URGENT!!!!! Please HELP!!! Unhandled Exception: PlatformException(Failed to run model, Attempt to invoke virtual method 'org.tensorflow.lite.Tensor org.tensorflow.lite.Interpreter.getInputTensor(int)' on a null object reference, java.lang.NullPointerException: Attempt to invoke virtual method 'org.tensorflow.lite.Tensor org.tensorflow.lite.Interpreter.getInputTensor(int)' on a null object reference

[khaiyue]

This is the whole debugging log shown. This happen after the image is chosen, no matter is from camera or gallery. D/VRI[MainActivity](31231): debugCancelDraw some OnPreDrawListener onPreDraw return false,cancelDraw=true,count=50,android.view.ViewRootImpl@2025556 D/FirebaseAuth(31231): Notifying id token listeners about user ( PCBsXViqy9U628twsSRcGPv1SGW2 ). I/TensorFlowLite(31231): Loaded native library: tensorflowlite_jni I/TensorFlowLite(31231): Didn't load native library: tensorflowlite_jni_gms_client I/tflite (31231): Initialized TensorFlow Lite runtime. W/libc (31231): Access denied finding property "ro.hardware.chipname" I/tflite (31231): Created TensorFlow Lite XNNPACK delegate for CPU. I/Quality (31231): Skipped: false 1 cost 29.663422 refreshRate 16683856 bit true processName com.example.fyp2.fyp2 I/flutter (31231): Failed to load model. D/VRI[MainActivity](31231): registerCallbacksForSync syncBuffer=false D/VRI[MainActivity](31231): Received frameCommittedCallback lastAttemptedDrawFrameNum=1 didProduceBuffer=true syncBuffer=false W/Parcel (31231): Expecting binder but got null! D/VRI[MainActivity](31231): debugCancelDraw cancelDraw=false,count = 220,android.view.ViewRootImpl@2025556 D/VRI[MainActivity](31231): draw finished. I/Quality (31231): TaskTrackInfo {"Pkg":com.example.fyp2.fyp2,"Window":com.example.fyp2.fyp2.MainActivity,"Type":1,"Action":10,"Cost":4135,"FV":16,"JC":16-15-0-1-0-0-1-0-4-1-0-0-0-0-0-0-0-0-1-0-4124-3849-924470182-1538,"SF":no-need,"UITid":31231,"RTid":3532} TTI:Access fail D/VRI[MainActivity](31231): onFocusEvent true D/ProfileInstaller(31231): Installing profile for com.example.fyp2.fyp2 D/OplusInputMethodManagerInternal(31231): get inputMethodManager extension: com.android.internal.view.IInputMethodManager$Stub$Proxy@e971ea8 D/VRI[MainActivity](31231): onFocusEvent false D/CompatibilityChangeReporter(31231): Compat change id reported: 78294732; UID 10446; state: ENABLED D/VRI[MainActivity](31231): onFocusEvent true I/flutter (31231): G O T !!!!!!! Image E/flutter (31231): [ERROR:flutter/runtime/dart_vm_initializer.cc(41)] Unhandled Exception: PlatformException(Failed to run model, Attempt to invoke virtual method 'org.tensorflow.lite.Tensor org.tensorflow.lite.Interpreter.getInputTensor(int)' on a null object reference, java.lang.NullPointerException: Attempt to invoke virtual method 'org.tensorflow.lite.Tensor org.tensorflow.lite.Interpreter.getInputTensor(int)' on a null object reference E/flutter (31231): at sq.flutter.flutter_tflite.TflitePlugin.feedInputTensor(TflitePlugin.java:368) E/flutter (31231): at sq.flutter.flutter_tflite.TflitePlugin.feedInputTensorImage(TflitePlugin.java:430) E/flutter (31231): at sq.flutter.flutter_tflite.TflitePlugin.detectObjectOnImage(TflitePlugin.java:624) E/flutter (31231): at sq.flutter.flutter_tflite.TflitePlugin.onMethodCall(TflitePlugin.java:157) E/flutter (31231): at io.flutter.plugin.common.MethodChannel$IncomingMethodCallHandler.onMessage(MethodChannel.java:267) E/flutter (31231): at io.flutter.embedding.engine.dart.DartMessenger.invokeHandler(DartMessenger.java:292) E/flutter (31231): at io.flutter.embedding.engine.dart.DartMessenger.lambda$dispatchMessageToQueue$0$io-flutter-embedding-engine-dart-DartMessenger(DartMessenger.java:319) E/flutter (31231): at io.flutter.embedding.engine.dart.DartMessenger$$ExternalSyntheticLambda0.run(Unknown Source:12) E/flutter (31231): at android.os.Handler.handleCallback(Handler.java:942) E/flutter (31231): at android.os.Handler.dispatchMessage(Handler.java:99) E/flutter (31231): at android.os.Looper.loopOnce(Looper.java:240) E/flutter (31231): at android.os.Looper.loop(Looper.java:351) E/flutter (31231): at android.app.ActivityThread.main(ActivityThread.java:8377) E/flutter (31231): at java.lang.reflect.Method.invoke(Native Method) E/flutter (31231): at com.android.internal.os.RuntimeInit$MethodAndArgsCaller.run(RuntimeInit.java:584) E/flutter (31231): at com.android.internal.os.ZygoteInit.main(ZygoteInit.java:1013) E/flutter (31231): , null) E/flutter (31231): #0 StandardMethodCodec.decodeEnvelope (package:flutter/src/services/message_codecs.dart:651:7) E/flutter (31231): #1 MethodChannel._invokeMethod (package:flutter/src/services/platform_channel.dart:334:18) E/flutter (31231): <asynchronous suspension> E/flutter (31231): #2 Tflite.detectObjectOnImage (package:flutter_tflite/flutter_tflite.dart:113:12) E/flutter (31231): <asynchronous suspension> E/flutter (31231): #3 _CameraPageState.yolov2Tiny (package:fyp2/views/camera_page.dart:494:24) E/flutter (31231): <asynchronous suspension> E/flutter (31231): #4 _CameraPageState.predictImage (package:fyp2/views/camera_page.dart:421:5) E/flutter (31231): <asynchronous suspension> E/flutter (31231): W/System (31231): A resource failed to call close. W/System (31231): A resource failed to call close.

