Resolved issue #30

README.md

@@ -15,6 +15,13 @@ We don't need to modify the app/retrain any ML model to add more people ( subjec
   
 ## What's New
 
+### Updates - September 2022
+
+- Modified `settings.gradle` to use the new plugin management system.
+- The conversion of `Bitmap` to NV21-formatted `ByteArray` ( YUV420 ) is now transformed into a suspending function 
+to avoid blocking of the UI thread when a large number of images are being processed.
+- 
+
 ### Updates - December 2021
 
 - Users can now control the use of `GpuDelegate` and `XNNPack` using `useGpu` and `useXNNPack` in 

app/build.gradle

@@ -4,11 +4,11 @@ plugins {
 }
 
 android {
-    compileSdk 32
+    compileSdk 33
     defaultConfig {
-        applicationId "com.edu.shubham0204.attendancesystem"
+        applicationId "com.ml.quaterion.facenetdetection"
         minSdk 25
-        targetSdk 32
+        targetSdk 33
         versionCode 1
         versionName "1.0"
         testInstrumentationRunner "androidx.test.runner.AndroidJUnitRunner"
@@ -33,8 +33,8 @@ android {
 
 dependencies {
     implementation fileTree(dir: 'libs', include: ['*.jar'])
-    implementation 'androidx.core:core-ktx:1.8.0'
-    implementation 'androidx.appcompat:appcompat:1.5.0'
+    implementation 'androidx.core:core-ktx:1.9.0'
+    implementation 'androidx.appcompat:appcompat:1.5.1'
     implementation 'com.google.android.material:material:1.6.1'
     implementation 'androidx.constraintlayout:constraintlayout:2.1.4'
 

app/src/main/java/com/ml/quaterion/facenetdetection/BitmapUtils.kt

@@ -20,6 +20,9 @@ import android.graphics.*
 import android.media.Image
 import android.net.Uri
 import android.os.ParcelFileDescriptor
+import android.util.Log
+import kotlinx.coroutines.Dispatchers
+import kotlinx.coroutines.withContext
 import java.io.ByteArrayOutputStream
 import java.io.File
 import java.io.FileDescriptor
@@ -109,13 +112,13 @@ class BitmapUtils {
 
         // Convert the given Bitmap to NV21 ByteArray
         // See this comment -> https://github.com/firebase/quickstart-android/issues/932#issuecomment-531204396
-        fun bitmapToNV21ByteArray(bitmap: Bitmap): ByteArray {
+        suspend fun bitmapToNV21ByteArray(bitmap: Bitmap): ByteArray = withContext(Dispatchers.Default) {
             val argb = IntArray(bitmap.width * bitmap.height )
             bitmap.getPixels(argb, 0, bitmap.width, 0, 0, bitmap.width, bitmap.height)
             val yuv = ByteArray(bitmap.height * bitmap.width + 2 * Math.ceil(bitmap.height / 2.0).toInt()
                     * Math.ceil(bitmap.width / 2.0).toInt())
             encodeYUV420SP( yuv, argb, bitmap.width, bitmap.height)
-            return yuv
+            return@withContext yuv
         }
 
         private fun encodeYUV420SP(yuv420sp: ByteArray, argb: IntArray, width: Int, height: Int) {

