mlkit 0.1.1

A Flutter plugin to use the Firebase ML Kit.

mlkit

A Flutter plugin to use the Firebase ML Kit.

Note: This plugin is still under development, and some APIs might not be available yet. Feedback and Pull Requests are most welcome!

Features

Feature	Android	iOS
Recognize text(on device)	✅	✅
Recognize text(cloud)	yet	yet
Detect faces(on device)	yet	yet
Scan barcodes(on device)	yet	yet
Label Images(on device)	yet	yet
Label Images(cloud)	yet	yet
Recognize landmarks(cloud)	yet	yet
Custom model	yet	yet

What features are available on device or in the cloud?

Usage

To use this plugin, add mlkit as a dependency in your pubspec.yaml file.

Getting Started

Check out the example directory for a sample app using Firebase Cloud Messaging.

Android Integration

To integrate your plugin into the Android part of your app, follow these steps:

1. Using the Firebase Console add an Android app to your project: Follow the assistant, download the generated google-services.json file and place it inside android/app. Next, modify the android/build.gradle file and the android/app/build.gradle file to add the Google services plugin as described by the Firebase assistant.

iOS Integration

To integrate your plugin into the iOS part of your app, follow these steps:

1. Using the Firebase Console add an iOS app to your project: Follow the assistant, download the generated GoogleService-Info.plist file, open ios/Runner.xcworkspace with Xcode, and within Xcode place the file inside ios/Runner. Don't follow the steps named "Add Firebase SDK" and "Add initialization code" in the Firebase assistant.

2. Remove the use_frameworks! line from ios/Podfile (workaround for flutter/flutter#9694).

Dart/Flutter Integration

From your Dart code, you need to import the plugin and instantiate it:

import 'package:mlkit/mlkit.dart';

FirebaseVisionTextDetector detector = FirebaseVisionTextDetector.instance;

var currentLabels = await detector.detectFromPath(_file?.path);