flutter_vision 1.1.1 
flutter_vision: ^1.1.1 copied to clipboard
yurihuallpa.comA Flutter plugin for managing Yolov5, Yolov8 and Tesseract v5 accessing with TensorFlow Lite 2.x. Support object detection and OCR on Android. iOS not updated, working in progress.
import 'dart:io';
import 'dart:typed_data';
import 'dart:ui';
import 'package:camera/camera.dart';
import 'package:flutter/material.dart';
import 'package:flutter_speed_dial/flutter_speed_dial.dart';
import 'dart:async';
import 'package:flutter_vision/flutter_vision.dart';
import 'package:image_picker/image_picker.dart';
enum Options { none, image, frame, tesseract, vision }
late List<CameraDescription> cameras;
main() async {
WidgetsFlutterBinding.ensureInitialized();
DartPluginRegistrant.ensureInitialized();
runApp(
const MaterialApp(
home: MyApp(),
),
);
}
class MyApp extends StatefulWidget {
const MyApp({Key? key}) : super(key: key);
@override
State<MyApp> createState() => _MyAppState();
}
class _MyAppState extends State<MyApp> {
Options option = Options.none;
@override
void initState() {
super.initState();
}
@override
Widget build(BuildContext context) {
return Scaffold(
body: task(option),
floatingActionButton: SpeedDial(
//margin bottom
icon: Icons.menu, //icon on Floating action button
activeIcon: Icons.close, //icon when menu is expanded on button
backgroundColor: Colors.black12, //background color of button
foregroundColor: Colors.white, //font color, icon color in button
activeBackgroundColor:
Colors.deepPurpleAccent, //background color when menu is expanded
activeForegroundColor: Colors.white,
visible: true,
closeManually: false,
curve: Curves.bounceIn,
overlayColor: Colors.black,
overlayOpacity: 0.5,
buttonSize: const Size(56.0, 56.0),
children: [
SpeedDialChild(
//speed dial child
child: const Icon(Icons.video_call),
backgroundColor: Colors.red,
foregroundColor: Colors.white,
label: 'Yolo on Frame',
labelStyle: const TextStyle(fontSize: 18.0),
onTap: () {
setState(() {
option = Options.frame;
});
},
),
SpeedDialChild(
child: const Icon(Icons.camera),
backgroundColor: Colors.blue,
foregroundColor: Colors.white,
label: 'Yolo on Image',
labelStyle: const TextStyle(fontSize: 18.0),
onTap: () {
setState(() {
option = Options.image;
});
},
),
SpeedDialChild(
child: const Icon(Icons.text_snippet_outlined),
foregroundColor: Colors.white,
backgroundColor: Colors.green,
label: 'Tesseract',
labelStyle: const TextStyle(fontSize: 18.0),
onTap: () {
setState(() {
option = Options.tesseract;
});
},
),
// SpeedDialChild(
// child: const Icon(Icons.document_scanner),
// foregroundColor: Colors.white,
// backgroundColor: Colors.green,
// label: 'Vision',
// labelStyle: const TextStyle(fontSize: 18.0),
// onTap: () {
// setState(() {
// option = Options.vision;
// });
// },
// ),
],
),
);
}
Widget task(Options option) {
if (option == Options.frame) {
return YoloVideo();
}
if (option == Options.image) {
return YoloImage();
}
if (option == Options.tesseract) {
return const TesseractImage();
}
return const Center(child: Text("Choose Task"));
}
}
class YoloVideo extends StatefulWidget {
YoloVideo({Key? key}) : super(key: key);
@override
State<YoloVideo> createState() => _YoloVideoState();
}
class _YoloVideoState extends State<YoloVideo> {
late CameraController controller;
late FlutterVision vision;
late List<Map<String, dynamic>> yoloResults;
CameraImage? cameraImage;
bool isLoaded = false;
bool isDetecting = false;
@override
void initState() {
super.initState();
init();
}
init() async {
cameras = await availableCameras();
vision = FlutterVision();
controller = CameraController(cameras[0], ResolutionPreset.low);
controller.initialize().then((value) {
loadYoloModel().then((value) {
setState(() {
isLoaded = true;
isDetecting = false;
yoloResults = [];
});
});
});
}
@override
void dispose() async {
super.dispose();
controller.dispose();
await vision.closeYoloModel();
}
@override
Widget build(BuildContext context) {
final Size size = MediaQuery.of(context).size;
if (!isLoaded) {
