Manage UI state with ViewModel

ViewModel

The ViewModel class is a business logic or screen level state holder, as explained in ViewModel overview on the Android Developer website. It exposes state to the UI and encapsulates related business logic.

The main advantage of using the ViewModel class is that it caches state and persists it through configuration changes. This means that the UI does not have to fetch data again when navigating between activities, or following configuration changes, such as screen rotation.

Add Android Jetpack Lifecycle libraries

You can now add Jetpack Lifecycle libraries to your app.

1. Navigate to libs.versions.toml and append the following line to the end of the [versions] section. This defines the version of the Jetpack Lifecycle libraries that you will be using.

    

        
        
lifecycle = "2.8.7"

    

2. Insert the following line to the [libraries] section, ideally between androidx-appcompat and material. This declares the Jetpack Lifecycle ViewModel Kotlin extension:

    

        
        
androidx-lifecycle-viewmodel = { group = "androidx.lifecycle", name = "lifecycle-viewmodel-ktx", version.ref = "lifecycle" }

    

3. Navigate to build.gradle.kts in your project’s app directory, then insert the following line into the dependencies block, ideally between implementation(libs.androidx.constraintlayout) and implementation(libs.camera.core):

    

        
        
implementation(libs.androidx.lifecycle.viewmodel)

    

Access the helper through a ViewModel

1. Create a new file named MainViewModel.kt and place it into the same directory of MainActivity.kt. Now copy and paste the code below into it:

    

        
        
package com.example.holisticselfiedemo

import android.app.Application
import android.util.Log
import androidx.lifecycle.ViewModel
import androidx.lifecycle.viewModelScope
import kotlinx.coroutines.launch

class MainViewModel : ViewModel(), HolisticRecognizerHelper.Listener {

    private val holisticRecognizerHelper = HolisticRecognizerHelper()

    fun setupHelper(context: Context) {
        viewModelScope.launch {
            holisticRecognizerHelper.apply {
                listener = this@MainViewModel
                setup(context)
            }
        }
    }

    fun shutdownHelper() {
        viewModelScope.launch {
            holisticRecognizerHelper.apply {
                listener = null
                shutdown()
            }
        }
    }

    fun recognizeLiveStream(imageProxy: ImageProxy) {
        holisticRecognizerHelper.recognizeLiveStream(
            imageProxy = imageProxy,
        )
    }

    override fun onFaceLandmarkerResults(resultBundle: FaceResultBundle) {
        Log.i(TAG, "Face result: $resultBundle")
    }

    override fun onFaceLandmarkerError(error: String, errorCode: Int) {
        Log.e(TAG, "Face landmarker error $errorCode: $error")
    }

    override fun onGestureResults(resultBundle: GestureResultBundle) {
        Log.i(TAG, "Gesture result: $resultBundle")
    }

    override fun onGestureError(error: String, errorCode: Int) {
        Log.e(TAG, "Gesture recognizer error $errorCode: $error")
    }

    companion object {
        private const val TAG = "MainViewModel"
    }
}

    

2. Bind MainViewModel to MainActivity by inserting the following line into MainActivity.kt, above the onCreate method. Do not forget to import the viewModels extension function through import androidx.activity.viewModels.

    

        
        
    private val viewModel: MainViewModel by viewModels()

    

3. Setup and shutdown the helper’s internal MediaPipe tasks on the app becomes active and inactive .

    

        
        
    private var isHelperReady = false

    override fun onResume() {
        super.onResume()
        viewModel.setupHelper(baseContext)
        isHelperReady = true
    }

    override fun onPause() {
        super.onPause()
        isHelperReady = false
        viewModel.shutdownHelper()
    }

    

Feed camera frames into livestream recognition

1. Add a new member variable named imageAnalysis to MainActivity, along with other camera- related member variables:

    

        
        
private var imageAnalysis: ImageAnalysis? = null

    

2. In MainActivity’s bindCameraUseCases() method, insert the following code after building preview, above cameraProvider.unbindAll():

    

        
        
        // ImageAnalysis. Using RGBA 8888 to match how MediaPipe models work
        imageAnalysis =
            ImageAnalysis.Builder()
                .setResolutionSelector(resolutionSelector)
                .setTargetRotation(targetRotation)
                .setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST)
                .setOutputImageFormat(ImageAnalysis.OUTPUT_IMAGE_FORMAT_RGBA_8888)
                .build()
                // The analyzer can then be assigned to the instance
                .also {
                    it.setAnalyzer(
                        // Forcing a serial executor without parallelism
                        // to avoid packets sent to MediaPipe out-of-order
                        Dispatchers.Default.limitedParallelism(1).asExecutor()
                    ) { image ->
                        if (isHelperReady)
                            viewModel.recognizeLiveStream(image)
                    }
                }

    

3. Append imageAnalysis along with other use cases to camera:

    

        
        
            camera = cameraProvider.bindToLifecycle(
                this, cameraSelector, preview, imageAnalysis
            )

    

4. Build and run the app again. Now you should see Face result: ... and Gesture result: ... debug messages in your Logcat , which prove that MediaPipe tasks are functioning properly. Good job!