app/src/main/java/com/ml/quaterion/facenetdetection/FileReader.kt

@@ -32,7 +32,8 @@ class FileReader( private var faceNetModel: FaceNetModel ) {
         .setPerformanceMode( FaceDetectorOptions.PERFORMANCE_MODE_FAST )
         .build()
     private val detector = FaceDetection.getClient( realTimeOpts )
-    private val coroutineScope = CoroutineScope( Dispatchers.Main )
+    private val defaultScope = CoroutineScope( Dispatchers.Default )
+    private val mainScope = CoroutineScope( Dispatchers.Main )
     private var numImagesWithNoFaces = 0
     private var imageCounter = 0
     private var numImages = 0
@@ -62,52 +63,55 @@ class FileReader( private var faceNetModel: FaceNetModel ) {
     // Crop faces and produce embeddings ( using FaceNet ) from given image.
     // Store the embedding in imageData
     private fun scanImage( name : String , image : Bitmap ) {
-        val inputImage = InputImage.fromByteArray(
-            BitmapUtils.bitmapToNV21ByteArray( image ) ,
-            image.width,
-            image.height,
-            0,
-            InputImage.IMAGE_FORMAT_NV21
-        )
-        detector.process( inputImage )
-            .addOnSuccessListener { faces ->
-                if ( faces.size != 0 ) {
-                    coroutineScope.launch{
-                        val embedding = getEmbedding( image , faces[ 0 ].boundingBox )
-                        imageData.add( Pair( name , embedding ) )
-                        // Embedding stored, now proceed to the next image.
-                        if ( imageCounter + 1 != numImages ) {
-                            imageCounter += 1
-                            scanImage( data[ imageCounter].first , data[ imageCounter ].second )
-                        }
-                        else {
-                            // Processing done, reset the file reader.
-                            callback.onProcessCompleted( imageData , numImagesWithNoFaces )
-                            reset()
+        mainScope.launch {
+            val inputImage = InputImage.fromByteArray(
+                BitmapUtils.bitmapToNV21ByteArray(image),
+                image.width,
+                image.height,
+                0,
+                InputImage.IMAGE_FORMAT_NV21
+            )
+            detector.process(inputImage)
+                .addOnSuccessListener { faces ->
+                    if (faces.size != 0) {
+                        mainScope.launch {
+                            val embedding = getEmbedding(image, faces[0].boundingBox)
+                            imageData.add(Pair(name, embedding))
+                            // Embedding stored, now proceed to the next image.
+                            if (imageCounter + 1 != numImages) {
+                                imageCounter += 1
+                                scanImage(data[imageCounter].first, data[imageCounter].second)
+                            } else {
+                                // Processing done, reset the file reader.
+                                callback.onProcessCompleted(imageData, numImagesWithNoFaces)
+                                reset()
+                            }
                         }
                     }
-                }
-                else {
-                    // The image contains no faces, proceed to the next one.
-                    numImagesWithNoFaces += 1
-                    if ( imageCounter + 1 != numImages ) {
-                        imageCounter += 1
-                        scanImage( data[ imageCounter].first , data[ imageCounter ].second )
-                    }
                     else {
-                        callback.onProcessCompleted( imageData , numImagesWithNoFaces )
-                        reset()
+                        // The image contains no faces, proceed to the next one.
+                        numImagesWithNoFaces += 1
+                        if (imageCounter + 1 != numImages) {
+                            imageCounter += 1
+                            scanImage(data[imageCounter].first, data[imageCounter].second)
+                        } else {
+                            callback.onProcessCompleted(imageData, numImagesWithNoFaces)
+                            reset()
+                        }
                     }
                 }
-
-            }
+        }
     }
 
     // Suspend function for running the FaceNet model
-    private suspend fun getEmbedding(image: Bitmap, bbox : Rect ) =
-        withContext( Dispatchers.Default ) {
-            return@withContext faceNetModel.getFaceEmbedding( BitmapUtils.cropRectFromBitmap( image , bbox ) )
-        }
+    private suspend fun getEmbedding(image: Bitmap, bbox : Rect ) : FloatArray = withContext( Dispatchers.Default ) {
+        return@withContext faceNetModel.getFaceEmbedding(
+            BitmapUtils.cropRectFromBitmap(
+                image,
+                bbox
+            )
+        )
+    }
 
 
     private fun reset() {

app/src/main/java/com/ml/quaterion/facenetdetection/FrameAnalyser.kt

@@ -92,7 +92,7 @@ class FrameAnalyser( private var context: Context ,
                 boundingBoxOverlay.frameWidth = frameBitmap.width
             }
 
-            val inputImage = InputImage.fromMediaImage( image.image , image.imageInfo.rotationDegrees )
+            val inputImage = InputImage.fromMediaImage(image.image!!, image.imageInfo.rotationDegrees )
             detector.process(inputImage)
                 .addOnSuccessListener { faces ->
                     CoroutineScope( Dispatchers.Default ).launch {

app/src/main/java/com/ml/quaterion/facenetdetection/Logger.kt

@@ -24,7 +24,7 @@ class Logger {
             // To scroll to the last message
             // See this SO answer -> https://stackoverflow.com/a/37806544/10878733
             while ( MainActivity.logTextView.canScrollVertically(1) ) {
-                MainActivity.logTextView.scrollBy(0, 10);
+                MainActivity.logTextView.scrollBy(0, 10)
             }
         }
 

app/src/main/java/com/ml/quaterion/facenetdetection/MainActivity.kt

@@ -111,8 +111,6 @@ class MainActivity : AppCompatActivity() {
         activityMainBinding = ActivityMainBinding.inflate( layoutInflater )
         setContentView( activityMainBinding.root )
 
