How to use Go language for intelligent security development?

In recent years, with the continuous development of intelligent security technology, more and more companies have begun to pay attention to the field of intelligent security, and the Go language has attracted much attention due to its efficiency, security and concurrency performance. This article will introduce how to use Go language for intelligent security development and explore its application in the field of intelligent security.

1. Application of Go language in the field of intelligent security

Go language has strong concurrency capabilities and excellent support for I/O-intensive operations. It is used in intelligent security It has a wide range of applications in the field, such as:

Camera image processing: extracting feature information such as faces and license plates from the camera.

Video stream processing: Transmit the video stream obtained by the camera to the server for analysis and processing.

Anti-theft alarm system: Use Go language to write security monitoring programs to ensure functions such as doorbell response, sensor detection, and IP camera monitoring.

2. How to use Go language for intelligent security development?

2.1. Camera image processing

Using Go language for camera image processing requires the installation of OpenCV dependent libraries.

The following is a sample code that uses Go language to extract faces from images:

func main() {
    img, err := gocv.VideoCaptureDevice(0)
    if err != nil {
        fmt.Printf("Error opening capture device: %v
", 0)
        return
    }
    defer img.Close()

    gray := gocv.NewMat()
    defer gray.Close()

    faces := gocv.NewMat()
    defer faces.Close()

    classifier := gocv.NewCascadeClassifier()
    defer classifier.Close()

    if classifier.Load("haarcascade_frontalface_default.xml") {
        fmt.Println("Classifier loaded")
    }

    for {
        if ok := img.Read(&frame); !ok {
            fmt.Printf("Device closed: %v
", 0)
            return
        }
        if img.Empty() {
            continue
        }

        gocv.CvtColor(frame, &gray, gocv.ColorBGRToGray)
        classifier.DetectMultiScale(gray, &faces, 1.1, 3, 0, image.Point{X: 0, Y: 0}, image.Point{X: 0, Y: 0})
        for i, face := range faces.Rows() {
            gocv.Rectangle(&frame, image.Rect(face.GetIntAt(0), face.GetIntAt(1), face.GetIntAt(0)+face.GetIntAt(2), face.GetIntAt(1)+face.GetIntAt(3)), color.RGBA{255, 0, 0, 0}, 2)
            fmt.Println("Face found:", i)
        }

        window.IMShow(frame)
        window.WaitKey(1)
    }
}

Using this code, we can obtain images through the camera and extract face information from them.

2.2. Video stream processing

Using Go language for video stream processing has higher network requirements, and concurrency performance is even more important. In the Go language, you can use goroutines to implement concurrent processing, as shown below:

func main() {
    http.HandleFunc("/stream", func(w http.ResponseWriter, r *http.Request) {
        setHeaders(w)

        conn, _, err := w.(http.Hijacker).Hijack()
        checkError(err)
        defer conn.Close()

        fmt.Fprintf(conn, "HTTP/1.1 200 OK
")
        fmt.Fprintf(conn, "Content-Type: multipart/x-mixed-replace; boundary=myboundary
")
        fmt.Fprintf(conn, "
")

        c := make(chan []byte)
        go func() {
            for {
                frame, err := getFrame()
                if err != nil {
                    log.Println(err)
                    continue
                }
                c <- frame
            }
        }()

        for {
            select {
            case frame := <-c:
                fmt.Fprintf(conn, "--myboundary
")
                fmt.Fprintf(conn, "Content-Type: image/jpeg
")
                fmt.Fprintf(conn, "Content-Length: %d
", len(frame))
                fmt.Fprintf(conn, "
")
                conn.Write(frame)
            }
        }
    })

    log.Println("Listening...")
    err := http.ListenAndServe(":8080", nil)
    checkError(err)
}

This code uses the HTTP protocol to transmit the video stream. Video stream data is transmitted in real time and goroutine is used for concurrent processing, which improves the parallel performance of the program.

2.3. Anti-theft alarm system

Using Go language to write an anti-theft alarm system requires the use of external devices for sensing and control. The following is a simple example code for an anti-theft alarm system:

func main() {
    defer gpio.Close()

    // 设置针脚模式
    pir, err := gpio.OpenPin(4, gpio.ModeInput)
    checkError(err)
    defer pir.Close()

    buzzer, err := gpio.OpenPin(17, gpio.ModeOutput)
    checkError(err)
    defer buzzer.Close()

    // 监控针脚输入状态变化
    err = pir.BeginWatch(gpio.EdgeRising, func() {
        log.Println("Motion detected!")
        buzzer.Set()
        time.Sleep(time.Second)
        buzzer.Clear()
    })
    checkError(err)

    // 一直运行，直到程序退出
    select {}
}

In this code, we create a Nanjing Heat Pipe Laboratory 5025H-PE-12V infrared surveillance sensor and set the pin mode to input mode. The buzzer will sound when motion is detected in the monitored area.

3. Conclusion

By analyzing the above three sample codes, we can see that Go language is widely used in the field of intelligent security and has high efficiency, concurrency and security. Features. But on the other hand, because the language features and writing methods of the Go language are different from other languages, novices may need to spend more time and energy learning and mastering the language. We believe that as more developers join the ranks of the Go language and develop smart security on it, the development of this field will further accelerate.

The above is the detailed content of How to use Go language for intelligent security development?. For more information, please follow other related articles on the PHP Chinese website!