Flutter韩国语机器学习插件google_ml_kit_for_korean的使用

Flutter韩国语机器学习插件google_ml_kit_for_korean的使用

Pub Version

一个用于在Android和iOS上使用Google独立ML Kit的Flutter插件。它仍在开发和测试中。

特性

视觉

要求

请参阅google_ml_kit 0.7.2 的原始页面。

许可证

MIT

完整示例Demo

以下是使用google_ml_kit_for_korean插件的基本示例代码。此示例展示了如何设置和使用文本检测功能。

import 'dart:io';

import 'package:camera/camera.dart';
import 'package:google_ml_kit_for_korean_example/NlpDetectorViews/entity_extraction_view.dart';
import 'package:google_ml_kit_for_korean_example/NlpDetectorViews/language_translator_view.dart';
import 'package:google_ml_kit_for_korean_example/NlpDetectorViews/smart_reply_view.dart';
import 'package:google_ml_kit_for_korean_example/VisionDetectorViews/object_detector_view.dart';

import 'NlpDetectorViews/language_identifier_view.dart';
import 'VisionDetectorViews/detector_views.dart';
import 'package:flutter/material.dart';

import 'VisionDetectorViews/text_detectorv2_view.dart';

List<CameraDescription> cameras = [];

Future<void> main() async {
  WidgetsFlutterBinding.ensureInitialized();

  cameras = await availableCameras();
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      debugShowCheckedModeBanner: false,
      home: Home(),
    );
  }
}

class Home extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('Google ML Kit Demo App'),
        centerTitle: true,
        elevation: 0,
      ),
      body: SafeArea(
        child: Center(
          child: SingleChildScrollView(
            child: Padding(
              padding: EdgeInsets.symmetric(horizontal: 16),
              child: Column(
                children: [
                  ExpansionTile(
                    title: const Text("Vision"),
                    children: [
                      CustomCard(
                        'Image Label Detector',
                        ImageLabelView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Face Detector',
                        FaceDetectorView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Barcode Scanner',
                        BarcodeScannerView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Pose Detector',
                        PoseDetectorView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Digital Ink Recogniser',
                        DigitalInkView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Text Detector',
                        TextDetectorView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Text Detector V2',
                        TextDetectorV2View(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                        'Object Detector',
                        ObjectDetectorView(),
                      ),
                      CustomCard(
                        'Remote Model Manager',
                        RemoteModelView(),
                        featureCompleted: true,
                      )
                    ],
                  ),
                  SizedBox(
                    height: 20,
                  ),
                  ExpansionTile(
                    title: const Text("Natural Language"),
                    children: [
                      CustomCard(
                        'Language Identifier',
                        LanguageIdentifierView(),
                        featureCompleted: true,
                      ),
                      CustomCard(
                          'Language Translator', LanguageTranslatorView()),
                      CustomCard('Entity Extractor', EntityExtractionView()),
                      CustomCard('Smart Reply', SmartReplyView())
                    ],
                  ),
                ],
              ),
            ),
          ),
        ),
      ),
    );
  }
}

class CustomCard extends StatelessWidget {
  final String _label;
  final Widget _viewPage;
  final bool featureCompleted;

  const CustomCard(this._label, this._viewPage,
      {this.featureCompleted = false});

  [@override](/user/override)
  Widget build(BuildContext context) {
    return Card(
      elevation: 5,
      margin: EdgeInsets.only(bottom: 10),
      child: ListTile(
        tileColor: Theme.of(context).primaryColor,
        title: Text(
          _label,
          style: TextStyle(color: Colors.white, fontWeight: FontWeight.bold),
        ),
        onTap: () {
          if (Platform.isIOS && !featureCompleted) {
            ScaffoldMessenger.of(context).showSnackBar(SnackBar(
                content: const Text(
                    'This feature has not been implemented for iOS yet')));
          } else
            Navigator.push(
                context, MaterialPageRoute(builder: (context) => _viewPage));
        },
      ),
    );
  }
}

更多关于Flutter韩国语机器学习插件google_ml_kit_for_korean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韩国语机器学习插件google_ml_kit_for_korean的使用的实战系列教程也可以访问 https://www.itying.com/category-92-b0.html


google_ml_kit 是 Google 提供的一套用于 Flutter 的机器学习工具包，它支持多种机器学习功能，如文本识别、人脸检测、条形码扫描等。然而，默认情况下，它并没有针对韩国语的特定优化。不过，你可以使用 google_ml_kit 中的文本识别功能来处理韩国语文本。

以下是如何在 Flutter 中使用 google_ml_kit 进行韩国语文本识别的步骤：

1. 添加依赖项

首先，在 pubspec.yaml 文件中添加 google_ml_kit 依赖项：

dependencies:
  flutter:
    sdk: flutter
  google_ml_kit: ^0.13.0

然后运行 flutter pub get 来安装依赖项。

2. 导入包

在需要使用 google_ml_kit 的 Dart 文件中导入包：

import 'package:google_ml_kit/google_ml_kit.dart';

3. 使用文本识别功能

google_ml_kit 提供了一个 TextRecognizer 类，可以用来识别图像中的文本。以下是一个简单的示例，展示如何使用 TextRecognizer 来识别韩国语文本：

import 'package:flutter/material.dart';
import 'package:google_ml_kit/google_ml_kit.dart';
import 'package:image_picker/image_picker.dart';
import 'dart:io';

void main() {
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      home: TextRecognitionScreen(),
    );
  }
}

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

class _TextRecognitionScreenState extends State<TextRecognitionScreen> {
  String _recognizedText = '';

  Future<void> _pickImageAndRecognizeText() async {
    final imagePicker = ImagePicker();
    final pickedFile = await imagePicker.pickImage(source: ImageSource.gallery);

    if (pickedFile != null) {
      final file = File(pickedFile.path);
      final inputImage = InputImage.fromFile(file);

      final textRecognizer = GoogleMlKit.vision.textRecognizer();
      final RecognizedText recognizedText = await textRecognizer.processImage(inputImage);

      setState(() {
        _recognizedText = recognizedText.text;
      });

      textRecognizer.close();
    }
  }

  [@override](/user/override)
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('韩国语文本识别'),
      ),
      body: Center(
        child: Column(
          mainAxisAlignment: MainAxisAlignment.center,
          children: [
            if (_recognizedText.isNotEmpty)
              Text('识别结果: $_recognizedText'),
            SizedBox(height: 20),
            ElevatedButton(
              onPressed: _pickImageAndRecognizeText,
              child: Text('选择图片并识别文本'),
            ),
          ],
        ),
      ),
    );
  }
}
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