go-face

go-face

go-face implements face recognition for Go using dlib, a popular machine learning toolkit. Read Face recognition with Go article for some background details if you're new to FaceNet concept.

Requirements

To compile go-face you need to have dlib (>= 19.10) and libjpeg development packages installed.

Ubuntu 18.10+, Debian sid

Latest versions of Ubuntu and Debian provide suitable dlib package so just run:

# Ubuntu
sudo apt-get install libdlib-dev libblas-dev libatlas-base-dev liblapack-dev libjpeg-turbo8-dev
# Debian
sudo apt-get install libdlib-dev libblas-dev libatlas-base-dev liblapack-dev libjpeg62-turbo-dev

macOS

Make sure you have Homebrew installed.

brew install dlib

Windows

Make sure you have MSYS2 installed.

1. Run MSYS2 MSYS shell from Start menu
2. Run pacman -Syu and if it asks you to close the shell do that
3. Run pacman -Syu again
4. Run pacman -S mingw-w64-x86_64-gcc mingw-w64-x86_64-dlib
5. 1. If you already have Go and Git installed and available in PATH uncomment set MSYS2_PATH_TYPE=inherit line in msys2_shell.cmd located in MSYS2 installation folder
   2. Otherwise run pacman -S mingw-w64-x86_64-go git
6. Run MSYS2 MinGW 64-bit shell from Start menu to compile and use go-face

Other systems

Try to install dlib/libjpeg with package manager of your distribution or compile from sources. Note that go-face won't work with old packages of dlib such as libdlib18. Alternatively create issue with the name of your system and someone might help you with the installation process.

Models

Currently shape_predictor_5_face_landmarks.dat, mmod_human_face_detector.dat and dlib_face_recognition_resnet_model_v1.dat are required. You may download them from go-face-testdata repo:

wget https://github.com/Kagami/go-face-testdata/raw/master/models/shape_predictor_5_face_landmarks.dat
wget https://github.com/Kagami/go-face-testdata/raw/master/models/dlib_face_recognition_resnet_model_v1.dat
wget https://github.com/Kagami/go-face-testdata/raw/master/models/mmod_human_face_detector.dat

Usage

To use go-face in your Go code:

import "github.com/Kagami/go-face"

To install go-face in your $GOPATH:

go get github.com/Kagami/go-face

For further details see GoDoc documentation.

Example

…

Run with:

mkdir -p ~/go && cd ~/go  # Or cd to your $GOPATH
mkdir -p src/go-face-example && cd src/go-face-example
git clone https://github.com/Kagami/go-face-testdata testdata
edit main.go  # Paste example code
go get && go run main.go

Test

To fetch test data and run tests:

make test

FAQ

How to improve recognition accuracy

There are few suggestions:

• Try CNN recognizing
• Try different tolerance values of ClassifyThreshold
• Try different size/padding/jittering values of NewRecognizerWithConfig
• Provide more samples of each category to SetSamples if possible
• Implement better classify heuristics (see classify.cc)
• Train network (dlib_face_recognition_resnet_model_v1.dat) on your own test data

License

go-face is licensed under CC0.