Fix emulator crash by adding runtime JNI loading check and fallback for MediaPipe Tasks Vision

android-project/app/src/main/java/com/photobooth/app/MainActivity.kt

@@ -67,10 +67,13 @@ class MainActivity : AppCompatActivity() {
     private lateinit var backgroundOptions: List<BackgroundOption>
     private val aiInferenceLock = Any()
     private var imageSegmenter: ImageSegmenter? = null
+    private var isAiSupported = true
 
-    private fun getImageSegmenter(): ImageSegmenter {
+    private fun getImageSegmenter(): ImageSegmenter? {
         synchronized(aiInferenceLock) {
+            if (!isAiSupported) return null
             if (imageSegmenter == null) {
+                try {
                     val baseOptions = BaseOptions.builder()
                         .setModelAssetPath("models/multiclass_segmenter.tflite")
                         .build()
@@ -82,16 +85,31 @@ class MainActivity : AppCompatActivity() {
                         .build()
 
                     imageSegmenter = ImageSegmenter.createFromOptions(this, options)
+                } catch (e: UnsatisfiedLinkError) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Không hỗ trợ xử lý AI trên thiết bị/emulator này (thiếu thư viện Native JNI)", Toast.LENGTH_LONG).show()
                     }
-            return imageSegmenter!!
+                    return null
+                } catch (e: Exception) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Lỗi khởi tạo AI Segmenter: ${e.message}", Toast.LENGTH_LONG).show()
+                    }
+                    return null
+                }
+            }
+            return imageSegmenter
         }
     }
 
     private var tfliteInterpreter: org.tensorflow.lite.Interpreter? = null
 
-    private fun getTfliteInterpreter(): org.tensorflow.lite.Interpreter {
+    private fun getTfliteInterpreter(): org.tensorflow.lite.Interpreter? {
         synchronized(aiInferenceLock) {
+            if (!isAiSupported) return null
             if (tfliteInterpreter == null) {
+                try {
                     val assetFileDescriptor = assets.openFd("models/midas.tflite")
                     val inputStream = java.io.FileInputStream(assetFileDescriptor.fileDescriptor)
                     val fileChannel = inputStream.channel
@@ -102,13 +120,26 @@ class MainActivity : AppCompatActivity() {
                     val options = org.tensorflow.lite.Interpreter.Options()
                     options.setNumThreads(4)
                     tfliteInterpreter = org.tensorflow.lite.Interpreter(modelBuffer, options)
+                } catch (e: UnsatisfiedLinkError) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Không hỗ trợ xử lý Depth trên thiết bị/emulator này (thiếu thư viện Native JNI)", Toast.LENGTH_LONG).show()
                     }
-            return tfliteInterpreter!!
+                    return null
+                } catch (e: Exception) {
+                    isAiSupported = false
+                    runOnUiThread {
+                        Toast.makeText(this, "Lỗi khởi tạo Depth Interpreter: ${e.message}", Toast.LENGTH_LONG).show()
+                    }
+                    return null
+                }
+            }
+            return tfliteInterpreter
         }
     }
 
     private fun runDepthInference(bitmap: android.graphics.Bitmap): FloatArray {
-        val interpreter = getTfliteInterpreter()
+        val interpreter = getTfliteInterpreter() ?: return FloatArray(256 * 256)
         
         // Input: 256x256 RGB
         val scaled = android.graphics.Bitmap.createScaledBitmap(bitmap, 256, 256, true)
@@ -1713,11 +1744,29 @@ class MainActivity : AppCompatActivity() {
             return capturedImage
         }
 
+        if (!isAiSupported) {
+            if (blurIntensity > 0f) {
+                val radius = (25 * blurIntensity).toInt().coerceIn(1, 25)
+                return blurBitmap(capturedImage, radius)
+            }
+            return capturedImage
+        }
+        
         try {
+            val segmenter = getImageSegmenter()
+            val interpreter = getTfliteInterpreter()
+            if (segmenter == null || interpreter == null) {
+                if (blurIntensity > 0f) {
+                    val radius = (25 * blurIntensity).toInt().coerceIn(1, 25)
+                    return blurBitmap(capturedImage, radius)
+                }
+                return capturedImage
+            }
+
             // 1. Run MediaPipe Multiclass Image Segmentation to locate subject
             val mpImage = com.google.mediapipe.framework.image.BitmapImageBuilder(capturedImage).build()
             val segmentationResult = synchronized(aiInferenceLock) {
-                getImageSegmenter().segment(mpImage)
+                segmenter.segment(mpImage)
             }
             val categoryMaskOptional = segmentationResult.categoryMask()
             if (!categoryMaskOptional.isPresent) {