[mob][photos] Cleanup face detection service

mobile/lib/services/machine_learning/face_ml/face_detection/face_detection_service.dart

@@ -1,12 +1,10 @@
 import "dart:async";
 import "dart:developer" as dev show log;
 import "dart:io" show File;
-import "dart:isolate";
+import 'dart:typed_data' show ByteData;
-import 'dart:typed_data' show ByteData, Float32List, Uint8List;
 import 'dart:ui' as ui show Image;
 
 import "package:computer/computer.dart";
-import 'package:flutter/material.dart';
 import 'package:logging/logging.dart';
 import 'package:onnxruntime/onnxruntime.dart';
 import "package:photos/face/model/dimension.dart";
@@ -15,15 +13,11 @@ import 'package:photos/services/machine_learning/face_ml/face_detection/face_det
 import 'package:photos/services/machine_learning/face_ml/face_detection/naive_non_max_suppression.dart';
 import 'package:photos/services/machine_learning/face_ml/face_detection/yolo_filter_extract_detections.dart';
 import "package:photos/services/remote_assets_service.dart";
-import "package:photos/utils/image_ml_isolate.dart";
 import "package:photos/utils/image_ml_util.dart";
-import "package:synchronized/synchronized.dart";
-
-enum FaceDetectionOperation { yoloInferenceAndPostProcessing }
 
 /// This class is responsible for running the face detection model (YOLOv5Face) on ONNX runtime, and can be accessed through the singleton instance [FaceDetectionService.instance].
 class FaceDetectionService {
-  static final _logger = Logger('YOLOFaceDetectionService');
+  static final _logger = Logger('FaceDetectionService');
 
   final _computer = Computer.shared();
 
@@ -32,7 +26,6 @@ class FaceDetectionService {
   static const String kModelBucketEndpoint = "https://models.ente.io/";
   static const String kRemoteBucketModelPath =
       "yolov5s_face_640_640_dynamic.onnx";
-  // static const kRemoteBucketModelPath = "yolov5n_face_640_640.onnx";
   static const String modelRemotePath =
       kModelBucketEndpoint + kRemoteBucketModelPath;
 
@@ -44,23 +37,8 @@ class FaceDetectionService {
 
   bool isInitialized = false;
 
-  // Isolate things
+  // Singleton pattern
-  Timer? _inactivityTimer;
-  final Duration _inactivityDuration = const Duration(seconds: 30);
-
-  final _initLock = Lock();
-  final _computerLock = Lock();
-
-  late Isolate _isolate;
-  late ReceivePort _receivePort = ReceivePort();
-  late SendPort _mainSendPort;
-
-  bool isSpawned = false;
-  bool isRunning = false;
-
-  // singleton pattern
   FaceDetectionService._privateConstructor();
-
   /// Use this instance to access the FaceDetection service. Make sure to call `init()` before using it.
   /// e.g. `await FaceDetection.instance.init();`
   ///
@@ -68,7 +46,6 @@ class FaceDetectionService {
   ///
   /// config options: yoloV5FaceN //
   static final instance = FaceDetectionService._privateConstructor();
-
   factory FaceDetectionService() => instance;
 
   /// Check if the interpreter is initialized, if not initialize it with `loadModel()`
@@ -78,7 +55,6 @@ class FaceDetectionService {
       final model =
           await RemoteAssetsService.instance.getAsset(modelRemotePath);
       final startTime = DateTime.now();
-      // Doing this from main isolate since `rootBundle` cannot be accessed outside it
       sessionAddress = await _computer.compute(
         _loadModel,
         param: {
@@ -104,222 +80,8 @@ class FaceDetectionService {
     }
   }
 
