facexlib
v0.2.5 Release Note
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facexlib aims at providing ready-to-use face-related functions based on current SOTA open-source methods.
Only PyTorch reference codes are available. For training or fine-tuning, please refer to their original repositories listed below.
Note that we just provide a collection of these algorithms. You need to refer to their original LICENCEs for your intended use.
If facexlib is helpful in your projects, please help to this repo. Thanks?
Other recommended projects:
| Function | Sources | Original LICENSE |
|---|---|---|
| Detection | Pytorch_Retinaface | MIT |
| Alignment | AdaptiveWingLoss | Apache 2.0 |
| Recognition | InsightFace_Pytorch | MIT |
| Parsing | face-parsing.PyTorch | MIT |
| Matting | MODNet | CC 4.0 |
| Headpose | deep-head-pose | Apache 2.0 |
| Tracking | SORT | GPL 3.0 |
| Assessment | hyperIQA | - |
| Utils | Face Restoration Helper | - |
pip install facexlibIt will automatically download pre-trained models at the first inference.
If your network is not stable, you can download in advance (may with other download tools), and put them in the folder: PACKAGE_ROOT_PATH/facexlib/weights.
This project is released under the MIT license.
If you have any question, open an issue or email [email protected].
