Flutter相机与谷歌机器学习视觉插件camera_google_ml_vision的使用

Flutter相机与谷歌机器学习视觉插件camera_google_ml_vision的使用

camera_google_ml_vision

版本: 1.1.0-nullsafety

描述: camera_google_ml_vision 是一个用于iOS和Android平台的Flutter包,它可以在预览相机的同时使用Google ML Vision进行检测。

flutter_camera_ml_vision

版本: 1.1.0-nullsafety

描述: flutter_camera_ml_visioncamera_google_ml_vision 的原始版本。本示例将使用 camera_google_ml_vision 包来展示如何在Flutter应用中实现相机功能并使用Google ML Vision进行条形码检测。

安装

首先,在 pubspec.yaml 文件中添加 camera_google_ml_vision 作为依赖项:

dependencies:
  flutter:
    sdk: flutter
  camera_google_ml_vision: 1.1.0-nullsafety

Android

修改你的 android/app/build.gradle 文件,将最小SDK版本设置为21或更高:

minSdkVersion 21

使用

示例:条形码检测

以下是完整的示例代码,展示了如何在Flutter应用中使用 camera_google_ml_vision 进行条形码检测。

import 'dart:ui';
import 'package:camera_google_ml_vision/camera_google_ml_vision.dart';
import 'package:flutter/material.dart';
import 'package:google_ml_vision/google_ml_vision.dart';

void main() => runApp(MyApp());

class MyApp extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      title: 'Flutter Demo',
      theme: ThemeData(
        primarySwatch: Colors.blue,
      ),
      home: MyHomePage(title: 'Flutter Demo Home Page'),
    );
  }
}

class MyHomePage extends StatefulWidget {
  MyHomePage({Key? key, required this.title}) : super(key: key);

  final String title;

  [@override](/user/override)
  _MyHomePageState createState() => _MyHomePageState();
}

class _MyHomePageState extends State<MyHomePage> {
  List<String> data = [];

  [@override](/user/override)
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text(widget.title),
      ),
      body: Column(
        mainAxisSize: MainAxisSize.min,
        crossAxisAlignment: CrossAxisAlignment.center,
        children: [
          ElevatedButton(
            onPressed: () async {
              final barcode = await Navigator.of(context).push<Barcode>(
                MaterialPageRoute(
                  builder: (c) {
                    return ScanPage();
                  },
                ),
              );
              if (barcode == null) {
                return;
              }

              setState(() {
                data.add(barcode.displayValue.toString());
              });
            },
            child: Text('Scan product'),
          ),
          Expanded(
            child: ListView(
              children: data.map((d) => Text(d)).toList(),
            ),
          ),
        ],
      ),
    );
  }
}

class ScanPage extends StatefulWidget {
  [@override](/user/override)
  _ScanPageState createState() => _ScanPageState();
}

class _ScanPageState extends State<ScanPage> {
  bool resultSent = false;
  BarcodeDetector detector = GoogleVision.instance.barcodeDetector();

  [@override](/user/override)
  Widget build(BuildContext context) {
    return Scaffold(
      body: SafeArea(
        child: SizedBox(
          width: MediaQuery.of(context).size.width,
          child: CameraMlVision<List<Barcode>>(
            overlayBuilder: (c) {
              return Container(
                decoration: ShapeDecoration(
                  shape: _ScannerOverlayShape(
                    borderColor: Theme.of(context).primaryColor,
                    borderWidth: 3.0,
                  ),
                ),
              );
            },
            detector: detector.detectInImage,
            onResult: (List<Barcode> barcodes) {
              if (!mounted || resultSent || barcodes == null || barcodes.isEmpty) {
                return;
              }
              resultSent = true;
              Navigator.of(context).pop<Barcode>(barcodes.first);
            },
            onDispose: () {
              detector.close();
            },
          ),
        ),
      ),
    );
  }
}

class _ScannerOverlayShape extends ShapeBorder {
  final Color borderColor;
  final double borderWidth;
  final Color overlayColor;

  _ScannerOverlayShape({
    this.borderColor = Colors.white,
    this.borderWidth = 1.0,
    this.overlayColor = const Color(0x88000000),
  });

  [@override](/user/override)
  EdgeInsetsGeometry get dimensions => EdgeInsets.all(10.0);

  [@override](/user/override)
  Path getInnerPath(Rect rect, {TextDirection? textDirection}) {
    return Path()
      ..fillType = PathFillType.evenOdd
      ..addPath(getOuterPath(rect), Offset.zero);
  }