-  Future<void> initIsolate() async {
-    return _initLock.synchronized(() async {
-      if (isSpawned) return;
-
-      _receivePort = ReceivePort();
-
-      try {
-        _isolate = await Isolate.spawn(
-          _isolateMain,
-          _receivePort.sendPort,
-        );
-        _mainSendPort = await _receivePort.first as SendPort;
-        isSpawned = true;
-
-        _resetInactivityTimer();
-      } catch (e) {
-        _logger.severe('Could not spawn isolate', e);
-        isSpawned = false;
-      }
-    });
-  }
-
-  Future<void> ensureSpawnedIsolate() async {
-    if (!isSpawned) {
-      await initIsolate();
-    }
-  }
-
-  /// The main execution function of the isolate.
-  static void _isolateMain(SendPort mainSendPort) async {
-    final receivePort = ReceivePort();
-    mainSendPort.send(receivePort.sendPort);
-
-    receivePort.listen((message) async {
-      final functionIndex = message[0] as int;
-      final function = FaceDetectionOperation.values[functionIndex];
-      final args = message[1] as Map<String, dynamic>;
-      final sendPort = message[2] as SendPort;
-
-      try {
-        switch (function) {
-          case FaceDetectionOperation.yoloInferenceAndPostProcessing:
-            final inputImageList = args['inputImageList'] as Float32List;
-            final inputShape = args['inputShape'] as List<int>;
-            final newSize = args['newSize'] as Dimensions;
-            final sessionAddress = args['sessionAddress'] as int;
-            final timeSentToIsolate = args['timeNow'] as DateTime;
-            final delaySentToIsolate =
-                DateTime.now().difference(timeSentToIsolate).inMilliseconds;
-
-            final Stopwatch stopwatchPrepare = Stopwatch()..start();
-            final inputOrt = OrtValueTensor.createTensorWithDataList(
-              inputImageList,
-              inputShape,
-            );
-            final inputs = {'input': inputOrt};
-            stopwatchPrepare.stop();
-            dev.log(
-              '[YOLOFaceDetectionService] data preparation is finished, in ${stopwatchPrepare.elapsedMilliseconds}ms',
-            );
-
-            stopwatchPrepare.reset();
-            stopwatchPrepare.start();
-            final runOptions = OrtRunOptions();
-            final session = OrtSession.fromAddress(sessionAddress);
-            stopwatchPrepare.stop();
-            dev.log(
-              '[YOLOFaceDetectionService] session preparation is finished, in ${stopwatchPrepare.elapsedMilliseconds}ms',
-            );
-
-            final stopwatchInterpreter = Stopwatch()..start();
-            late final List<OrtValue?> outputs;
-            try {
-              outputs = session.run(runOptions, inputs);
-            } catch (e, s) {
-              dev.log(
-                '[YOLOFaceDetectionService] Error while running inference: $e \n $s',
-              );
-              throw YOLOFaceInterpreterRunException();
-            }
-            stopwatchInterpreter.stop();
-            dev.log(
-              '[YOLOFaceDetectionService] interpreter.run is finished, in ${stopwatchInterpreter.elapsedMilliseconds} ms',
-            );
-
-            final relativeDetections =
-                _yoloPostProcessOutputs(outputs, newSize);
-
-            sendPort
-                .send((relativeDetections, delaySentToIsolate, DateTime.now()));
-            break;
-        }
-      } catch (e, stackTrace) {
-        sendPort
-            .send({'error': e.toString(), 'stackTrace': stackTrace.toString()});
-      }
-    });
-  }
-
-  /// The common method to run any operation in the isolate. It sends the [message] to [_isolateMain] and waits for the result.
-  Future<dynamic> _runInIsolate(
-    (FaceDetectionOperation, Map<String, dynamic>) message,
-  ) async {
-    await ensureSpawnedIsolate();
-    _resetInactivityTimer();