return const Scaffold(
body: Center(
child: Text("Model not loaded, waiting for it"),
),
);
}
return Stack(
fit: StackFit.expand,
children: [
AspectRatio(
aspectRatio: controller.value.aspectRatio,
child: CameraPreview(
controller,
),
),
...displayBoxesAroundRecognizedObjects(size),
Positioned(
bottom: 75,
width: MediaQuery.of(context).size.width,
child: Container(
height: 80,
width: 80,
decoration: BoxDecoration(
shape: BoxShape.circle,
border: Border.all(
width: 5, color: Colors.white, style: BorderStyle.solid),
),
child: isDetecting
? IconButton(
onPressed: () async {
stopDetection();
},
icon: const Icon(
Icons.stop,
color: Colors.red,
),
iconSize: 50,
)
: IconButton(
onPressed: () async {
await startDetection();
},
icon: const Icon(
Icons.play_arrow,
color: Colors.white,
),
iconSize: 50,
),
),
),
],
);
}
Future<void> loadYoloModel() async {
await vision.loadYoloModel(
labels: 'assets/labels.txt',
modelPath: 'assets/yolov8n.tflite',
modelVersion: "yolov8",
numThreads: 2,
useGpu: true);
setState(() {
isLoaded = true;
});
}
Future<void> yoloOnFrame(CameraImage cameraImage) async {
final result = await vision.yoloOnFrame(
bytesList: cameraImage.planes.map((plane) => plane.bytes).toList(),
imageHeight: cameraImage.height,
imageWidth: cameraImage.width,
iouThreshold: 0.4,
confThreshold: 0.4,
classThreshold: 0.5);
if (result.isNotEmpty) {
setState(() {
yoloResults = result;
});
}
}
Future<void> startDetection() async {
setState(() {
isDetecting = true;
});
if (controller.value.isStreamingImages) {
return;
}
await controller.startImageStream((image) async {
if (isDetecting) {
cameraImage = image;
yoloOnFrame(image);
}
});
}
Future<void> stopDetection() async {
setState(() {
isDetecting = false;
yoloResults.clear();
});
}
List<Widget> displayBoxesAroundRecognizedObjects(Size screen) {
if (yoloResults.isEmpty) return [];
double factorX = screen.width / (cameraImage?.height ?? 1);
double factorY = screen.height / (cameraImage?.width ?? 1);
Color colorPick = const Color.fromARGB(255, 50, 233, 30);
return yoloResults.map((result) {
return Positioned(
left: result["box"][0] * factorX,
top: result["box"][1] * factorY,
width: (result["box"][2] - result["box"][0]) * factorX,
height: (result["box"][3] - result["box"][1]) * factorY,
child: Container(
decoration: BoxDecoration(
borderRadius: const BorderRadius.all(Radius.circular(10.0)),
border: Border.all(color: Colors.pink, width: 2.0),
),
child: Text(
"${result['tag']} ${(result['box'][4] * 100).toStringAsFixed(0)}%",
style: TextStyle(
background: Paint()..color = colorPick,
color: Colors.white,
fontSize: 18.0,
),
),
),
);
}).toList();
}
}
class YoloImage extends StatefulWidget {
YoloImage({Key? key}) : super(key: key);
@override
State<YoloImage> createState() => _YoloImageState();
}
class _YoloImageState extends State<YoloImage> {
late FlutterVision vision;
late List<Map<String, dynamic>> yoloResults;
File? imageFile;
int imageHeight = 1;
int imageWidth = 1;
bool isLoaded = false;
@override
void initState() {
super.initState();
vision = FlutterVision();
loadYoloModel().then((value) {
setState(() {
yoloResults = [];
isLoaded = true;
});
});
}
@override
void dispose() async {
super.dispose();
await vision.closeYoloModel();
}
@override
Widget build(BuildContext context) {
final Size size = MediaQuery.of(context).size;
if (!isLoaded) {
return const Scaffold(
body: Center(
child: Text("Model not loaded, waiting for it"),
),
);
}
return Stack(
fit: StackFit.expand,
children: [
imageFile != null ? Image.file(imageFile!) : const SizedBox(),
Align(
alignment: Alignment.bottomCenter,
child: Row(
mainAxisAlignment: MainAxisAlignment.center,
children: [
TextButton(
onPressed: pickImage,
child: const Text("Pick image"),
),
ElevatedButton(
onPressed: yoloOnImage,
child: const Text("Detect"),
)
],
),
),
...displayBoxesAroundRecognizedObjects(size),
],
);
}
Future<void> loadYoloModel() async {
await vision.loadYoloModel(
labels: 'assets/labels.txt',
modelPath: 'assets/yolov8n.tflite',
modelVersion: "yolov8",
numThreads: 2,
