Golang implements face liveness detection? Baidu AI interface teaches you how to implement it easily!

Golang implements live face detection? Baidu AI interface teaches you how to implement it easily!

Introduction:
With the development of artificial intelligence technology, face recognition technology has become one of the core technologies in many application fields. In the application of face recognition, face liveness detection is a very important part, which can effectively prevent the use of photos or videos for forgery and deception. This article will introduce how to use Golang to implement face liveness detection. This function can be easily realized through the functions provided by Baidu AI interface.

1. Get API Key and Secret Key
   First, you need to register an account on Baidu AI platform and create an application. After creating the application, you can obtain the API Key and Secret Key, which are needed for subsequent API calls.

2. Install Go SDK
   Before you start, you need to install the Go development environment and Baidu AI's Go SDK. You can install the SDK through the following command:

   go get github.com/solomondove/goaiplus

3. Start using the SDK
   In your Go code, you need to import the SDK package to use related functions:

   import (
    "fmt"
    "github.com/solomondove/goaiplus"
   )

4. Call the liveness detection interface
   Below we will call the face liveness detection interface to implement liveness detection. Before calling the interface, you need to read the image file to be detected as byte stream data and convert it into a base64-encoded string.

   imgData, err := ioutil.ReadFile("test.jpg")
   if err != nil {
    fmt.Println("Read image file error:", err)
    return
   }
   imgBase64 := base64.StdEncoding.EncodeToString(imgData)

Then, you need to create a Baidu AI client object and initialize it with your API Key and Secret Key:

client := goaiplus.NewAIClient("your_api_key", "your_secret_key")

Finally, use the client The object calls the interface for live detection:

result, err := client.FaceLivenessVerify(imgBase64)
if err != nil {
    fmt.Println("Face liveness verify error:", err)
    return
}
fmt.Println("Face liveness verify result:", result)

5. Parsing results
   The result returned by the live detection interface is a JSON string. We need to parse the string to obtain the specific live detection results. . You can use Go's json package for parsing:

   type LivenessVerifyResult struct {
    LogId      string `json:"log_id"`
    Result     struct {
        FaceList []struct {
            FaceToken string `json:"face_token"`
            Location  struct {
                Left     int `json:"left"`
                Top      int `json:"top"`
                Width    int `json:"width"`
                Height   int `json:"height"`
                Rotation int `json:"rotation"`
            } `json:"location"`
            Liveness struct {
                Livemapscore float64 `json:"livemapscore"`
            } `json:"liveness"`
        } `json:"face_list"`
    } `json:"result"`
   }
   
   var lvResult LivenessVerifyResult
   err = json.Unmarshal([]byte(result), &lvResult)
   if err != nil {
    fmt.Println("Parse liveness verify result error:", err)
    return
   }
   fmt.Println("Face token:", lvResult.Result.FaceList[0].FaceToken)
   fmt.Println("Liveness score:", lvResult.Result.FaceList[0].Liveness.Livemapscore)

In the above code, we define a structure to correspond to the JSON format of the live detection results, and then use the json.Unmarshal function Parse the resulting string into this structure.

Summary:
This article introduces how to use Golang to implement face liveness detection and use Baidu AI interface to implement this function. Through the analysis results, it can be judged whether the face in the picture is a real living body, which effectively improves the security of face recognition. I hope this article can help you have a better understanding of face liveness detection in Golang.

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