-    final completer = Completer<dynamic>();
-    final answerPort = ReceivePort();
-
-    _mainSendPort.send([message.$1.index, message.$2, answerPort.sendPort]);
-
-    answerPort.listen((receivedMessage) {
-      if (receivedMessage is Map && receivedMessage.containsKey('error')) {
-        // Handle the error
-        final errorMessage = receivedMessage['error'];
-        final errorStackTrace = receivedMessage['stackTrace'];
-        final exception = Exception(errorMessage);
-        final stackTrace = StackTrace.fromString(errorStackTrace);
-        completer.completeError(exception, stackTrace);
-      } else {
-        completer.complete(receivedMessage);
-      }
-    });
-
-    return completer.future;
-  }
-
-  /// Resets a timer that kills the isolate after a certain amount of inactivity.
-  ///
-  /// Should be called after initialization (e.g. inside `init()`) and after every call to isolate (e.g. inside `_runInIsolate()`)
-  void _resetInactivityTimer() {
-    _inactivityTimer?.cancel();
-    _inactivityTimer = Timer(_inactivityDuration, () {
-      _logger.info(
-        'Face detection (YOLO ONNX) Isolate has been inactive for ${_inactivityDuration.inSeconds} seconds. Killing isolate.',
-      );
-      disposeIsolate();
-    });
-  }
-
-  /// Disposes the isolate worker.
-  void disposeIsolate() {
-    if (!isSpawned) return;
-
-    isSpawned = false;
-    _isolate.kill();
-    _receivePort.close();
-    _inactivityTimer?.cancel();
-  }
-
   /// Detects faces in the given image data.
-  Future<(List<FaceDetectionRelative>, Dimensions)> predict(
+  static Future<(List<FaceDetectionRelative>, Dimensions)> predict(
-    Uint8List imageData,
-  ) async {
-    assert(isInitialized);
-
-    final stopwatch = Stopwatch()..start();
-
-    final stopwatchDecoding = Stopwatch()..start();
-    final (inputImageList, originalSize, newSize) =
-        await ImageMlIsolate.instance.preprocessImageYoloOnnx(
-      imageData,
-      normalize: true,
-      requiredWidth: kInputWidth,
-      requiredHeight: kInputHeight,
-      maintainAspectRatio: true,
-      quality: FilterQuality.medium,
-    );
-
-    // final input = [inputImageList];
-    final inputShape = [
-      1,
-      3,
-      kInputHeight,
-      kInputWidth,
-    ];
-    final inputOrt = OrtValueTensor.createTensorWithDataList(
-      inputImageList,
-      inputShape,
-    );
-    final inputs = {'input': inputOrt};
-    stopwatchDecoding.stop();
-    _logger.info(
-      'Image decoding and preprocessing is finished, in ${stopwatchDecoding.elapsedMilliseconds}ms',
-    );
-    _logger.info('original size: $originalSize \n new size: $newSize');
-
-    // Run inference
-    final stopwatchInterpreter = Stopwatch()..start();
-    List<OrtValue?>? outputs;
-    try {
-      final runOptions = OrtRunOptions();
-      final session = OrtSession.fromAddress(sessionAddress);
-      outputs = session.run(runOptions, inputs);
-      // inputOrt.release();
-      // runOptions.release();
-    } catch (e, s) {
-      _logger.severe('Error while running inference: $e \n $s');
-      throw YOLOFaceInterpreterRunException();
-    }
-    stopwatchInterpreter.stop();
-    _logger.info(
-      'interpreter.run is finished, in ${stopwatchInterpreter.elapsedMilliseconds} ms',
-    );
-
-    final relativeDetections = _yoloPostProcessOutputs(outputs, newSize);
-
-    stopwatch.stop();
-    _logger.info(
-      'predict() face detection executed in ${stopwatch.elapsedMilliseconds}ms',
-    );
-
-    return (relativeDetections, originalSize);
-  }
-
-  /// Detects faces in the given image data.
-  static Future<(List<FaceDetectionRelative>, Dimensions)> predictSync(
     ui.Image image,
     ByteData imageByteData,
     int sessionAddress,
@@ -339,7 +101,6 @@ class FaceDetectionService {
       maintainAspectRatio: true,
     );
 
