Flutter苹果视觉对象识别插件apple_vision_object的使用
Flutter 苹果视觉对象识别插件 apple_vision_object 的使用
apple_vision_object
Apple Vision 自拍检测是一个 Flutter 插件,使 Flutter 应用能够使用 Apple Vision 自拍检测。
- 该插件并非由 Apple 赞助或维护。作者是希望为 macOS 创建类似 Google ML Kit 的开发者。
要求
MacOS
- 最低 osx 部署目标:10.13
- Xcode 13 或更新版本
- Swift 5
- ML Kit 仅支持 64 位架构(x86_64 和 arm64)
iOS
- 最低 osx 部署目标:14.0
- Xcode 13 或更新版本
- Swift 5
- ML Kit 仅支持 64 位架构(x86_64 和 arm64)
开始使用
首先需要导入 'package:apple_vision/apple_vision.dart';
final GlobalKey cameraKey = GlobalKey(debugLabel: "cameraKey");
AppleVisionObjectController visionController = AppleVisionObjectController();
InsertCamera camera = InsertCamera();
Size imageSize = const Size(640, 640 * 9 / 16);
String? deviceId;
bool loading = true;
List<ObjectData>? objectData;
late double deviceWidth;
late double deviceHeight;
[@override](/user/override)
void initState() {
camera.setupCameras().then((value) {
setState(() {
loading = false;
});
camera.startLiveFeed((InputImage i) {
if (i.metadata?.size != null) {
imageSize = i.metadata!.size;
}
if (mounted) {
Uint8List? image = i.bytes;
visionController.processImage(image!, imageSize).then((data) {
objectData = data;
// print(objectData!.objects);
setState(() {});
});
}
});
});
super.initState();
}
[@override](/user/override)
void dispose() {
camera.dispose();
super.dispose();
}
[@override](/user/override)
Widget build(BuildContext context) {
deviceWidth = MediaQuery.of(context).size.width;
deviceHeight = MediaQuery.of(context).size.height;
return Stack(
children: [
SizedBox(
width: imageSize.width,
height: imageSize.height,
child: loading ? Container() : CameraSetup(camera: camera, size: imageSize)
),
] + showRects()
);
}
List<Widget> showRects() {
if (objectData == null || objectData!.isEmpty) return [];
List<Widget> widgets = [];
for (int i = 0; i < objectData!.length; i++) {
// if(objectData!.objects[i]. confidence > 0.5){
widgets.add(
Positioned(
top: objectData![i].object.top,
left: objectData![i].object.left,
child: Container(
width: objectData![i].object.width * imageSize.width,
height: objectData![i].object.height * imageSize.height,
decoration: BoxDecoration(
color: Colors.transparent,
border: Border.all(width: 1, color: Colors.green),
borderRadius: BorderRadius.circular(5)
),
child: Text(
'${objectData![i].label}: ${objectData![i].confidence}',
style: const TextStyle(
color: Colors.white,
fontSize: 12
),
)
)
)
);
//}
}
return widgets;
}
Widget loadingWidget() {
return Container(
width: deviceWidth,
height: deviceHeight,
color: Theme.of(context).canvasColor,
alignment: Alignment.center,
child: const CircularProgressIndicator(color: Colors.blue)
);
}
示例
完整的示例代码可以在以下链接找到: example/lib/main.dart
import 'package:apple_vision_object/apple_vision_object.dart';
import 'package:flutter/material.dart';
import '../camera/camera_insert.dart';
import 'package:flutter/foundation.dart';
import 'package:flutter/services.dart';
import 'camera/input_image.dart';
void main() {
runApp(const MyApp());
}
class MyApp extends StatelessWidget {
const MyApp({super.key});
// This widget is the root of your application.
