: Contact
If you have any question, open an issue or email xintao.wang@outlook.com.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
facexlib-0.1.0.tar.gz
(4.1 kB
view details)
Built Distribution
File details
Details for the file facexlib-0.1.0.tar.gz.
File metadata
- Download URL: facexlib-0.1.0.tar.gz
- Upload date:
- Size: 4.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 09ab2bddf98dd8fa87e8d6a1a7683843a87092506c865cab50aa22de36cb2fc8 |
|
| MD5 | f745b91e67f9cfae3fe7ddd66cab97fe |
|
| BLAKE2b-256 | e25aa99b674afe83d776532a33c653859d01111b6af7fa4ace8254227cc191aa |
File details
Details for the file facexlib-0.1.0-py3-none-any.whl.
File metadata
- Download URL: facexlib-0.1.0-py3-none-any.whl
- Upload date:
- Size: 2.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 8b6f77d7ec82ccccfc17e935383acb4a22fe4e290bfd398addb0c4da3d3b0698 |
|
| MD5 | c1ee28586850bb46bb29efbc9ce05dfc |
|
| BLAKE2b-256 | cb8788b1da74d9b3d9a28597a68268d49f6e0d2d92f725daf0d2cc8e615baad1 |
