beginning work on ui

lib/main.dart

@@ -1,9 +1,20 @@
+import 'package:camera/camera.dart';
 import 'package:flutter/material.dart';
+import 'package:flutter/services.dart';
 import 'package:tensordex_mobile/widgets/tensordex_home.dart';
 import 'package:tensordex_mobile/utils/logger.dart';
 
+late List<CameraDescription> cameras;
+
 Future<void> main() async {
-  runApp(const MyApp());
+  WidgetsFlutterBinding.ensureInitialized();
+  cameras = await availableCameras();
+  SystemChrome.setPreferredOrientations([
+    DeviceOrientation.portraitUp,
+    DeviceOrientation.portraitDown,
+  ]).then((_) {
+    runApp(const MyApp());
+  });
 }
 
 class MyApp extends StatelessWidget {

lib/tflite/classifier.dart

@@ -1,7 +1,9 @@
+import 'dart:io';
 import 'dart:math';
 
 import 'package:collection/collection.dart';
 import 'package:image/image.dart' as image_lib;
+import 'package:path_provider/path_provider.dart';
 import 'package:tflite_flutter/tflite_flutter.dart';
 import 'package:tflite_flutter_helper/tflite_flutter_helper.dart';
 
@@ -31,6 +33,7 @@ class Classifier {
   /// Labels file loaded as list
   late List<String> _labels;
   int classifierCreationStart = -1;
+  bool _shouldReturnFrame = false;
 
   Classifier(
     Interpreter interpreter, {
@@ -67,6 +70,10 @@ class Classifier {
     }
   }
 
+  void setReturnFrame(bool returnFrame) {
+    _shouldReturnFrame = returnFrame;
+  }
+
   /// Pre-process the image
   TensorImage? getProcessedImage(TensorImage? inputImage) {
     int cropSize = min(_inputImage.height, _inputImage.width);
@@ -83,12 +90,14 @@ class Classifier {
   }
 
   /// Runs object detection on the input image
-  Map<String, dynamic>? predict(image_lib.Image image) {
+  Future<Map<String, dynamic>?> predict(image_lib.Image image) async {
     var preProcStart = DateTime.now().millisecondsSinceEpoch;
-    _inputImage.loadImage(image);
+    _inputImage.loadImage(image_lib.copyRotate(image, 90));
     _inputImage = getProcessedImage(_inputImage)!;
+
+
     var inferenceStart = DateTime.now().millisecondsSinceEpoch;
-    _interpreter.run(_inputImage.buffer, _outputBuffer.getBuffer());
+        _interpreter.run(_inputImage.buffer, _outputBuffer.getBuffer());
     var postProcStart = DateTime.now().millisecondsSinceEpoch;
     Map<String, double> labeledProb =
         TensorLabel.fromList(labels, _outputProcessor.process(_outputBuffer))
@@ -106,6 +115,7 @@ class Classifier {
         inferenceTime: postProcStart - inferenceStart,
         postProcessingTime: endTime - postProcStart,
       ),
+      'image': _shouldReturnFrame? _inputImage.image : null,
     };
   }
 

lib/tflite/ml_isolate.dart

@@ -5,6 +5,7 @@ import 'package:tensordex_mobile/tflite/classifier.dart';
 import 'package:tflite_flutter/tflite_flutter.dart';
 
 import '../utils/image_utils.dart';
+import '../utils/logger.dart';
 
 class IsolateBase {
   final ReceivePort _receivePort = ReceivePort();
@@ -25,6 +26,7 @@ class MLIsolate extends IsolateBase {
     _sendPort = await _receivePort.first;
   }
 
+
   static void entryPoint(SendPort sendPort) async {
     final port = ReceivePort();
     sendPort.send(port.sendPort);
@@ -33,10 +35,15 @@ class MLIsolate extends IsolateBase {
       var cameraImage = mlIsolateData.cameraImage;
       var converted = ImageUtils.convertCameraImage(cameraImage);
       if (converted != null) {
-        Classifier classifier = Classifier(
+        var classifier = Classifier(
             Interpreter.fromAddress(mlIsolateData.interpreterAddress),
             labels: mlIsolateData.labels);
-        var result = classifier.predict(converted);
+        if (classifier.interpreter.address !=
+            mlIsolateData.interpreterAddress) {
+          logger.e('INTERPRETER ADDRESS MISMATCH!');
+        }
+        classifier.setReturnFrame(mlIsolateData.shouldSaveFrame);
+        var result = await classifier.predict(converted);
         mlIsolateData.responsePort?.send(result);
       } else {
         mlIsolateData.responsePort?.send({'response': 'not working yet'});
@@ -49,6 +56,7 @@ class MLIsolate extends IsolateBase {
 class MLIsolateData {
   CameraImage cameraImage;
   int interpreterAddress;
+  bool shouldSaveFrame;
   List<String> labels;
   SendPort? responsePort;
 
@@ -56,5 +64,6 @@ class MLIsolateData {
     this.cameraImage,
     this.interpreterAddress,
     this.labels,
+    this.shouldSaveFrame,
   );
 }

lib/widgets/poke_finder.dart

@@ -1,19 +1,21 @@
 import 'dart:convert';
+import 'dart:io';
 import 'dart:isolate';
-
 import 'package:camera/camera.dart';
 import 'package:flutter/material.dart';
 import 'package:flutter/services.dart';
+import 'package:image/image.dart';
+import 'package:path_provider/path_provider.dart';
 import 'package:tensordex_mobile/tflite/ml_isolate.dart';
 import 'package:tensordex_mobile/tflite/model/configuration.dart';
 import 'package:tensordex_mobile/tflite/model/outputs/stats.dart';
 import 'package:tflite_flutter/tflite_flutter.dart';
 
