How to Integrate Server-Based Liveness into Your Mobile Application

This guide outlines the steps for integrating the Oz Liveness Mobile SDK into a customer mobile application for capturing facial videos and subsequently analyzing them on the server.

The SDK implements a ready-to-use face capture user interface that is essential for seamless customer experience and accurate liveness results. The SDK methods for liveness analysis communicate with Oz API under the hood.

Before you begin, make sure you have Oz API credentials. When using SaaS API, you get them from us:

For the on-premise Oz API, you need to create a user yourself or ask your team that manages the API. See the guide on user creation via Web Console. Consider the proper user role (CLIENT in most cases or CLIENT ADMIN, if you are going to make SDK work with the pre-created folders from other API users). In the end, you need to obtain a similar set of credentials as you would get for the SaaS scenario.

We also recommend that you use our logging service called telemetry, as it helps a lot in investigating attacks' details. For Oz API users, the service is enabled by default. For on-premise installations, we'll provide you with credentials.

Oz Liveness Mobile SDK requires a license. License is bound to the bundle_id of your application, e.g., com.yourcompany.yourapp. Issue the 1-month trial license on our website or email us for a long-term license.

Android

1. Add SDK to your project

In the build.gradle of your project, add:

allprojects {
    repositories {
        maven { url "https://ozforensics.jfrog.io/artifactory/main" }
    }
}

In the build.gradle of the module, add:

dependencies {
    implementation 'com.ozforensics.liveness:full:<version>'
    // You can find the version needed in the Android changelog
}

2. Initialize SDK

Rename the license file to forensics.license and place it into the project's res/raw folder.

OzLivenessSDK.init(
    context,
    listOf(LicenseSource.LicenseAssetId(R.raw.forensics))
)

3. Connect SDK to Oz API

Use API credentials (login, password, and API URL) that you’ve got from us.

OzLivenessSDK.setApiConnection(
    OzConnection.fromCredentials(host, username, password),
    statusListener(
        { token -> /* token */ },
        { ex -> /* error */ }
    )
)

In production, instead of hard-coding login and password in the application, it is recommended to get access token on your backend with API auth method then pass it to your application:

OzLivenessSDK.setApiConnection(OzConnection.fromServiceToken(host, token))

4. Add face recording

To start recording, use startActivityForResult:

val OZ_LIVENESS_REQUEST_CODE = 1
val intent = OzLivenessSDK.createStartIntent(listOf( OzAction.Blank)) startActivityForResult(intent, OZ_LIVENESS_REQUEST_CODE)

To obtain the captured video, use onActivityResult:

override fun onActivityResult(requestCode: Int, resultCode: Int, data: Intent?) {
    super.onActivityResult(requestCode, resultCode, data)
        if (requestCode == OZ_LIVENESS_REQUEST_CODE) {
            val sdkMediaResult = OzLivenessSDK.getResultFromIntent(data)
            val sdkErrorString = OzLivenessSDK.getErrorFromIntent(data)
            if (!sdkMediaResult.isNullOrEmpty()) {
                analyzeMedia(sdkMediaResult)
            } else println(sdkErrorString)
        }
    }

The sdkMediaResult object contains the captured videos.

5. Run analyses

To run the analyses, execute the code below. Mind that mediaList is an array of objects that were captured (sdkMediaResult) or otherwise created (media you captured on your own).

private fun analyzeMedia(mediaList: List<OzAbstractMedia>) {
    AnalysisRequest.Builder()
        .addAnalysis(Analysis(Analysis.Type.QUALITY, Analysis.Mode.SERVER_BASED, mediaList))
        .build()
        .run(object : AnalysisRequest.AnalysisListener {
            override fun onSuccess(result: List<OzAnalysisResult>) {
                result.forEach { 
                    println(it.resolution.name)
                    println(it.folderId)
                }
            }
            override fun onError(error: OzException) {
                error.printStackTrace()
            }
        })
} 

iOS

1. Add our SDK to your project

Install OZLivenessSDK via CocoaPods. To integrate OZLivenessSDK into an Xcode project, add to Podfile:

pod 'OZLivenessSDK', :git => 'https://gitlab.com/oz-forensics/oz-liveness-ios', :tag => '<version>' // You can find the version needed in  iOS changelog

2. Initialize SDK

Rename the license file to forensics.license and put it into the project.

OZSDK(licenseSources: [.licenseFileName("forensics.license")]) { licenseData, error in
    if let error = error {
        print(error.errorDescription)
    }
}

3. Connect SDK to Oz API

Use API credentials (login, password, and API URL) that you’ve got from us.

OZSDK.setApiConnection(Connection.fromCredentials(host: “https://sandbox.ohio.ozforensics.com”, login: login, password: p)) { (token, error) in
    // Your code to handle error or token
}

In production, instead of hard-coding the login and password in the application, it is recommended to get an access token on your back end using the API auth method, then pass it to your application:

OZSDK.setApiConnection(Connection.fromServiceToken(host: "https://sandbox.ohio.ozforensics.com", token: token)) { (token, error) in
}

4. Add face recording

Create a controller that will capture videos as follows:

let actions: [OZVerificationMovement] = [.selfie]
let ozLivenessVC: UIViewController = OZSDK.createVerificationVCWithDelegate(delegate, actions: actions) 
self.present(ozLivenessVC, animated: true)

The delegate object must implement OZLivenessDelegate protocol:

let actions: [OZVerificationMovement] = [.selfie]
let ozLivenessVC: UIViewController = OZSDK.createVerificationVCWithDelegate(delegate, actions: actions) 
self.present(ozLivenessVC, animated: true)

5. Run analyses

Use AnalysisRequestBuilder to initiate the Liveness analysis. The communication with Oz API is under the hood of the run method.

let analysisRequest = AnalysisRequestBuilder()
let analysis = Analysis.init(
media: mediaToAnalyze, 
type: .quality, 
mode: .serverBased)
analysisRequest.uploadMedia(mediaToAnalyze)
analysisRequest.addAnalysis(analysis)
analysisRequest.run(
scenarioStateHandler: { state in }, // scenario steps progress handler
uploadProgressHandler: { (progress) in } // file upload progress handler 
) { (analysisResults : [OzAnalysisResult], error) in 
    // receive and handle analyses results here 
    for result in analysisResults {
        print(result.resolution)
        print(result.folderID)
    }
}

With these steps, you are done with basic integration of Mobile SDKs. You will be able to access recorded media and analysis results in Web Console via browser or programmatically via API.

In developer guides, you can also find instructions for customizing the SDK look-and-feel and access the full list of our Mobile SDK methods. Check out the table below:

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