  [@override](/user/override)
  Path getOuterPath(Rect rect, {TextDirection? textDirection}) {
    Path _getLeftTopPath(Rect rect) {
      return Path()
        ..moveTo(rect.left, rect.bottom)
        ..lineTo(rect.left, rect.top)
        ..lineTo(rect.right, rect.top);
    }

    return _getLeftTopPath(rect)
      ..lineTo(
        rect.right,
        rect.bottom,
      )
      ..lineTo(
        rect.left,
        rect.bottom,
      )
      ..lineTo(
        rect.left,
        rect.top,
      );
  }

  [@override](/user/override)
  void paint(Canvas canvas, Rect rect, {TextDirection? textDirection}) {
    const lineSize = 30;

    final width = rect.width;
    final borderWidthSize = width * 10 / 100;
    final height = rect.height;
    final borderHeightSize = height - (width - borderWidthSize);
    final borderSize = Size(borderWidthSize / 2, borderHeightSize / 2);

    var paint = Paint()
      ..color = overlayColor
      ..style = PaintingStyle.fill;

    canvas
      ..drawRect(
        Rect.fromLTRB(
            rect.left, rect.top, rect.right, borderSize.height + rect.top),
        paint,
      )
      ..drawRect(
        Rect.fromLTRB(rect.left, rect.bottom - borderSize.height, rect.right,
            rect.bottom),
        paint,
      )
      ..drawRect(
        Rect.fromLTRB(rect.left, rect.top + borderSize.height,
            rect.left + borderSize.width, rect.bottom - borderSize.height),
        paint,
      )
      ..drawRect(
        Rect.fromLTRB(
            rect.right - borderSize.width,
            rect.top + borderSize.height,
            rect.right,
            rect.bottom - borderSize.height),
        paint,
      );

    paint = Paint()
      ..color = borderColor
      ..style = PaintingStyle.stroke
      ..strokeWidth = borderWidth;

    final borderOffset = borderWidth / 2;
    final realReact = Rect.fromLTRB(
        borderSize.width + borderOffset,
        borderSize.height + borderOffset + rect.top,
        width - borderSize.width - borderOffset,
        height - borderSize.height - borderOffset + rect.top);

    // Draw top right corner
    canvas
      ..drawPath(
          Path()
            ..moveTo(realReact.right, realReact.top)
            ..lineTo(realReact.right, realReact.top + lineSize),
          paint)
      ..drawPath(
          Path()
            ..moveTo(realReact.right, realReact.top)
            ..lineTo(realReact.right - lineSize, realReact.top),
          paint)
      ..drawPoints(
        PointMode.points,
        [Offset(realReact.right, realReact.top)],
        paint,
      )

      // Draw top left corner
      ..drawPath(
          Path()
            ..moveTo(realReact.left, realReact.top)
            ..lineTo(realReact.left, realReact.top + lineSize),
          paint)
      ..drawPath(
          Path()
            ..moveTo(realReact.left, realReact.top)
            ..lineTo(realReact.left + lineSize, realReact.top),
          paint)
      ..drawPoints(
        PointMode.points,
        [Offset(realReact.left, realReact.top)],
        paint,
      )

      // Draw bottom right corner
      ..drawPath(
          Path()
            ..moveTo(realReact.right, realReact.bottom)
            ..lineTo(realReact.right, realReact.bottom - lineSize),
          paint)
      ..drawPath(
          Path()
            ..moveTo(realReact.right, realReact.bottom)
            ..lineTo(realReact.right - lineSize, realReact.bottom),
          paint)
      ..drawPoints(
        PointMode.points,
        [Offset(realReact.right, realReact.bottom)],
        paint,
      )

      // Draw bottom left corner
      ..drawPath(
          Path()
            ..moveTo(realReact.left, realReact.bottom)
            ..lineTo(realReact.left, realReact.bottom - lineSize),
          paint)
      ..drawPath(
          Path()
            ..moveTo(realReact.left, realReact.bottom)
            ..lineTo(realReact.left + lineSize, realReact.bottom),
          paint)
      ..drawPoints(
        PointMode.points,
        [Offset(realReact.left, realReact.bottom)],
        paint,
      );
  }

  [@override](/user/override)
  ShapeBorder scale(double t) {
    return _ScannerOverlayShape(
      borderColor: borderColor,
      borderWidth: borderWidth,
      overlayColor: overlayColor,
    );
  }
}

更多关于Flutter相机与谷歌机器学习视觉插件camera_google_ml_vision的使用的实战教程也可以访问 https://www.itying.com/category-92-b0.html

