flutter_vision 1.1.2 
flutter_vision: ^1.1.2 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, imagev5, imagev8, 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> {
late FlutterVision vision;
Options option = Options.none;
@override
void initState() {
super.initState();
vision = FlutterVision();
}
@override
void dispose() async {
super.dispose();
await vision.closeTesseractModel();
await vision.closeYoloModel();
}
@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: 'YoloV8 on Image',
labelStyle: const TextStyle(fontSize: 18.0),
onTap: () {
setState(() {
option = Options.imagev8;
});
},
),
SpeedDialChild(
child: const Icon(Icons.camera),
backgroundColor: Colors.blue,
foregroundColor: Colors.white,
label: 'YoloV5 on Image',
labelStyle: const TextStyle(fontSize: 18.0),
onTap: () {
setState(() {
option = Options.imagev5;
});
},
),
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(vision: vision);
}
if (option == Options.imagev5) {
return YoloImageV5(vision: vision);
}
if (option == Options.imagev8) {
return YoloImageV8(vision: vision);
}
if (option == Options.tesseract) {
return TesseractImage(vision: vision);
}
return const Center(child: Text("Choose Task"));
}
}
class YoloVideo extends StatefulWidget {
final FlutterVision vision;
const YoloVideo({Key? key, required this.vision}) : super(key: key);
@override
State<YoloVideo> createState() => _YoloVideoState();
}
class _YoloVideoState extends State<YoloVideo> {
late CameraController controller;
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();
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();
}
@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 widget.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 widget.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 YoloImageV5 extends StatefulWidget {
final FlutterVision vision;
const YoloImageV5({Key? key, required this.vision}) : super(key: key);
@override
State<YoloImageV5> createState() => _YoloImageV5State();
}
class _YoloImageV5State extends State<YoloImageV5> {
late List<Map<String, dynamic>> yoloResults;
File? imageFile;
int imageHeight = 1;
int imageWidth = 1;
bool isLoaded = false;
@override
void initState() {
super.initState();
loadYoloModel().then((value) {
setState(() {
yoloResults = [];
isLoaded = true;
});
});
}
@override
void dispose() async {
super.dispose();
}
@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 widget.vision.loadYoloModel(
labels: 'assets/labels.txt',
modelPath: 'assets/yolov5n.tflite',
modelVersion: "yolov5",
quantization: false,
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 widget.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 YoloImageV8 extends StatefulWidget {
final FlutterVision vision;
const YoloImageV8({Key? key, required this.vision}) : super(key: key);
@override
State<YoloImageV8> createState() => _YoloImageV8State();
}
class _YoloImageV8State extends State<YoloImageV8> {
late List<Map<String, dynamic>> yoloResults;
File? imageFile;
int imageHeight = 1;
int imageWidth = 1;
bool isLoaded = false;
@override
void initState() {
super.initState();
loadYoloModel().then((value) {
setState(() {
yoloResults = [];
isLoaded = true;
});
});
}
@override
void dispose() async {
super.dispose();
}
@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 an image"),
),
ElevatedButton(
onPressed: yoloOnImage,
child: const Text("Detect"),
)
],
),
),
...displayBoxesAroundRecognizedObjects(size),
],
);
}
Future<void> loadYoloModel() async {
await widget.vision.loadYoloModel(
labels: 'assets/labels.txt',
modelPath: 'assets/yolov8n.tflite',
modelVersion: "yolov8",
quantization: false,
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 widget.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 {
final FlutterVision vision;
const TesseractImage({Key? key, required this.vision}) : super(key: key);
@override
State<TesseractImage> createState() => _TesseractImageState();
}
class _TesseractImageState extends State<TesseractImage> {
late List<Map<String, dynamic>> tesseractResults = [];
File? imageFile;
bool isLoaded = false;
@override
void initState() {
super.initState();
loadTesseractModel().then((value) {
setState(() {
isLoaded = true;
tesseractResults = [];
});
});
}
@override
void dispose() async {
super.dispose();
}
@override
Widget build(BuildContext context) {
if (!isLoaded) {
return const Scaffold(
body: Center(
child: Text("Model not loaded, waiting for it"),
),
);
}
return Center(
child: 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 an image"),
),
ElevatedButton(
onPressed: tesseractOnImage,
child: const Text("Get Text"),
)
],
),
],
),
),
);
}
Future<void> loadTesseractModel() async {
await widget.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 widget.vision.tesseractOnImage(bytesList: byte);
if (result.isNotEmpty) {
setState(() {
tesseractResults = result;
});
}
}
}Metadata
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Publisher
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)
View/report issues
License
unknown (license)