-    // final input = [inputImageList];
     final inputShape = [
       1,
       3,
@@ -388,274 +149,6 @@ class FaceDetectionService {
     return (relativeDetections, originalSize);
   }
 
-  /// Detects faces in the given image data.
-  Future<(List<FaceDetectionRelative>, Dimensions)> predictInIsolate(
-    Uint8List imageData,
-  ) async {
-    await ensureSpawnedIsolate();
-    assert(isInitialized);
-
-    _logger.info('predictInIsolate() is called');
-
-    final stopwatch = Stopwatch()..start();
-
-    final stopwatchDecoding = Stopwatch()..start();
-    final (inputImageList, originalSize, newSize) =
-        await ImageMlIsolate.instance.preprocessImageYoloOnnx(
-      imageData,
-      normalize: true,
-      requiredWidth: kInputWidth,
-      requiredHeight: kInputHeight,
-      maintainAspectRatio: true,
-      quality: FilterQuality.medium,
-    );
-    // final input = [inputImageList];
-    final inputShape = [
-      1,
-      3,
-      kInputHeight,
-      kInputWidth,
-    ];
-
-    stopwatchDecoding.stop();
-    _logger.info(
-      'Image decoding and preprocessing is finished, in ${stopwatchDecoding.elapsedMilliseconds}ms',
-    );
-    _logger.info('original size: $originalSize \n new size: $newSize');
-
-    final (
-      List<FaceDetectionRelative> relativeDetections,
-      delaySentToIsolate,
-      timeSentToMain
-    ) = await _runInIsolate(
-      (
-        FaceDetectionOperation.yoloInferenceAndPostProcessing,
-        {
-          'inputImageList': inputImageList,
-          'inputShape': inputShape,
-          'newSize': newSize,
-          'sessionAddress': sessionAddress,
-          'timeNow': DateTime.now(),
-        }
-      ),
-    ) as (List<FaceDetectionRelative>, int, DateTime);
-
-    final delaySentToMain =
-        DateTime.now().difference(timeSentToMain).inMilliseconds;
-
-    stopwatch.stop();
-    _logger.info(
-      'predictInIsolate() face detection executed in ${stopwatch.elapsedMilliseconds}ms, with ${delaySentToIsolate}ms delay sent to isolate, and ${delaySentToMain}ms delay sent to main, for a total of ${delaySentToIsolate + delaySentToMain}ms delay due to isolate',
-    );
-
-    return (relativeDetections, originalSize);
-  }
-
-  Future<(List<FaceDetectionRelative>, Dimensions)> predictInComputer(
-    String imagePath,
-  ) async {
-    assert(isInitialized);
-
-    _logger.info('predictInComputer() is called');
-
-    final stopwatch = Stopwatch()..start();
-
-    final stopwatchDecoding = Stopwatch()..start();
-    final imageData = await File(imagePath).readAsBytes();
-    final (inputImageList, originalSize, newSize) =
-        await ImageMlIsolate.instance.preprocessImageYoloOnnx(
-      imageData,
-      normalize: true,
-      requiredWidth: kInputWidth,
-      requiredHeight: kInputHeight,
-      maintainAspectRatio: true,
-      quality: FilterQuality.medium,
-    );
-    // final input = [inputImageList];
-    return await _computerLock.synchronized(() async {
-      final inputShape = [
-        1,
-        3,
-        kInputHeight,
-        kInputWidth,
-      ];
-
-      stopwatchDecoding.stop();
-      _logger.info(
-        'Image decoding and preprocessing is finished, in ${stopwatchDecoding.elapsedMilliseconds}ms',
-      );
-      _logger.info('original size: $originalSize \n new size: $newSize');
-
-      final (
-        List<FaceDetectionRelative> relativeDetections,
-        delaySentToIsolate,
-        timeSentToMain
-      ) = await _computer.compute(
-        inferenceAndPostProcess,
-        param: {
-          'inputImageList': inputImageList,
-          'inputShape': inputShape,
-          'newSize': newSize,
-          'sessionAddress': sessionAddress,
-          'timeNow': DateTime.now(),
-        },
-      ) as (List<FaceDetectionRelative>, int, DateTime);
-
-      final delaySentToMain =
-          DateTime.now().difference(timeSentToMain).inMilliseconds;
-
-      stopwatch.stop();
-      _logger.info(
-        'predictInIsolate() face detection executed in ${stopwatch.elapsedMilliseconds}ms, with ${delaySentToIsolate}ms delay sent to isolate, and ${delaySentToMain}ms delay sent to main, for a total of ${delaySentToIsolate + delaySentToMain}ms delay due to isolate',
-      );
-
-      return (relativeDetections, originalSize);
-    });
-  }
-
-  /// Detects faces in the given image data.
-  /// This method is optimized for batch processing.
-  ///
-  /// `imageDataList`: The image data to analyze.
-  ///
-  /// WARNING: Currently this method only returns the detections for the first image in the batch.
-  /// Change the function to output all detection before actually using it in production.
-  Future<List<FaceDetectionRelative>> predictBatch(
