Use Gin framework to implement face recognition and identity verification functions

With the continuous advancement of artificial intelligence technology, facial recognition technology has gradually been applied to various areas of life, such as payment, attendance, access control, etc. In these scenarios, face recognition technology has been widely used as an efficient and convenient identity verification method. This article will introduce how to use the Gin framework to implement face recognition and identity verification functions, and provide a detailed analysis of the identity verification process and code.

1. Face recognition technology and applications

1.1 What is face recognition technology

Face recognition technology is a technology that uses computer image processing and pattern recognition to Technology for automatic detection, tracking and recognition of faces in digital or video images. Face recognition technology mainly includes the following steps:

1) Collecting face images

2) Facial image preprocessing

3) Facial feature extraction

4) Face feature comparison

5) Recognition result output

1.2 Application of face recognition technology

Currently, face recognition technology has been widely used In the following fields:

1) Bank card, payment and other financial fields

2) Access control management

3) Attendance management

4) Security field

5) Transportation field

6) Social network

7) Games and other entertainment fields

2. Identity verification process

Identity verification The process refers to the process of verifying the user's identity through face recognition technology. The specific process is as follows:

1) The user uploads pictures through the application

2) The application processes the uploaded pictures Face detection and facial feature extraction

3) The application compares the extracted facial features with the pre-stored features in the database

4) If the comparison is successful, the authentication is successful. If the pair fails, the authentication fails

5) Return the authentication result

3. Use the Gin framework to implement face recognition

3.1 Introduction to the Gin framework

Gin framework It is a lightweight Web framework developed using the Go language. It has the advantages of fast, efficient, and easy to learn. It is currently one of the most widely used Web frameworks.

3.2 Implementation Idea

This article will use the Gin framework and facebox face recognition library to implement face recognition and identity verification functions. The specific implementation steps are as follows:

1) User uploads pictures

2) The server receives the pictures and performs face detection and feature extraction through the facebox library

3) The server will extract The facial features are stored in the database

4) The next time the user performs identity verification, after the uploaded image has been subjected to face detection and feature extraction, the extracted facial features will be compared with the pre-stored features in the database Comparison, if the comparison is successful, the authentication is successful, otherwise the authentication fails.

3.3 Code Implementation

The following is a sample code that uses the Gin framework and facebox library to implement face recognition and authentication:

package main

import (
    "fmt"
    "github.com/gin-gonic/gin"
    "github.com/rakyll/statik/fs"
    "image"
    _ "image/jpeg"
    "io/ioutil"
    "log"
    "net/http"
    _ "strconv"
    _ "strings"
    _ "sync"
    "time"
    "github.com/joho/godotenv"
    "github.com/snowzach/rotate"
    "github.com/hybridgroup/mjpeg"
    _ "github.com/gogo/protobuf/proto"
    _ "github.com/golang/snappy"
    "io"
    "github.com/esimov/caire"
    "github.com/esimov/stackblur-go"
    "github.com/esimov/pigo/core"
)

const (
    connHost = "127.0.0.1"
    connPort = ":8080"
)

type User struct {
    ID   int64  `json:"id"`
    Name string `json:"name"`
    Age  int    `json:"age"`
}

type Users struct {
    Users []User `json:"users"`
}

func main() {
    
    // 加载配置文件
    err := godotenv.Load()
    if err != nil {
        log.Fatal("Error loading .env file")
    }

    router := gin.Default()

    // 上传图片
    router.POST("/upload", func(c *gin.Context) {

        file, header, err := c.Request.FormFile("image")
        if err != nil {
            c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
            return
        }

        // 图像预处理
        img, format, err := image.Decode(file)
        if err != nil {
            c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
            return
        }

        var body io.Reader
        var contentType string
        var contentEncoding string

        // 图像压缩
        if img.Bounds().Dx() > 720 || img.Bounds().Dy() > 720 {
            img = resizeProcess(img, 720)
        }

        buffer := make([]byte, 0, 1024*1024)
        writer := bytes.NewBuffer(buffer)
        var q = jpeg.Options{Quality: 90}

        err = jpeg.Encode(writer, img, &q)
        if err != nil {
            c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
            return
        }

        body = writer
        contentType = http.DetectContentType(buffer)
        contentEncoding = "identity"

        bufSize := uint32(len(buffer))
        if bufSize < 6 || bufSize > core.GetMaxImageBufferSize() {
            c.String(http.StatusBadRequest, fmt.Sprintf("Image size %d is not valid", bufSize))
            return
        }

        // 进行人脸检测和特征提取
        fb := NewFaceboxHandler()
        featureIds, err := fb.indexModule.Index(clientId, buffer)

        if err != nil {
            log.Fatal("Error indexing image: ", err)
        } else {
            fmt.Println("Index featureIds: ", featureIds)
            c.JSON(200, gin.H{"image_id": featureIds})
        }

        // 文件上传和保存操作。。。
        
    })

    router.Run(connHost + connPort)
}

4. Conclusion

This article mainly introduces face recognition technology and applications, and how to use the Gin framework and facebox library to implement face recognition and identity verification functions. Of course, this is just a simple example, and actual application scenarios may include some other functions and details. However, I believe that through the introduction of this article, readers have already gained a certain understanding and understanding of face recognition technology and the use of the Gin framework to implement this function, and can further explore this field in the future.

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