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google_mlkit_commons

一个 Flutter 插件,包含用于在移动平台上实现 Google 的独立 ML Kit 的通用文件。

AndroidiOS
近 30 天下载
63.1万
喜欢数
38
Pub 分数
150

安装插件

flutter pub add google_mlkit_commons

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。

一个 Flutter 插件,提供用于将 Google 的独立 ML Kit 集成到移动应用程序中的共享实用工具和通用组件。它支持 Android 和 iOS 上的机器学习任务,使开发者能够利用预训练模型实现文本识别、人脸检测和条形码扫描等功能。该包通过提供可重用的代码和跨平台的一致接口,简化了实现过程。专为与 Flutter 生态系统中的其他 Google ML Kit 插件无缝集成而设计。

适合场景

  • 图像中的文本识别
  • 条形码扫描
  • 人脸检测
  • 图像标注
  • 目标检测
  • 实时处理

主要特点

  • 共享实用程序类
  • 跨平台兼容性
  • 与 Google ML Kit 的集成
  • 轻量级核心依赖项
  • 一致的 API 设计
  • 对 Android 和 iOS 的支持

适合对象

  • 使用 Flutter 的移动应用开发者
  • 需要设备端机器学习推理的项目
  • 需要OCR或计算机视觉的应用
  • 开发人工智能功能的开发者
  • 使用 Google ML Kit 进行移动开发的团队

使用建议

  • 需要额外的 ML Kit 插件以启用特定功能
  • 仅限移动平台
  • 依赖 Google Play 服务(Android)
  • 可能增加应用大小
  • 需要相机和存储的正确权限
  • 不适用于服务器端处理

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.

所属分类

源码仓库

使用此插件的项目