Golang implements face liveness detection, Baidu AI interface teaches you how to do it!

Golang implements live face detection, Baidu AI interface teaches you how to do it!

Face liveness detection is one of the hot research areas in the field of artificial intelligence today. It can distinguish real faces from fake faces, improving the security and accuracy of face recognition systems. This article will introduce how to use Golang to write code to implement face liveness detection, and use Baidu AI interface to assist in realizing this function.

Before we begin, we need to create an account on the Baidu AI platform and create an application for face liveness detection. After creating the application, you will get an API Key and Secret Key. We will use these keys to access the Baidu AI interface.

First, we need to install an HTTP request library in the Go environment to send requests and receive responses to the Baidu AI interface. This library can be installed using the following command:

go get github.com/go-resty/resty/v2

Introduce this library into the code:

import (
    "github.com/go-resty/resty/v2"
)

Next, we define a function to send an HTTP POST request and return the response from the Baidu AI interface:

func sendRequest(url string, imagePath string, accessToken string) ([]byte, error) {
    client := resty.New()
    resp, err := client.R().
        SetFile("image", imagePath).
        SetHeader("Content-Type", "multipart/form-data").
        SetHeader("Authorization", "Bearer "+accessToken).
        Post(url)

    if err != nil {
        return nil, err
    }

    return resp.Body(), nil
}

In this function, we use the resty library to create an HTTP client and add the image file to the request using the SetFile method. Next, we set the Content-Type header of the request, setting it to multipart/form-data, indicating that we are sending multiple parts of the form data. You also need to set the Authorization header and add the access token of the Baidu AI interface to the request. Finally, we send the request using the POST method and return the body of the response.

Next, we define a function to obtain the access token of Baidu AI interface:

func getAccessToken(apiKey string, secretKey string) (string, error) {
    client := resty.New()
    resp, err := client.R().
        SetFormData(map[string]string{
            "grant_type":    "client_credentials",
            "client_id":     apiKey,
            "client_secret": secretKey,
        }).
        Post("https://aip.baidubce.com/oauth/2.0/token")

    if err != nil {
        return "", err
    }

    var data struct {
        AccessToken string `json:"access_token"`
    }
    if err := json.Unmarshal(resp.Body(), &data); err != nil {
        return "", err
    }

    return data.AccessToken, nil
}

In this function, we use the resty library to create an HTTP client and use The SetFormData method sets the requested form data. We need to add four fields to the form data: grant_type, client_id, client_secret, and access_token. The request will be sent to the specified URL, and the body of the response will contain the access token. Finally, we use the json.Unmarshal function to decode the JSON response into a structure and extract the access token from it.

Now, we can start writing the code to implement face liveness detection. The following is a sample function:

func faceLivenessDetection(imagePath string) (bool, error) {
    apiKey := "your-api-key"
    secretKey := "your-secret-key"

    accessToken, err := getAccessToken(apiKey, secretKey)
    if err != nil {
        return false, err
    }

    url := "https://aip.baidubce.com/rest/2.0/face/v3/faceverify?access_token=" + accessToken
    resp, err := sendRequest(url, imagePath, accessToken)
    if err != nil {
        return false, err
    }

    var data struct {
        ErrorMsg string `json:"error_msg"`
        Result   struct {
            FaceList []struct {
                FaceProbability float64 `json:"face_probability"`
                Spoofing       struct {
                    Liveness float64 `json:"liveness"`
                } `json:"spoofing_info"`
            } `json:"face_list"`
        } `json:"result"`
    }
    if err := json.Unmarshal(resp, &data); err != nil {
        return false, err
    }

    if data.ErrorMsg != "SUCCESS" {
        return false, errors.New(data.ErrorMsg)
    }

    return data.Result.FaceList[0].Spoofing.Liveness > 0.9, nil
}

In this function, we first obtain the access token of Baidu AI interface. We then build the API's URL, using the access token as a query parameter. We call the sendRequest method defined above to send the face image and receive the response. Finally, we decode the JSON response and extract the liveness detection results from it.

To use this function, we only need to provide the path of a face image as a parameter, and it will return a Boolean value indicating whether the face passes liveness detection.

func main() {
    imagePath := "path/to/face/image.jpg"
    isLive, err := faceLivenessDetection(imagePath)
    if err != nil {
        log.Fatalf("Failed to detect face liveness: %v", err)
    }

    if isLive {
        fmt.Println("Face passed liveness detection.")
    } else {
        fmt.Println("Face failed liveness detection.")
    }
}

This is a simple example that demonstrates how to use Golang to write code to implement face liveness detection, and complete this function through Baidu AI interface. I hope this article will help you understand Golang and face liveness detection!

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