google_ml_kit 0.12.0

A Flutter plugin to use all APIs from Google's standalone ML Kit for mobile platforms.

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.

In versions 0.7.3 and earlier all features were included in a single plugin, but a lot of developers started to get issues with the size of their apps, because even though they only needed a single feature, the plugin included all the resources for the rest of the features, that increased the size of the app significantly.

Since version 0.8.0 we have split the plugin in multiple plugins to allow developers to use only what they need. google_ml_kit now is an umbrella plugin including all of the plugins. Start using or migrate to the new plugins to use only what you need. Go to each plugin to read about their requirements. If you find issues report and contribute with your pull requests.

Features

Vision APIs

Feature	Plugin	Source Code	Android	iOS
Barcode Scanning	google_mlkit_barcode_scanning		✅	✅
Face Detection	google_mlkit_face_detection		✅	✅
Image Labeling	google_mlkit_image_labeling		✅	✅
Object Detection and Tracking	google_mlkit_object_detection		✅	✅
Text Recognition	google_mlkit_text_recognition		✅	✅
Text Recognition V2	google_mlkit_text_recognition		✅	✅
Digital Ink Recognition	google_mlkit_digital_ink_recognition		✅	✅
Pose Detection	google_mlkit_pose_detection		✅	✅
Selfie Segmentation	google_mlkit_selfie_segmentation		✅	✅

Natural Language APIs

Feature	Plugin	Source Code	Android	iOS
Language Identification	google_mlkit_language_id		✅	✅
On-Device Translation	google_mlkit_translation		✅	✅
Smart Reply	google_mlkit_smart_reply		✅	✅
Entity Extraction	google_mlkit_entity_extraction		✅	✅

Getting Started

Before you get started read about the requirements and known issues of this plugin here.

Go to the documentation of each plugin to learn how to use it.

Example app

Find the example app here.

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.