file not displayed

build.gradle

@@ -25,7 +25,7 @@ buildscript {
 
         // 4.1.0-alpha10 or above and Android Studio 4.1 Canary 10 or above is required for
         // TensorFlow Lite / Machine Learning (ML) binding
-        classpath 'com.android.tools.build:gradle:4.1.0-rc03'
+        classpath 'com.android.tools.build:gradle:7.0.2'
         classpath "org.jetbrains.kotlin:kotlin-gradle-plugin:$kotlin_version"
 
     }

finish/src/main/java/org/tensorflow/lite/examples/classification/MainActivity.kt

@@ -50,7 +50,7 @@ import java.util.concurrent.Executors
 import org.tensorflow.lite.gpu.CompatibilityList
 
 // Constants
-private const val MAX_RESULT_DISPLAY = 3 // Maximum number of results displayed
+private const val MAX_RESULT_DISPLAY = 1 // Maximum number of results displayed
 private const val TAG = "TFL Classify" // Name for logging
 private const val REQUEST_CODE_PERMISSIONS = 999 // Return code after asking for permission
 private val REQUIRED_PERMISSIONS = arrayOf(Manifest.permission.CAMERA) // permission needed

gradle/wrapper/gradle-wrapper.properties

@@ -19,4 +19,4 @@ distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
 zipStoreBase=GRADLE_USER_HOME
 zipStorePath=wrapper/dists
-distributionUrl=https\://services.gradle.org/distributions/gradle-6.5-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-7.0.2-bin.zip

start/build.gradle

@@ -55,6 +55,7 @@ android {
     // Enable data binding
     buildFeatures{
         dataBinding = true
+        mlModelBinding true
     }
 
 }
@@ -66,6 +67,9 @@ dependencies {
     implementation 'androidx.core:core-ktx:1.3.2'
     implementation 'androidx.appcompat:appcompat:1.2.0'
     implementation 'com.google.android.material:material:1.2.1'
+    implementation 'org.tensorflow:tensorflow-lite-support:0.1.0-rc1'
+    implementation "androidx.recyclerview:recyclerview:1.1.0"
+    implementation 'org.tensorflow:tensorflow-lite-metadata:0.1.0-rc1'
 
     // Import for CameraX
     def camerax_version = "1.0.0-beta10"
@@ -78,7 +82,7 @@ dependencies {
     implementation "androidx.activity:activity-ktx:1.1.0"
 
     // TODO 5: Optional GPU Delegates
-
+    implementation 'org.tensorflow:tensorflow-lite-gpu:2.3.0'
 
     testImplementation 'junit:junit:4.13'
     androidTestImplementation 'androidx.test.ext:junit:1.1.2'

start/src/main/java/org/tensorflow/lite/examples/classification/MainActivity.kt

@@ -39,15 +39,19 @@ import androidx.core.app.ActivityCompat
 import androidx.core.content.ContextCompat
 import androidx.lifecycle.Observer
 import androidx.recyclerview.widget.RecyclerView
+import org.tensorflow.lite.examples.classification.ml.FlowerModel
 import org.tensorflow.lite.examples.classification.ui.RecognitionAdapter
 import org.tensorflow.lite.examples.classification.util.YuvToRgbConverter
 import org.tensorflow.lite.examples.classification.viewmodel.Recognition
 import org.tensorflow.lite.examples.classification.viewmodel.RecognitionListViewModel
+import org.tensorflow.lite.gpu.CompatibilityList
+import org.tensorflow.lite.schema.Model
+import org.tensorflow.lite.support.image.TensorImage
 import java.util.concurrent.Executors
 import kotlin.random.Random
 
 // Constants
-private const val MAX_RESULT_DISPLAY = 3 // Maximum number of results displayed
+private const val MAX_RESULT_DISPLAY = 1 // Maximum number of results displayed
 private const val TAG = "TFL Classify" // Name for logging
 private const val REQUEST_CODE_PERMISSIONS = 999 // Return code after asking for permission
 private val REQUIRED_PERMISSIONS = arrayOf(Manifest.permission.CAMERA) // permission needed
@@ -209,24 +213,43 @@ class MainActivity : AppCompatActivity() {
         // TODO 1: Add class variable TensorFlow Lite Model
         // Initializing the flowerModel by lazy so that it runs in the same thread when the process
         // method is called.
+        private val flowerModel: FlowerModel by lazy {
+            // TODO 6. Optional GPU acceleration
+            val compatList = CompatibilityList()
+
+            val options = if (compatList.isDelegateSupportedOnThisDevice) {
+                Log.d(TAG, "This device is GPU compatible ")
+                org.tensorflow.lite.support.model.Model.Options.Builder().setDevice(org.tensorflow.lite.support.model.Model.Device.GPU).build()
+            } else {
+                Log.d(TAG, "This device is GPU incompatible ")
+                org.tensorflow.lite.support.model.Model.Options.Builder().setNumThreads(4).build()
+            }
+            FlowerModel.newInstance(ctx,options)
+        }
+
+
 
-        // TODO 6. Optional GPU acceleration
 
 
         override fun analyze(imageProxy: ImageProxy) {
 
             val items = mutableListOf<Recognition>()
 
             // TODO 2: Convert Image to Bitmap then to TensorImage
+            val tfImage = TensorImage.fromBitmap(toBitmap(imageProxy))
 
             // TODO 3: Process the image using the trained model, sort and pick out the top results
-
+            val outputs = flowerModel.process(tfImage).probabilityAsCategoryList.apply {
+                sortByDescending { it.score }
+            }.take(MAX_RESULT_DISPLAY)
             // TODO 4: Converting the top probability items into a list of recognitions
-
-            // START - Placeholder code at the start of the codelab. Comment this block of code out.
-            for (i in 0 until MAX_RESULT_DISPLAY){
-                items.add(Recognition("Fake label $i", Random.nextFloat()))
+            for (output in outputs){
+                items.add(Recognition(output.label, output.score))
             }
+            // START - Placeholder code at the start of the codelab. Comment this block of code out.
+//            for (i in 0 until MAX_RESULT_DISPLAY){
+//                items.add(Recognition("Fake label $i", Random.nextFloat()))
+//            }
             // END - Placeholder code at the start of the codelab. Comment this block of code out.
 
             // Return the result