-        // Implementation of CameraX preview
-
         previewView = activityMainBinding.previewView
         logTextView = activityMainBinding.logTextview
         logTextView.movementMethod = ScrollingMovementMethod()

app/src/main/java/com/ml/quaterion/facenetdetection/model/FaceNetModel.kt

@@ -57,17 +57,17 @@ class FaceNetModel( context : Context ,
         val interpreterOptions = Interpreter.Options().apply {
             // Add the GPU Delegate if supported.
             // See -> https://www.tensorflow.org/lite/performance/gpu#android
-            if ( CompatibilityList().isDelegateSupportedOnThisDevice ) {
-                if ( useGpu ) {
+            if ( useGpu ) {
+                if ( CompatibilityList().isDelegateSupportedOnThisDevice ) {
                     addDelegate( GpuDelegate( CompatibilityList().bestOptionsForThisDevice ))
                 }
             }
             else {
                 // Number of threads for computation
-                setNumThreads( 4 )
+                numThreads = 4
             }
             setUseXNNPACK( useXNNPack )
-            setUseNNAPI(true)
+            useNNAPI = true
         }
         interpreter = Interpreter(FileUtil.loadMappedFile(context, model.assetsFilename ) , interpreterOptions )
         Logger.log("Using ${model.name} model.")

app/src/main/java/com/ml/quaterion/facenetdetection/model/MaskDetectionModel.kt

@@ -44,7 +44,7 @@ class MaskDetectionModel( context: Context ) {
             }
             else {
                 // Number of threads for computation
-                setNumThreads( 4 )
+                numThreads = 4
             }
             setUseXNNPACK(true)
         }
@@ -61,7 +61,7 @@ class MaskDetectionModel( context: Context ) {
     // Kotlin Extension function for arg max.
     // See https://kotlinlang.org/docs/extensions.html
     private fun FloatArray.argmax() : Int {
-        return this.indexOf( this.maxOrNull()!! )
+        return this.indexOfFirst { it == this.maxOrNull()!! }
     }
 
 

app/src/main/java/com/ml/quaterion/facenetdetection/model/ModelInfo.kt

@@ -6,6 +6,4 @@ class ModelInfo(
     val cosineThreshold : Float ,
     val l2Threshold : Float ,
     val outputDims : Int ,
-    val inputDims : Int ) {
-
-}
+    val inputDims : Int )

build.gradle

@@ -1,24 +1,8 @@
 // Top-level build file where you can add configuration options common to all sub-projects/modules.
-
-buildscript {
-    ext.kotlin_version = '1.5.30'
-    repositories {
-        google()
-        mavenCentral()
-    }
-    dependencies {
-        classpath 'com.android.tools.build:gradle:7.2.0'
-        classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
-        // NOTE: Do not place your application dependencies here; they belong
-        // in the individual module build.gradle files
-    }
-}
-
-allprojects {
-    repositories {
-        google()
-        mavenCentral()
-    }
+plugins {
+    id 'com.android.application' version '7.3.0' apply false
+    id 'com.android.library' version '7.3.0' apply false
+    id 'org.jetbrains.kotlin.android' version '1.6.10' apply false
 }
 
 task clean(type: Delete) {

gradle/wrapper/gradle-wrapper.properties

@@ -1,6 +1,6 @@
-#Sun Sep 11 07:35:00 IST 2022
+#Sat Oct 01 09:16:18 IST 2022
 distributionBase=GRADLE_USER_HOME
-distributionUrl=https\://services.gradle.org/distributions/gradle-7.3.3-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-7.4-bin.zip
 distributionPath=wrapper/dists
 zipStorePath=wrapper/dists
 zipStoreBase=GRADLE_USER_HOME

settings.gradle

@@ -1,2 +1,16 @@
+pluginManagement {
+    repositories {
+        gradlePluginPortal()
+        google()
+        mavenCentral()
+    }
+}
+dependencyResolutionManagement {
+    repositoriesMode.set(RepositoriesMode.FAIL_ON_PROJECT_REPOS)
+    repositories {
+        google()
+        mavenCentral()
+    }
+}
 rootProject.name='FaceNet Detection'
 include ':app'