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google_ml_kit

一个用于移动平台的 Flutter 插件,可使用 Google 独立 ML Kit 的所有 API。

AndroidiOS
近 30 天下载
3930
喜欢数
1200
Pub 分数
160

安装插件

flutter pub add google_ml_kit

插件介绍

基于插件公开信息、社区数据与项目使用情况整理的选型参考。

Google ML Kit 是一个 Flutter 插件,可提供对 Google 的 ML Kit API 的访问,适用于移动平台,使开发者能够将机器学习功能(如图像标记、人脸检测、文本识别和文档扫描)直接集成到其应用中。它支持 Android 和 iOS,提供针对设备端处理优化的预训练模型。该插件无需云连接即可简化强大计算机视觉和 OCR 功能的使用。通过简单的 API,可快速实现智能功能,例如条形码扫描、地标检测和从图像中提取文本。

适合场景

  • 实时图像文本识别
  • 文档扫描和提取
  • 面部和关键点检测
  • 条形码和二维码扫描
  • 图像标注和分类

主要特点

  • 设备端机器学习
  • 对 Android 和 iOS 的支持
  • 预训练模型用于常见任务
  • 与 Flutter 的轻松集成
  • 低延迟推理

适合对象

  • 需要OCR的移动应用
  • 需要实时图像分析的应用程序
  • 开发文档扫描仪的开发者
  • 使用设备端人工智能的项目
  • 专注于计算机视觉的Flutter应用

使用建议

  • 需要原生SDK设置才能实现完整功能
  • 模型大小可能会影响应用包大小
  • 性能取决于设备硬件
  • 对高级机器学习模型的自定义有限
  • 可能需要额外的权限以访问摄像头

原始 README

以下为关联源码仓库的 README 原文快照,最新内容请访问源码仓库。

Google's ML Kit for Flutter

Google's ML Kit for Flutter is a set of Flutter plugins that enable Flutter apps to use Google's standalone ML Kit.

Features

Vision APIs
Feature Plugin Source Code Android iOS
Barcode Scanning google_mlkit_barcode_scanning Pub Version GitHub ✅ ✅
Face Detection google_mlkit_face_detection Pub Version GitHub ✅ ✅
Face Mesh Detection (Beta) google_mlkit_face_mesh_detection Pub Version GitHub ✅ ❌
Text Recognition v2 google_mlkit_text_recognition Pub Version GitHub ✅ ✅
Image Labeling google_mlkit_image_labeling Pub Version GitHub ✅ ✅
Object Detection and Tracking google_mlkit_object_detection Pub Version GitHub ✅ ✅
Digital Ink Recognition google_mlkit_digital_ink_recognition Pub Version GitHub ✅ ✅
Pose Detection (Beta) google_mlkit_pose_detection Pub Version GitHub ✅ ✅
Selfie Segmentation (Beta) google_mlkit_selfie_segmentation Pub Version GitHub ✅ ✅
Subject Segmentation (Beta) google_mlkit_subject_segmentation Pub Version GitHub ✅ ❌
Document Scanner google_mlkit_document_scanner Pub Version GitHub ✅ ❌
Natural Language APIs
Feature Plugin Source Code Android iOS
Language Identification google_mlkit_language_id Pub Version GitHub ✅ ✅
On-Device Translation google_mlkit_translation Pub Version GitHub ✅ ✅
Smart Reply google_mlkit_smart_reply Pub Version GitHub ✅ ✅
Entity Extraction (Beta) google_mlkit_entity_extraction Pub Version GitHub ✅ ✅
GenAI APIs

⚠️ Important: GenAI APIs are built on top of AICore and will not support all Android devices. These APIs require devices with AICore support. Please check device compatibility before using these features in production.

⚠️ Production Disclaimer: Using GenAI plugins in production is the responsibility of the developers consuming the plugins, not the authors. The authors provide these plugins as-is and are not responsible for any issues, failures, or compatibility problems that may arise from using these plugins in production environments.

Feature Plugin Source Code Android iOS
Summarization (Beta) google_mlkit_genai_summarization Pub Version GitHub ✅ ❌
Proofreading (Beta) google_mlkit_genai_proofreading Pub Version GitHub ✅ ❌
Rewriting (Beta) google_mlkit_genai_rewriting Pub Version GitHub ✅ ❌
Image Description (Beta) google_mlkit_genai_image_description Pub Version GitHub ✅ ❌
Speech Recognition (Alpha) google_mlkit_genai_speech_recognition Pub Version GitHub ✅ ❌
Prompt (Beta) google_mlkit_genai_prompt Pub Version GitHub ✅ ❌

PLEASE READ THIS before continuing or posting a new issue:

  • Google's ML Kit was build only for mobile platforms: iOS and Android apps. Web or any other platform is not supported, you can request support for those platform to Google in their repo.

  • This plugin is not sponsored or maintained by Google. The authors are developers excited about Machine Learning that wanted to expose Google's native APIs to Flutter.

  • Google's ML Kit APIs are only developed natively for iOS and Android. This plugin uses Flutter Platform Channels as explained here.

    Messages are passed between the client (the app/plugin) and host (platform) using platform channels as illustrated in this diagram:

    Messages and responses are passed asynchronously, to ensure the user interface remains responsive. To read more about platform channels go here.

    Because this plugin uses platform channels, no Machine Learning processing is done in Flutter/Dart, all the calls are passed to the native platform using MethodChannel in Android and FlutterMethodChannel in iOS, and executed using Google's native APIs. Think of this plugin as a bridge between your app and Google's native ML Kit APIs. This plugin only passes the call to the native API and the processing is done by Google's API. It is important that you understand this concept when it comes to debugging errors for your ML model and/or app.

  • Since the plugin uses platform channels, you may encounter issues with the native API. Before submitting a new issue, identify the source of the issue. You can run both iOS and/or Android native example apps by Google and make sure that the issue is not reproducible with their native examples. If you can reproduce the issue in their apps then report the issue to Google. The authors do not have access to the source code of their native APIs, so you need to report the issue to them. If you find that their example apps are okay and still you have an issue using this plugin, then look at our closed and open issues. If you cannot find anything that can help you then report the issue and provide enough details. Be patient, someone from the community will eventually help you.

Migrating from ML Kit for Firebase to the new standalone ML Kit SDK

When Migrating from ML Kit for Firebase to the new standalone ML Kit SDK read this guide.

For Android details read this.

For iOS details read this.

Example app

Find the example app here.

Consuming image streams on Android

Until https://github.com/flutter/flutter/issues/145961 is resolved, the most recent version of the camera package doesn't support the required image formats. To make things work, manually add the legacy plugin via the instructions from https://pub.dev/packages/camera_android.

Contributing

Contributions are welcome. In case of any problems look at existing issues, if you cannot find anything related to your problem then open an issue. Create an issue before opening a pull request for non trivial fixes. In case of trivial fixes open a pull request directly.

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依赖

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源码仓库

使用此插件的项目