This is the complete code that I modified based on my use case, but mostly is the similar one. `import 'dart:async'; import 'dart:io'; import 'dart:typed_data'; import 'package:flutter/material.dart'; import 'package:flutter/services.dart'; import 'package:image/image.dart' as img; import 'package:image_picker/image_picker.dart'; import 'package:flutter_tflite/flutter_tflite.dart';

class CameraPage extends StatefulWidget { const CameraPage({super.key});

@override _CameraPageState createState() => _CameraPageState(); }

class _CameraPageState extends State { final ImagePicker _picker = ImagePicker(); XFile? _image; List? _recognitions; late double _imageHeight; late double _imageWidth; bool _busy = false;

Future predictImagePicker(ImageSource source) async { var image = await _picker.pickImage(source: source); if (image == null) { ScaffoldMessenger.of(context).showSnackBar( const SnackBar(content: Text("Image selection cancelled"))); return; } print('G O T !!!!!!! Image'); setState(() { _busy = true; }); predictImage(image); }

Future predictImage(XFile image) async { await yolov2Tiny(image);

FileImage(File(image.path))
    .resolve(const ImageConfiguration())
    .addListener(ImageStreamListener((ImageInfo info, bool _) {
  setState(() {
    _imageHeight = info.image.height.toDouble();
    _imageWidth = info.image.width.toDouble();
  });
}));

setState(() {
  _image = image;
  _busy = false;
});