+import '../main.dart';
 import '../tflite/classifier.dart';
 import '../tflite/model/outputs/recognition.dart';
 import '../utils/logger.dart';
 
-
 class PokeFinder extends StatefulWidget {
   /// Callback to pass results after inference to [HomeView]
   final Function(List<Recognition> recognitions) resultsCallback;
@@ -35,9 +37,9 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
   bool predicting = false;
   bool _cameraInitialized = false;
   bool _classifierInitialized = false;
+  bool _saveClassifierImage = false;
+  int cameraIndex = 0;
 
-  //cameras
-  late List<CameraDescription> cameras;
   late CameraController cameraController;
 
   //ml variables
@@ -56,7 +58,10 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
     WidgetsBinding.instance.addObserver(this);
     _mlIsolate = MLIsolate();
     await _mlIsolate.start();
-    initializeCamera();
+    swapToCamera(cameras[0]);
+    for (CameraDescription cam in cameras) {
+      logger.i(cam);
+    }
     initializeModel();
     predicting = false;
   }
@@ -86,16 +91,12 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
         options: config.interpreters[0]);
   }
 
-  /// Initializes the camera by setting [cameraController]
+  void swapToCamera(CameraDescription cameraDescription) async {
-  void initializeCamera() async {
+    cameraController = CameraController(cameraDescription, ResolutionPreset.low,
-    cameras = await availableCameras();
+        enableAudio: false);
-    cameraController =
-        CameraController(cameras[0], ResolutionPreset.low, enableAudio: false);
-
     cameraController.initialize().then((_) async {
       /// previewSize is size of each image frame captured by controller
       /// 352x288 on iOS, 240p (320x240) on Android with ResolutionPreset.low
-      // Stream of image passed to [onLatestImageAvailable] callback
       await cameraController.startImageStream(onLatestImageAvailable);
       setState(() {
         _cameraInitialized = true;
@@ -112,8 +113,12 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
       setState(() {
         predicting = true;
       });
+      logger.i(_saveClassifierImage);
       var results = await inference(MLIsolateData(
-          cameraImage, classifier.interpreter.address, classifier.labels));
+          cameraImage,
+          classifier.interpreter.address,
+          classifier.labels,
+          _saveClassifierImage));
 
       if (results.containsKey('recognitions')) {
         widget.resultsCallback(results['recognitions']);
@@ -121,23 +126,62 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
       if (results.containsKey('stats')) {
         widget.statsCallback(results['stats']);
       }
-      logger.i(results);
+      if (results.containsKey('image')) {
-
+        var image = results['image'];
+        if (image != null) {
+          Directory tempDir = await getTemporaryDirectory();
+          String tempPath = tempDir.path;
+          logger.i(tempPath);
+          logger.i('SAVING IMAGE!');
+          await File('$tempPath/${DateTime.now().millisecondsSinceEpoch}.png')
+              .writeAsBytes(encodePng(image));
+          _saveClassifierImage = false;
+        }
+      }
       setState(() {
         predicting = false;
       });
     }
   }
 
+  void swapCamera() async {
+    logger.i(cameras);
+    logger.i(cameraIndex);
+    cameraIndex += 1;
+    if (cameras.length <= cameraIndex) {
+      cameraIndex = 0;
+    }
+    swapToCamera(cameras[cameraIndex]);
+  }
+
+  void saveMLImage() async {
+    logger.i('setting save classifier to true');
+    _saveClassifierImage = true;
+  }
+
+  void setZoom() async {
+    logger.i(await cameraController.getMinZoomLevel());
+    logger.i(await cameraController.getMaxZoomLevel());
+    logger.i(cameraController.setZoomLevel(2.0));
+  }
+
   @override
   Widget build(BuildContext context) {
     // Return empty container while the camera is not initialized
     if (!_cameraInitialized) {
       return Container();
     }
-    return AspectRatio(
+    return Column(
-        aspectRatio: 1 / cameraController.value.aspectRatio,
+      children: [
-        child: CameraPreview(cameraController));
+        AspectRatio(
+            aspectRatio: 1 / cameraController.value.aspectRatio,
+            child: CameraPreview(cameraController)),
+        TextButton(onPressed: swapCamera, child: const Text('Change Camera!')),
+        TextButton(
+            onPressed: saveMLImage, child: const Text('Save Model Image')),
+        TextButton(onPressed: setZoom, child: const Text('Zoom!'))
+      ],
+    );
   }
 
   /// Runs inference in another isolate

lib/widgets/tensordex_home.dart

@@ -64,6 +64,34 @@ class _TensordexHomeState extends State<TensordexHome> {
         appBar: AppBar(
           title: Text(widget.title),
         ),
+        drawer: Drawer(
+          child: ListView(
+            // Important: Remove any padding from the ListView.
+            padding: EdgeInsets.zero,
+            children: [
+              const DrawerHeader(
+                decoration: BoxDecoration(
+                  color: Colors.blue,
+                ),
+                child: Text('Drawer Header'),
+              ),
+              ListTile(
+                title: const Text('Item 1'),
+                onTap: () {
+                  // Update the state of the app.
+                  // ...
+                },
+              ),
+              ListTile(
+                title: const Text('Item 2'),
+                onTap: () {
+                  // Update the state of the app.
+                  // ...
+                },
+              ),
+            ],
+          ),
+        ),
         body: Center(
           child: Column(
             mainAxisAlignment: MainAxisAlignment.start,