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adding some basic linting - prepping support for multiple models being loaded in by the app.

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This commit is contained in:
Lucas Oskorep
2022-07-08 18:30:25 -04:00
parent b8119e6520
commit 284fa4a2f8
13 changed files with 99 additions and 54 deletions
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lib/widgets/poke_finder.dart
+38 -17
View File
@@ -1,16 +1,19 @@
import 'dart:convert';
import 'dart:isolate';
import 'package:camera/camera.dart';
import 'package:flutter/material.dart';
import 'package:flutter/services.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 '../tflite/classifier.dart';
import '../tflite/model/outputs/recognition.dart';
import '../utils/logger.dart';
import '../tflite/data/recognition.dart';
import '../tflite/data/stats.dart';
/// [PokeFinder] sends each frame for inference
class PokeFinder extends StatefulWidget {
/// Callback to pass results after inference to [HomeView]
final Function(List<Recognition> recognitions) resultsCallback;
@@ -28,17 +31,20 @@ class PokeFinder extends StatefulWidget {
}
class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
late List<CameraDescription> cameras;
late CameraController cameraController;
late MLIsolate _mlIsolate;
/// true when inference is ongoing
bool predicting = false;
bool _cameraInitialized = false;
bool _classifierInitialized = false;
//cameras
late List<CameraDescription> cameras;
late CameraController cameraController;
//ml variables
late Interpreter interpreter;
late Classifier classifier;
late MLIsolate _mlIsolate;
late List<ModelConfiguration> modelConfigurations;
@override
void initState() {
@@ -55,19 +61,34 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
predicting = false;
}
Future<List<String>> getModelFiles() async {
final manifestContent = await rootBundle.loadString('AssetManifest.jsn');
final Map<String, dynamic> manifestMap = json.decode(manifestContent);
return manifestMap.keys
.where((String key) => key.contains('.tflite'))
.map((String key) => key.substring(7))
.toList();
}
void initializeModel() async {
var interpreterOptions = InterpreterOptions()..threads = 8;
interpreter = await Interpreter.fromAsset('efficientnet_v2s.tflite',
options: interpreterOptions);
classifier = Classifier(interpreter: interpreter);
var modelFiles = await getModelFiles();
var modelConfigurations =
modelFiles.map((e) => ModelConfiguration(e)).toList();
var currentConfig = modelConfigurations[0];
logger.i(modelFiles);
interpreter = await createInterpreter(currentConfig);
classifier = Classifier(interpreter);
_classifierInitialized = true;
}
Future<Interpreter> createInterpreter(ModelConfiguration config) async {
return await Interpreter.fromAsset(config.name,
options: config.interpreters[0]);
}
/// Initializes the camera by setting [cameraController]
void initializeCamera() async {
cameras = await availableCameras();
// cameras[0] for rear-camera
cameraController =
CameraController(cameras[0], ResolutionPreset.low, enableAudio: false);
@@ -94,11 +115,11 @@ class _PokeFinderState extends State<PokeFinder> with WidgetsBindingObserver {
var results = await inference(MLIsolateData(
cameraImage, classifier.interpreter.address, classifier.labels));
if (results.containsKey("recognitions")) {
widget.resultsCallback(results["recognitions"]);
if (results.containsKey('recognitions')) {
widget.resultsCallback(results['recognitions']);
}
if (results.containsKey("stats")) {
widget.statsCallback(results["stats"]);
if (results.containsKey('stats')) {
widget.statsCallback(results['stats']);
}
logger.i(results);
lib/widgets/results.dart
+2 -2
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@@ -1,7 +1,7 @@
import 'package:flutter/material.dart';
import 'package:tensordex_mobile/widgets/poke_finder.dart';
import 'package:tensordex_mobile/tflite/data/recognition.dart';
import 'package:tensordex_mobile/tflite/data/stats.dart';
import '../tflite/model/outputs/recognition.dart';
import '../tflite/model/outputs/stats.dart';
/// [PokeFinder] sends each frame for inference
lib/widgets/tensordex_home.dart
+4 -4
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@@ -1,10 +1,10 @@
import 'package:flutter/material.dart';
import 'package:tensordex_mobile/tflite/model/outputs/recognition.dart';
import 'package:tensordex_mobile/tflite/model/outputs/stats.dart';
import 'package:tensordex_mobile/widgets/poke_finder.dart';
import 'package:tensordex_mobile/widgets/results.dart';
import '../utils/logger.dart';
import '../tflite/data/recognition.dart';
import '../tflite/data/stats.dart';
class TensordexHome extends StatefulWidget {
const TensordexHome({Key? key, required this.title}) : super(key: key);
@@ -22,7 +22,7 @@ class TensordexHome extends StatefulWidget {
class _TensordexHomeState extends State<TensordexHome> {
/// Results from the image classifier
List<Recognition> results = [Recognition(1, "NOTHING DETECTED", .5)];
List<Recognition> results = [Recognition(1, 'NOTHING DETECTED', .5)];
Stats stats = Stats();
/// Scaffold Key
@@ -30,7 +30,7 @@ class _TensordexHomeState extends State<TensordexHome> {
void _incrementCounter() {
setState(() {
logger.d("Counter Incremented!");
logger.d('Counter Incremented!');
});
}