1 回复

更多关于Flutter相机与谷歌机器学习视觉插件camera_google_ml_vision的使用的实战系列教程也可以访问 https://www.itying.com/category-92-b0.html


当然,以下是一个使用Flutter的camera插件与google_ml_vision插件来实现实时相机预览和物体识别的示例代码。

首先,确保你已经在pubspec.yaml文件中添加了必要的依赖:

dependencies:
  flutter:
    sdk: flutter
  camera: ^0.10.0+3  # 请检查最新版本号
  google_ml_vision: ^0.14.0  # 请检查最新版本号

然后,运行flutter pub get来安装这些依赖。

接下来,你需要处理Android和iOS平台的权限和配置。确保在AndroidManifest.xml中添加相机权限:

<uses-permission android:name="android.permission.CAMERA" />
<uses-feature android:name="android.hardware.camera" android:required="true" />
<uses-feature android:name="android.hardware.camera.autofocus" />

在iOS上,你需要在Info.plist中添加相机使用描述:

<key>NSCameraUsageDescription</key>
<string>Need camera access</string>

现在,让我们编写Flutter代码来实现相机预览和物体识别。

import 'package:flutter/material.dart';
import 'package:camera/camera.dart';
import 'package:google_ml_vision/google_ml_vision.dart';

List<CameraDescription> cameras;
CameraController? controller;
final ValueNotifier<List<RecognizedObject>> objects = ValueNotifier([]);

Future<void> main() async {
  WidgetsFlutterBinding.ensureInitialized();
  cameras = await availableCameras();
  controller = CameraController(cameras[0], ResolutionPreset.high);
  controller!.initialize().then((_) {
    if (!mounted) {
      return;
    }
    setState(() {});
  });
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: CameraApp(),
    );
  }
}

class CameraApp extends StatefulWidget {
  @override
  _CameraAppState createState() => _CameraAppState();
}

class _CameraAppState extends State<CameraApp> {
  ImageAnalyzer? _imageAnalyzer;

  @override
  void initState() {
    super.initState();
    _imageAnalyzer = ImageAnalyzerBuilder()
        .setDetector(ObjectDetector())
        .build()
        ..processImage(inputImage: InputImage.fromCameraImage(
            controller!.value.previewImage!,
            size: Size(controller!.value.previewSize!.width!.toDouble(),
                controller!.value.previewSize!.height!.toDouble())))
        .listen((List<RecognizedObject> results) {
      objects.value = results;
    });
    controller!.startImageStream((image) {
      _imageAnalyzer!.processImage(inputImage: InputImage.fromBytes(
          bytes: image.planes[0].bytes,
          size: Size(image.width, image.height),
          imageRotation: 90, // 根据需要调整
          format: image.format));
    });
  }

  @override
  void dispose() {
    controller!.dispose();
    _imageAnalyzer!.cancel();
    objects.dispose();
    super.dispose();
  }

  @override
  Widget build(BuildContext context) {
    if (!controller!.value.isInitialized) {
      return Container();
    }
    return Scaffold(
      appBar: AppBar(
        title: Text('Camera with ML Vision'),
      ),
      body: Stack(
        children: <Widget>[
          CameraPreview(controller!),
          Positioned.fill(
            child: Column(
              crossAxisAlignment: CrossAxisAlignment.start,
              children: <Widget>[
                Expanded(
                  child: Container(
                    color: Colors.black45,
                    child: Center(
                      child: objects.value.isEmpty
                          ? Text('No objects detected')
                          : ListView.builder(
                              shrinkWrap: true,
                              itemCount: objects.value.length,
                              itemBuilder: (context, index) {
                                final RecognizedObject object = objects.value[index];
                                return Padding(
                                  padding: EdgeInsets.all(8.0),
                                  child: Text(
                                    '${object.label} (${object.boundingBox!.width * 100}%)',
                                    style: TextStyle(color: Colors.white),
                                  ),
                                );
                              },
                            ),
                    ),
                  ),
                ),
              ],
            ),
          ),
        ],
      ),
    );
  }
}

请注意,这个示例代码假设你使用的是较新的Flutter和插件版本。如果使用的版本有所不同,可能需要调整一些API调用。这个示例展示了如何使用camera插件进行相机预览,并通过google_ml_vision插件进行实时物体检测。检测结果会在相机预览的顶部显示。

此外,确保在真实项目中处理异常和错误情况,例如相机初始化失败、权限被拒绝等。

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