useGpu: true);
setState(() {
isLoaded = true;
});
}
Future<void> pickImage() async {
final ImagePicker picker = ImagePicker();
// Capture a photo
final XFile? photo = await picker.pickImage(source: ImageSource.gallery);
if (photo != null) {
setState(() {
imageFile = File(photo.path);
});
}
}
yoloOnImage() async {
yoloResults.clear();
Uint8List byte = await imageFile!.readAsBytes();
final image = await decodeImageFromList(byte);
imageHeight = image.height;
imageWidth = image.width;
final result = await vision.yoloOnImage(
bytesList: byte,
imageHeight: image.height,
imageWidth: image.width,
iouThreshold: 0.8,
confThreshold: 0.4,
classThreshold: 0.5);
if (result.isNotEmpty) {
setState(() {
yoloResults = result;
});
}
}
List<Widget> displayBoxesAroundRecognizedObjects(Size screen) {
if (yoloResults.isEmpty) return [];
double factorX = screen.width / (imageWidth);
double imgRatio = imageWidth / imageHeight;
double newWidth = imageWidth * factorX;
double newHeight = newWidth / imgRatio;
double factorY = newHeight / (imageHeight);
double pady = (screen.height - newHeight) / 2;
Color colorPick = const Color.fromARGB(255, 50, 233, 30);
return yoloResults.map((result) {
return Positioned(
left: result["box"][0] * factorX,
top: result["box"][1] * factorY + pady,
width: (result["box"][2] - result["box"][0]) * factorX,
height: (result["box"][3] - result["box"][1]) * factorY,
child: Container(
decoration: BoxDecoration(
borderRadius: const BorderRadius.all(Radius.circular(10.0)),
border: Border.all(color: Colors.pink, width: 2.0),
),
child: Text(
"${result['tag']} ${(result['box'][4] * 100).toStringAsFixed(0)}%",
style: TextStyle(
background: Paint()..color = colorPick,
color: Colors.white,
fontSize: 18.0,
),
),
),
);
}).toList();
}
}
class TesseractImage extends StatefulWidget {
const TesseractImage({Key? key}) : super(key: key);
@override
State<TesseractImage> createState() => _TesseractImageState();
}
class _TesseractImageState extends State<TesseractImage> {
late FlutterVision vision;
late List<Map<String, dynamic>> tesseractResults = [];
File? imageFile;
bool isLoaded = false;
@override
void initState() {
super.initState();
vision = FlutterVision();
loadTesseractModel().then((value) {
setState(() {
isLoaded = true;
tesseractResults = [];
});
});
}
@override
void dispose() async {
super.dispose();
await vision.closeTesseractModel();
}
@override
Widget build(BuildContext context) {
if (!isLoaded) {
return const Scaffold(
body: Center(
child: Text("Model not loaded, waiting for it"),
),
);
}
return SingleChildScrollView(
child: Column(
children: [
imageFile != null ? Image.file(imageFile!) : const SizedBox(),
tesseractResults.isEmpty
? const SizedBox()
: Align(child: Text(tesseractResults[0]["text"])),
Row(
mainAxisAlignment: MainAxisAlignment.center,
children: [
TextButton(
onPressed: pickImage,
child: const Text("Pick image"),
),
ElevatedButton(
onPressed: tesseractOnImage,
child: const Text("Get Text"),
)
],
),
],
),
);
}
Future<void> loadTesseractModel() async {
await vision.loadTesseractModel(
args: {
'psm': '11',
'oem': '1',
'preserve_interword_spaces': '1',
},
language: 'spa',
);
setState(() {
isLoaded = true;
});
}
Future<void> pickImage() async {
final ImagePicker picker = ImagePicker();
// Capture a photo
final XFile? photo = await picker.pickImage(source: ImageSource.gallery);
if (photo != null) {
setState(() {
imageFile = File(photo.path);
});
}
}
tesseractOnImage() async {
tesseractResults.clear();
Uint8List byte = await imageFile!.readAsBytes();
final result = await vision.tesseractOnImage(bytesList: byte);
if (result.isNotEmpty) {
setState(() {
tesseractResults = result;
});
}
}
}Metadata
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Metadata
A Flutter plugin for managing Yolov5, Yolov8 and Tesseract v5 accessing with TensorFlow Lite 2.x. Support object detection and OCR on Android. iOS not updated, working in progress.
Repository (GitHub)
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License
unknown (license)