[@override](/user/override)
Widget build(BuildContext context) {
return MaterialApp(
title: 'Flutter Demo',
theme: ThemeData(
primarySwatch: Colors.blue,
),
home: const VisionObject(),
);
}
}
class VisionObject extends StatefulWidget {
const VisionObject({
Key? key,
this.onScanned
}) : super(key: key);
final Function(dynamic data)? onScanned;
[@override](/user/override)
_VisionObject createState() => _VisionObject();
}
class _VisionObject extends State<VisionObject> {
final GlobalKey cameraKey = GlobalKey(debugLabel: "cameraKey");
AppleVisionObjectController visionController = AppleVisionObjectController();
InsertCamera camera = InsertCamera();
Size imageSize = const Size(640, 640 * 9 / 16);
String? deviceId;
bool loading = true;
List<ObjectData>? objectData;
late double deviceWidth;
late double deviceHeight;
[@override](/user/override)
void initState() {
camera.setupCameras().then((value) {
setState(() {
loading = false;
});
camera.startLiveFeed((InputImage i) {
if (i.metadata?.size != null) {
imageSize = i.metadata!.size;
}
if (mounted) {
Uint8List? image = i.bytes;
visionController.processImage(image!, imageSize).then((data) {
objectData = data;
// print(objectData!.objects);
setState(() {});
});
}
});
});
super.initState();
}
[@override](/user/override)
void dispose() {
camera.dispose();
super.dispose();
}
[@override](/user/override)
Widget build(BuildContext context) {
deviceWidth = MediaQuery.of(context).size.width;
deviceHeight = MediaQuery.of(context).size.height;
return Stack(
children: [
SizedBox(
width: imageSize.width,
height: imageSize.height,
child: loading ? Container() : CameraSetup(camera: camera, size: imageSize)
),
] + showRects()
);
}
List<Widget> showRects() {
if (objectData == null || objectData!.isEmpty) return [];
List<Widget> widgets = [];
for (int i = 0; i < objectData!.length; i++) {
// if(objectData!.objects[i]. confidence > 0.5){
widgets.add(
Positioned(
top: objectData![i].object.top,
left: objectData![i].object.left,
child: Container(
width: objectData![i].object.width * imageSize.width,
height: objectData![i].object.height * imageSize.height,
decoration: BoxDecoration(
color: Colors.transparent,
border: Border.all(width: 1, color: Colors.green),
borderRadius: BorderRadius.circular(5)
),
child: Text(
'${objectData![i].label}: ${objectData![i].confidence}',
style: const TextStyle(
color: Colors.white,
fontSize: 12
),
)
)
)
);
//}
}
return widgets;
}
Widget loadingWidget() {
return Container(
width: deviceWidth,
height: deviceHeight,
color: Theme.of(context).canvasColor,
alignment: Alignment.center,
child: const CircularProgressIndicator(color: Colors.blue)
);
}
}
更多关于Flutter苹果视觉对象识别插件apple_vision_object的使用的实战教程也可以访问 https://www.itying.com/category-92-b0.html
更多关于Flutter苹果视觉对象识别插件apple_vision_object的使用的实战系列教程也可以访问 https://www.itying.com/category-92-b0.html
apple_vision_object
是一个 Flutter 插件,用于在 iOS 设备上利用 Apple 的 Vision 框架进行对象识别。这个插件可以帮助开发者在 Flutter 应用中轻松集成对象识别功能。以下是如何使用 apple_vision_object
插件的基本步骤:
1. 添加依赖
首先,在 pubspec.yaml
文件中添加 apple_vision_object
插件的依赖:
dependencies:
flutter:
sdk: flutter
apple_vision_object: ^latest_version
然后,运行 flutter pub get
来安装依赖。
2. 导入插件
在你的 Dart 文件中导入 apple_vision_object
插件:
import 'package:apple_vision_object/apple_vision_object.dart';
3. 初始化对象识别
你可以通过 AppleVisionObject
类来初始化和管理对象识别。
AppleVisionObject visionObject = AppleVisionObject();
4. 执行对象识别
要执行对象识别,你需要提供一个图像(例如从相机或图库中获取的图像)。假设你已经有了一个 UIImage
对象(在 iOS 上),你可以将其传递给 AppleVisionObject
进行识别。
void recognizeObjects(UIImage image) async {
try {
List<RecognizedObject> objects = await visionObject.recognizeObjects(image);
for (var object in objects) {
print("Detected object: ${object.label}");
print("Confidence: ${object.confidence}");
print("Bounding box: ${object.boundingBox}");
}
} catch (e) {
print("Error recognizing objects: $e");
}
}
5. 处理识别结果
recognizeObjects
方法返回一个 List<RecognizedObject>
,其中每个 RecognizedObject
包含以下信息:
label
: 识别出的对象的标签(例如 “dog”, “car” 等)。confidence
: 识别结果的置信度,范围从 0 到 1。boundingBox
: 对象在图像中的边界框,通常是一个CGRect
。
你可以根据这些信息在你的应用中显示识别结果,例如绘制边界框或在 UI 中显示标签。
6. 处理权限
在 iOS 上使用相机或访问图库时,可能需要请求相应的权限。你需要在 Info.plist
文件中添加相应的权限描述。
<key>NSCameraUsageDescription</key>
<string>需要访问相机以进行对象识别</string>
<key>NSPhotoLibraryUsageDescription</key>
<string>需要访问图库以选择图像进行对象识别</string>
7. 集成相机或图库
为了获取图像,你可以使用 camera
插件或 image_picker
插件来从相机或图库中获取图像。
import 'package:image_picker/image_picker.dart';
void pickImage() async {
final ImagePicker _picker = ImagePicker();
final XFile? image = await _picker.pickImage(source: ImageSource.gallery);
if (image != null) {
// 将 XFile 转换为 UIImage(假设你有一个方法可以做到这一点)
UIImage uiImage = await convertXFileToUIImage(image);
recognizeObjects(uiImage);
}
}