}

@override void initState() { super.initState(); _busy = true;

loadModel().then((val) {
  setState(() {
    _busy = false;
  });
});

}

Future loadModel() async { Tflite.close(); try { String res = (await Tflite.loadModel( model: "assets/best-int8.tflite", labels: "assets/labels.txt", numThreads: 4, isAsset: true, useGpuDelegate: false, ))!; print('Load successfully'); } on PlatformException { print('Failed to load model.'); } }

Uint8List imageToByteListFloat32( img.Image image, int inputSize, double mean, double std) { var convertedBytes = Float32List(1 inputSize inputSize * 3); var buffer = Float32List.view(convertedBytes.buffer); int pixelIndex = 0; for (var i = 0; i < inputSize; i++) { for (var j = 0; j < inputSize; j++) { var pixel = image.getPixel(j, i); buffer[pixelIndex++] = (img.getRed(pixel) - mean) / std; buffer[pixelIndex++] = (img.getGreen(pixel) - mean) / std; buffer[pixelIndex++] = (img.getBlue(pixel) - mean) / std; } } return convertedBytes.buffer.asUint8List(); }

Future yolov2Tiny(XFile image) async { int startTime = DateTime.now().millisecondsSinceEpoch; var recognitions = await Tflite.detectObjectOnImage( path: image.path, model: "YOLO", threshold: 0.3, imageMean: 0.0, imageStd: 255.0, numResultsPerClass: 3, asynch: true, ); setState(() { _recognitions = recognitions!; }); int endTime = DateTime.now().millisecondsSinceEpoch; print("Inference took ${endTime - startTime}ms"); }

List renderBoxes(Size screen) { if (_recognitions == null) return []; double factorX = screen.width; double factorY = _imageHeight / _imageWidth screen.width; Color blue = const Color.fromRGBO(37, 213, 253, 1.0); return _recognitions!.map((re) { return Positioned( left: re["rect"]["x"] factorX, top: re["rect"]["y"] factorY, width: re["rect"]["w"] factorX, height: re["rect"]["h"] factorY, child: Container( decoration: BoxDecoration( borderRadius: const BorderRadius.all(Radius.circular(8.0)), border: Border.all( color: blue, width: 2, ), ), child: Text( "${re["detectedClass"]} ${(re["confidenceInClass"] 100).toStringAsFixed(0)}%", style: TextStyle( background: Paint()..color = blue, color: Colors.white, fontSize: 12.0, ), ), ), ); }).toList(); }

@override Widget build(BuildContext context) { Size size = MediaQuery.of(context).size; List stackChildren = [];

if(_image != null){
  stackChildren.add(Positioned(
    top: 0.0,
    left: 0.0,
    width: size.width,
    child: Image.file(File(_image?.path ?? '')),
  ));
}

if (_busy) {
  stackChildren.add(const Opacity(
    opacity: 0.3,
    child: ModalBarrier(dismissible: false, color: Colors.grey),
  ));
  stackChildren.add(const Center(child: CircularProgressIndicator()));
}

if (_recognitions != null && _recognitions!.isNotEmpty) {
  stackChildren.addAll(renderBoxes(size));
}

return MaterialApp(
  home: Scaffold(
    appBar: AppBar(
      title: const Text('Scan Ingredients'),
    ),
    body: Center(
      child: Column(
        mainAxisAlignment: MainAxisAlignment.center,
        children: [
          ElevatedButton.icon(
            onPressed: (){predictImagePicker(ImageSource.camera);},
            icon: const Icon(Icons.camera, size: 24.0,),
            label: const Text('Capture image with camera'),
          ),
          const SizedBox(height: 16),
          ElevatedButton.icon(
            onPressed: (){predictImagePicker(ImageSource.gallery);},
            icon: const Icon(Icons.image, size: 24.0,),
            label: const Text('Choose from Gallery'),
          ),
        ],
      ),
    ),
  ),
);

} }`