https://github.com/xinntao/facexlib

FaceXlib aims at providing ready-to-use face-related functions based on current STOA open-source methods.
https://github.com/xinntao/facexlib

alignment assessment deep-learning detection face headpose matting parsing pytorch recognition tracking

Last synced: about 4 hours ago
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FaceXlib aims at providing ready-to-use face-related functions based on current STOA open-source methods.

• Host: GitHub
• URL: https://github.com/xinntao/facexlib
• Owner: xinntao
• License: mit
• Created: 2021-03-19T09:06:02.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2024-02-29T08:35:02.000Z (7 months ago)
• Last Synced: 2024-05-17T11:45:05.895Z (5 months ago)
• Topics: alignment, assessment, deep-learning, detection, face, headpose, matting, parsing, pytorch, recognition, tracking
• Language: Python
• Homepage:
• Size: 1.05 MB
• Stars: 759
• Watchers: 14
• Forks: 137
• Open Issues: 30
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ![icon](assets/icon_small.png) FaceXLib

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[English](README.md) **|** [简体中文](README_CN.md)

---

**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 :star: this repo. Thanks:blush: 


Other recommended projects:   :arrow_forward: [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)   :arrow_forward: [GFPGAN](https://github.com/TencentARC/GFPGAN)   :arrow_forward: [BasicSR](https://github.com/xinntao/BasicSR)

---

## :sparkles: Functions

| Function | Sources  | Original LICENSE |

| :--- | :---:        |     :---:      |

| [Detection](facexlib/detection/README.md) | [Pytorch_Retinaface](https://github.com/biubug6/Pytorch_Retinaface) | MIT |

| [Alignment](facexlib/alignment/README.md) |[AdaptiveWingLoss](https://github.com/protossw512/AdaptiveWingLoss) | Apache 2.0 |

| [Recognition](facexlib/recognition/README.md) | [InsightFace_Pytorch](https://github.com/TreB1eN/InsightFace_Pytorch) | MIT |

| [Parsing](facexlib/parsing/README.md) | [face-parsing.PyTorch](https://github.com/zllrunning/face-parsing.PyTorch) | MIT |

| [Matting](facexlib/matting/README.md) | [MODNet](https://github.com/ZHKKKe/MODNet) | CC 4.0 |

| [Headpose](facexlib/headpose/README.md) | [deep-head-pose](https://github.com/natanielruiz/deep-head-pose) | Apache 2.0  |

| [Tracking](facexlib/tracking/README.md) |  [SORT](https://github.com/abewley/sort) | GPL 3.0 |

| [Assessment](facexlib/assessment/README.md) | [hyperIQA](https://github.com/SSL92/hyperIQA) | - |

| [Utils](facexlib/utils/README.md) | Face Restoration Helper | - |

## :eyes: Demo and Tutorials

## :wrench: Dependencies and Installation

- Python >= 3.7 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))

- [PyTorch >= 1.7](https://pytorch.org/)

- Option: NVIDIA GPU + [CUDA](https://developer.nvidia.com/cuda-downloads)

### Installation

```bash

pip install facexlib

```

### Pre-trained models

It 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`.

## :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 `[email protected]`.