Flutter文字识别插件focused_area_ocr_flutter的使用
Flutter文字识别插件focused_area_ocr_flutter的使用
focused_area_ocr_flutter
是一个基于OCR技术的文字识别插件,可以从相机聚焦区域中获取文本。该插件依赖于 google_mlkit_text_recognition
。
特性
通过这个插件,您可以从相机聚焦区域中提取文本内容。以下是插件的功能展示:
开始使用
iOS 设置
在 ios/Runner/Info.plist
文件中添加以下代码以请求相机和麦克风权限:
<key>NSCameraUsageDescription</key>
<string>your usage description here</string>
<key>NSMicrophoneUsageDescription</key>
<string>your usage description here</string>
编辑 ios/Runner/Info.plist
文件如下:
platform :ios, '12.0' # 或更新版本
...
# 添加这行:
$iOSVersion = '12.0' # 或更新版本
post_install do |installer|
# 添加这些行:
installer.pods_project.build_configurations.each do |config|
config.build_settings["EXCLUDED_ARCHS[sdk=*]"] = "armv7"
config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'] = $iOSVersion
end
installer.pods_project.targets.each do |target|
flutter_additional_ios_build_settings(target)
# 添加这些行:
target.build_configurations.each do |config|
if Gem::Version.new($iOSVersion) > Gem::Version.new(config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'])
config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'] = $iOSVersion
end
end
end
end
Android 设置
编辑 android/app/build.gradle
并设置以下SDK版本:
- minSdkVersion: 21
- targetSdkVersion: 33
- compileSdkVersion: 33
使用方法
这是一个使用 focused_area_ocr_flutter
插件的Flutter项目的完整示例:
import 'dart:async';
import 'package:flutter/material.dart';
import 'package:focused_area_ocr_flutter/focused_area_ocr_view.dart';
void main() {
WidgetsFlutterBinding.ensureInitialized();
runApp(const MyApp());
}
class MyApp extends StatelessWidget {
const MyApp({Key? key}) : super(key: key);
[@override](/user/override)
Widget build(BuildContext context) {
return MaterialApp(
title: 'Focused Area OCR Flutter',
theme: ThemeData(
colorScheme: ColorScheme.fromSeed(seedColor: Colors.deepPurple),
useMaterial3: true,
),
home: const MyHomePage(),
);
}
}
class MyHomePage extends StatefulWidget {
const MyHomePage({Key? key}) : super(key: key);
[@override](/user/override)
State<MyHomePage> createState() => _MyHomePageState();
}
class _MyHomePageState extends State<MyHomePage> {
final StreamController<String> controller = StreamController<String>();
final double _textViewHeight = 80.0;
[@override](/user/override)
Widget build(BuildContext context) {
final double statusBarHeight = MediaQuery.of(context).viewPadding.top;
final Offset focusedAreaCenter = Offset(
0,
(statusBarHeight + kToolbarHeight + _textViewHeight) / 2,
);
return Scaffold(
backgroundColor: Colors.black,
body: Stack(
children: [
FocusedAreaOCRView(
onScanText: (text) {
controller.add(text);
},
focusedAreaCenter: focusedAreaCenter,
),
Column(
children: [
SizedBox(
height: statusBarHeight + kToolbarHeight,
child: AppBar(
title: const Text('Focused Area OCR Flutter'),
backgroundColor: Colors.blue,
foregroundColor: Colors.white,
),
),
Container(
padding: const EdgeInsets.all(16.0),
width: double.infinity,
height: _textViewHeight,
color: Colors.black,
child: StreamBuilder<String>(
stream: controller.stream,
builder: (BuildContext context, AsyncSnapshot<String> snapshot) {
