前言
学校的项目需要通过监控考生，实现反作弊功能。
之前用python通过face_recognition库实现了人脸识别，今天想试试go是否可行。
golang的go-face包需要安装dlib，我是用的macbook m1开发，
在引用go-face库时候出些各种问题，诸如 clang: error: the clang compiler does not support '-march=native'，又或者是 jpeg_mem_loader.cc:3:10: fatal error: 'jpeglib.h' file not found 等等。搞了半天都没弄通，于是想在ubuntu中试一试。
docker拉取ubuntu镜像
docker pull ubuntu
docker run -itd --name myface-demo -v $PWD/myface/go:/var/go ubuntu
安装dlib、golang、
docker exec -it myface-demo /bin/bash
// 更新源
apt-get update
// 安装dlib gcc库
apt-get install libdlib-dev libopenblas-dev libatlas-base-dev libjpeg-turbo8-dev build-essential wget vim
// 查看版本号
gcc --version
gcc (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
安装golang(下载地址)
wget https://golang.google.cn/dl/go1.17.7.linux-arm64.tar.gz
// 解压到/usr/local目录
tar -C /usr/local -xzf go1.17.7.linux-arm64.tar.gz
// 添加到环境变量中
vim ~/.bashrc
export PATH=$PATH:/usr/local/go/bin
source ~/.bashrc
// 检查版本
go version
go version go1.17.7 linux/arm64
拉取go-face包
cd /var/go/demo
go mod init myface
touch main.go
// 设置golang代理
echo "export GO111MODULE=on" >> ~/.bashrc
echo "export GOPROXY=https://goproxy.cn" >> ~/.bashrc
source ~/.bashrc
// 拉取go-face包
go get github.com/Kagami/go-face
项目结构
--models
--main.go
--go.mod
--jay-zhou.jpeg
--jay.jpeg
代码 main.go
package main
import (
"fmt"
"github.com/Kagami/go-face"
"log"
"path/filepath"
)
func main() {
fmt.Println("Facial Recognition System v0.01")
rec, err := face.NewRecognizer("models")
if err != nil {
fmt.Println("Cannot INItialize recognizer")
return
}
defer rec.Close()
fmt.Println("Recognizer Initialized")
avengersImage := filepath.Join("jay-zhou.jpeg")
faces, err := rec.RecognizeFile(avengersImage)
if err != nil {
log.Fatalf("Can't recognize: %v", err)
}
fmt.Println("Number of Faces in Image: ", len(faces))
var samples []face.Descriptor
var avengers []int32
for i, f := range faces {
samples = append(samples, f.Descriptor)
// Each face is unique on that image so Goes to its own category.
avengers = append(avengers, int32(i))
}
// Name the categories, i.e. people on the image.
labels := []string{
"周杰伦",
}
// Pass samples to the recognizer.
rec.SetSamples(samples, avengers)
// Now let's try to classify some not yet known image.
testTonyStark := filepath.Join("jay.jpeg")
tonyStark, err := rec.RecognizeSingleFile(testTonyStark)
if err != nil {
log.Fatalf("Can't recognize: %v", err)
}
if tonyStark == nil {
log.Fatalf("Not a single face on the image")
}
avengerID := rec.ClassifyThreshold(tonyStark.Descriptor, 0.3)
if avengerID < 0 {
fmt.Println(avengerID)
log.Fatalf("Can't classify")
}
fmt.Println(avengerID)
fmt.Println(labels[avengerID])
}
执行main.go
go run main.go
Facial Recognition System v0.01
Recognizer Initialized
Number of Faces in Image: 1
0
周杰伦
