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https://github.com/gnimuc/fabsoften

Unofficial implementation of "FabSoften: face beautification via dynamic skin smoothing, guided feathering, and texture restoration"
https://github.com/gnimuc/fabsoften

cpp20 dlib face-beautification opencv

Last synced: 28 days ago
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Unofficial implementation of "FabSoften: face beautification via dynamic skin smoothing, guided feathering, and texture restoration"

Host: GitHub
URL: https://github.com/gnimuc/fabsoften
Owner: Gnimuc
License: mit
Created: 2021-10-24T13:07:04.000Z (about 3 years ago)
Default Branch: main
Last Pushed: 2021-11-28T15:04:40.000Z (almost 3 years ago)
Last Synced: 2023-02-28T19:32:28.995Z (over 1 year ago)
Topics: cpp20, dlib, face-beautification, opencv
Language: C++
Homepage:
Size: 10.1 MB
Stars: 20
Watchers: 2
Forks: 4
Open Issues: 3
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # FabSoften

[![Build Status](https://dev.azure.com/Gnimuc/FabSoften/_apis/build/status/Gnimuc.FabSoften?branchName=main)](https://dev.azure.com/Gnimuc/FabSoften/_build/latest?definitionId=1&branchName=main)

[![CI](https://github.com/Gnimuc/FabSoften/actions/workflows/CI.yml/badge.svg)](https://github.com/Gnimuc/FabSoften/actions/workflows/CI.yml)

[![Windows](https://svgshare.com/i/ZhY.svg)](https://svgshare.com/i/ZhY.svg)

[![Documentation](https://img.shields.io/badge/docs-dev-blue.svg)](https://gnimuc.github.io/FabSoften)

This project is an unofficial implementation of [FabSoften: face beautification via dynamic skin smoothing, guided feathering, and texture restoration](https://openaccess.thecvf.com/content_CVPRW_2020/papers/w31/Velusamy_FabSoften_Face_Beautification_via_Dynamic_Skin_Smoothing_Guided_Feathering_and_CVPRW_2020_paper.pdf). This paper is from Samsung R&D Institute Bangalore, India, and is very likely patented. This implementation is mainly for educational purposes, so the performance is not optimized.

![](./assets/result.png)

## Prerequisites

This project uses some C++20 features(e.g. [The One Ranges Proposal](http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2018/p0896r4.pdf)), so you need a relatively new C++ compiler.

As for the `ranges` feature, you need GCC 10+, Clang++ 13+, Microsoft Visual Studio 2019 16.10+. For other features, please check https://en.cppreference.com/w/cpp/compiler_support.

Before you begin, you'll install the following softwares on your system:

- [CMake 3.21+](https://cmake.org/): An open-source, cross-platform family of tools designed to build, test and package software

- [OpenCV 4+](https://github.com/opencv/opencv): Open Source Computer Vision Library

- [doxygen](https://github.com/doxygen/doxygen)(optional): The de facto standard tool for generating documentation from annotated C++ sources

- [7zip](https://www.7-zip.org/)(optional): A file archiver with a high compression ratio

[7zip](https://www.7-zip.org/) is used for extracting [bzip2](https://en.wikipedia.org/wiki/Bzip2) files(e.g. `shape_predictor_68_face_landmarks.dat.bz2`). If you'd like to [manually provide those models](./models/README.md) without auto-downloading through CMake, there is no need to use 7zip. If not, make sure `7z -h` works on the command line, for example:

```powershell

C:\Users\Gnimuc>7z -h

7-Zip 19.00 (x64) : Copyright (c) 1999-2018 Igor Pavlov : 2019-02-21

Usage: 7z  [...]  [...] [@listfile]

  a : Add files to archive

  b : Benchmark

...

```

## Build

On Windows, it's highly recommended to use `Powershell` or [Windows Terminal](https://aka.ms/terminal) to build this project:

```powershell

mkdir build

cd build

cmake .. -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=~/your_install_prefix_dir

cmake --build . --config Release

ctest --Release

```

## Examples

This library provides a thin C89 API over the C++ API, please check [this example](./examples/LibFabSoftenAPI) for details.

The C++ API and other examples can also be found in the `examples` folder.

## TODO List

- [x] Preprocessing

  - [x] Landmark Detection

  - [x] Binary Skin Mask

  - [x] Blemish Detection and Concealment

- [ ] Skin Mask Generation and Refinement

  - [x] GMM Clustering (https://github.com/Gnimuc/FabSoften/issues/6)

  - [ ] Segmentation?

  - [ ] Guided Feathering (pending)

- [x] Skin Imperfection Smoothing

  - [x] Dynamic Mean Filter

  - [x] Attribute-aware Dynamic Guided Filter

- [ ] Skin Texture Restoration (Wavelet-based STR)

## LICENSE

FabSoften is primarily distributed under the terms of the MIT license.

All _code_ in this repository is released under the terms of the MIT license.

Those [assets](./assets), [models](./models), and [external dependencies](./external) are released under their licenses, respectively.