-    List<Uint8List> imageDataList,
-  ) async {
-    assert(isInitialized);
-
-    final stopwatch = Stopwatch()..start();
-
-    final stopwatchDecoding = Stopwatch()..start();
-    final List<Float32List> inputImageDataLists = [];
-    final List<(Dimensions, Dimensions)> originalAndNewSizeList = [];
-    int concatenatedImageInputsLength = 0;
-    for (final imageData in imageDataList) {
-      final (inputImageList, originalSize, newSize) =
-          await ImageMlIsolate.instance.preprocessImageYoloOnnx(
-        imageData,
-        normalize: true,
-        requiredWidth: kInputWidth,
-        requiredHeight: kInputHeight,
-        maintainAspectRatio: true,
-        quality: FilterQuality.medium,
-      );
-      inputImageDataLists.add(inputImageList);
-      originalAndNewSizeList.add((originalSize, newSize));
-      concatenatedImageInputsLength += inputImageList.length;
-    }
-
-    final inputImageList = Float32List(concatenatedImageInputsLength);
-
-    int offset = 0;
-    for (int i = 0; i < inputImageDataLists.length; i++) {
-      final inputImageData = inputImageDataLists[i];
-      inputImageList.setRange(
-        offset,
-        offset + inputImageData.length,
-        inputImageData,
-      );
-      offset += inputImageData.length;
-    }
-
-    // final input = [inputImageList];
-    final inputShape = [
-      inputImageDataLists.length,
-      3,
-      kInputHeight,
-      kInputWidth,
-    ];
-    final inputOrt = OrtValueTensor.createTensorWithDataList(
-      inputImageList,
-      inputShape,
-    );
-    final inputs = {'input': inputOrt};
-    stopwatchDecoding.stop();
-    _logger.info(
-      'Image decoding and preprocessing is finished, in ${stopwatchDecoding.elapsedMilliseconds}ms',
-    );
-    // _logger.info('original size: $originalSize \n new size: $newSize');
-
-    _logger.info('interpreter.run is called');
-    // Run inference
-    final stopwatchInterpreter = Stopwatch()..start();
-    List<OrtValue?>? outputs;
-    try {
-      final runOptions = OrtRunOptions();
-      final session = OrtSession.fromAddress(sessionAddress);
-      outputs = session.run(runOptions, inputs);
-      inputOrt.release();
-      runOptions.release();
-    } catch (e, s) {
-      _logger.severe('Error while running inference: $e \n $s');
-      throw YOLOFaceInterpreterRunException();
-    }
-    stopwatchInterpreter.stop();
-    _logger.info(
-      'interpreter.run is finished, in ${stopwatchInterpreter.elapsedMilliseconds} ms, or ${stopwatchInterpreter.elapsedMilliseconds / inputImageDataLists.length} ms per image',
-    );
-
-    _logger.info('outputs: $outputs');
-
-    const int imageOutputToUse = 0;
-
-    // // Get output tensors
-    final nestedResults =
-        outputs[0]?.value as List<List<List<double>>>; // [b, 25200, 16]
-    final selectedResults = nestedResults[imageOutputToUse]; // [25200, 16]
-
-    // final rawScores = <double>[];
-    // for (final result in firstResults) {
-    //   rawScores.add(result[4]);
-    // }
-    // final rawScoresCopy = List<double>.from(rawScores);
-    // rawScoresCopy.sort();
-    // _logger.info('rawScores minimum: ${rawScoresCopy.first}');
-    // _logger.info('rawScores maximum: ${rawScoresCopy.last}');
-
-    var relativeDetections = yoloOnnxFilterExtractDetections(
-      kMinScoreSigmoidThreshold,
-      kInputWidth,
-      kInputHeight,
-      results: selectedResults,
-    );
-
-    // Release outputs
-    for (var element in outputs) {
-      element?.release();
-    }
-
-    // Account for the fact that the aspect ratio was maintained
-    for (final faceDetection in relativeDetections) {
-      faceDetection.correctForMaintainedAspectRatio(
-        const Dimensions(
-          width: kInputWidth,
-          height: kInputHeight,
-        ),
-        originalAndNewSizeList[imageOutputToUse].$2,
-      );
-    }
-
-    // Non-maximum suppression to remove duplicate detections
-    relativeDetections = naiveNonMaxSuppression(
-      detections: relativeDetections,
-      iouThreshold: kIouThreshold,
-    );
-
-    if (relativeDetections.isEmpty) {
-      _logger.info('No face detected');
-      return <FaceDetectionRelative>[];
-    }
-
-    stopwatch.stop();
-    _logger.info(
-      'predict() face detection executed in ${stopwatch.elapsedMilliseconds}ms',
-    );
-
-    return relativeDetections;
-  }
-
   static List<FaceDetectionRelative> _yoloPostProcessOutputs(
     List<OrtValue?>? outputs,
     Dimensions newSize,
@@ -665,15 +158,7 @@ class FaceDetectionService {
         outputs?[0]?.value as List<List<List<double>>>; // [1, 25200, 16]
     final firstResults = nestedResults[0]; // [25200, 16]
 