return Text(
snapshot.data != null ? snapshot.data! : '',
style: const TextStyle(color: Colors.white),
);
},
),
),
],
),
],
),
);
}
}
更多关于Flutter文字识别插件focused_area_ocr_flutter的使用的实战系列教程也可以访问 https://www.itying.com/category-92-b0.html
更多关于Flutter文字识别插件focused_area_ocr_flutter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,以下是如何在Flutter项目中集成和使用 focused_area_ocr_flutter
插件的一个基本示例。这个插件允许你进行局部区域的OCR(光学字符识别)。
步骤1:添加依赖
首先,在你的 pubspec.yaml
文件中添加 focused_area_ocr_flutter
依赖:
dependencies:
flutter:
sdk: flutter
focused_area_ocr_flutter: ^最新版本号 # 请替换为实际发布的最新版本号
步骤2:运行 Flutter pub get
在终端中运行以下命令以获取依赖项:
flutter pub get
步骤3:配置 Android 权限
由于OCR功能通常需要使用相机,因此你需要在 android/app/src/main/AndroidManifest.xml
文件中添加相机权限:
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.example.yourapp">
<uses-permission android:name="android.permission.CAMERA" />
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" />
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />
<!-- 其他配置 -->
</manifest>
步骤4:编写 Flutter 代码
在你的 Dart 文件中,你可以按照以下示例来使用 focused_area_ocr_flutter
插件:
import 'package:flutter/material.dart';
import 'package:focused_area_ocr_flutter/focused_area_ocr_flutter.dart';
import 'package:image_picker/image_picker.dart'; // 用于选择图像
void main() {
runApp(MyApp());
}
class MyApp extends StatelessWidget {
@override
Widget build(BuildContext context) {
return MaterialApp(
home: OcrScreen(),
);
}
}
class OcrScreen extends StatefulWidget {
@override
_OcrScreenState createState() => _OcrScreenState();
}
class _OcrScreenState extends State<OcrScreen> {
final ImagePicker _picker = ImagePicker();
File? _imageFile;
String _ocrResult = '';
Future<void> _pickImage() async {
final XFile? image = await _picker.pickImage(source: ImageSource.camera);
if (image != null && image.path != null) {
setState(() {
_imageFile = File(image.path!);
});
// 进行OCR识别
_performOCR();
}
}
Future<void> _performOCR() async {
if (_imageFile == null) return;
try {
// 假设你有一个矩形区域需要识别,这里使用整个图像作为示例
final Rect rect = Rect.fromLTWH(0, 0, _imageFile!.width!.toDouble(), _imageFile!.height!.toDouble());
final String result = await FocusedAreaOcrFlutter.performOcr(
imagePath: _imageFile!.path,
rect: rect,
language: 'eng', // 识别语言,例如 'eng' 表示英语
);
setState(() {
_ocrResult = result;
});
} catch (e) {
print('OCR Error: $e');
}
}
@override
Widget build(BuildContext context) {
return Scaffold(
appBar: AppBar(
title: Text('OCR Demo'),
),
body: Column(
mainAxisAlignment: MainAxisAlignment.center,
children: <Widget>[
_imageFile == null
? Text('No image selected.')
: Image.file(_imageFile!),
SizedBox(height: 20),
Text('OCR Result:'),
Text(_ocrResult, style: TextStyle(fontSize: 18)),
SizedBox(height: 20),
ElevatedButton(
onPressed: _pickImage,
child: Text('Pick Image from Camera'),
),
],
),
);
}
}
注意事项
- 依赖项:示例代码中使用了
image_picker
插件来选择图像。确保你已经在pubspec.yaml
中添加了image_picker
依赖,并运行flutter pub get
。 - 权限处理:在实际应用中,你可能需要在运行时请求相机和存储权限。可以使用
permission_handler
插件来处理这些权限请求。 - 错误处理:示例代码中的错误处理非常简单。在实际应用中,你可能需要更复杂的错误处理逻辑。
通过以上步骤,你应该能够在Flutter应用中成功集成并使用 focused_area_ocr_flutter
插件进行局部区域的OCR识别。