-    // final rawScores = <double>[];
+    // Filter output
-    // for (final result in firstResults) {
-    //   rawScores.add(result[4]);
-    // }
-    // final rawScoresCopy = List<double>.from(rawScores);
-    // rawScoresCopy.sort();
-    // _logger.info('rawScores minimum: ${rawScoresCopy.first}');
-    // _logger.info('rawScores maximum: ${rawScoresCopy.last}');
-
     var relativeDetections = yoloOnnxFilterExtractDetections(
       kMinScoreSigmoidThreshold,
       kInputWidth,
@@ -713,13 +198,11 @@ class FaceDetectionService {
       ..setIntraOpNumThreads(1)
       ..setSessionGraphOptimizationLevel(GraphOptimizationLevel.ortEnableAll);
     try {
-      // _logger.info('Loading face embedding model');
       final session =
           OrtSession.fromFile(File(args["modelPath"]), sessionOptions);
-      // _logger.info('Face embedding model loaded');
       return session.address;
-    } catch (e, _) {
+    } catch (e, s) {
-      // _logger.severe('Face embedding model not loaded', e, s);
+      _logger.severe('Face detection model not loaded', e, s);
     }
     return -1;
   }
@@ -733,56 +216,4 @@ class FaceDetectionService {
     session.release();
     return;
   }
-
-  static Future<(List<FaceDetectionRelative>, int, DateTime)>
-      inferenceAndPostProcess(
-    Map args,
-  ) async {
-    final inputImageList = args['inputImageList'] as Float32List;
-    final inputShape = args['inputShape'] as List<int>;
-    final newSize = args['newSize'] as Dimensions;
-    final sessionAddress = args['sessionAddress'] as int;
-    final timeSentToIsolate = args['timeNow'] as DateTime;
-    final delaySentToIsolate =
-        DateTime.now().difference(timeSentToIsolate).inMilliseconds;
-
-    final Stopwatch stopwatchPrepare = Stopwatch()..start();
-    final inputOrt = OrtValueTensor.createTensorWithDataList(
-      inputImageList,
-      inputShape,
-    );
-    final inputs = {'input': inputOrt};
-    stopwatchPrepare.stop();
-    dev.log(
-      '[YOLOFaceDetectionService] data preparation is finished, in ${stopwatchPrepare.elapsedMilliseconds}ms',
-    );
-
-    stopwatchPrepare.reset();
-    stopwatchPrepare.start();
-    final runOptions = OrtRunOptions();
-    final session = OrtSession.fromAddress(sessionAddress);
-    stopwatchPrepare.stop();
-    dev.log(
-      '[YOLOFaceDetectionService] session preparation is finished, in ${stopwatchPrepare.elapsedMilliseconds}ms',
-    );
-
-    final stopwatchInterpreter = Stopwatch()..start();
-    late final List<OrtValue?> outputs;
-    try {
-      outputs = session.run(runOptions, inputs);
-    } catch (e, s) {
-      dev.log(
-        '[YOLOFaceDetectionService] Error while running inference: $e \n $s',
-      );
-      throw YOLOFaceInterpreterRunException();
-    }
-    stopwatchInterpreter.stop();
-    dev.log(
-      '[YOLOFaceDetectionService] interpreter.run is finished, in ${stopwatchInterpreter.elapsedMilliseconds} ms',
-    );
-
-    final relativeDetections = _yoloPostProcessOutputs(outputs, newSize);
-
-    return (relativeDetections, delaySentToIsolate, DateTime.now());
-  }
 }

mobile/lib/services/machine_learning/face_ml/face_ml_service.dart

@@ -1144,7 +1144,7 @@ class FaceMlService {
     try {
       // Get the bounding boxes of the faces
       final (List<FaceDetectionRelative> faces, dataSize) =
-          await FaceDetectionService.predictSync(
+          await FaceDetectionService.predict(
         image,
         imageByteData,
         interpreterAddress,