rn-mlkit-custom-model v0.1.1

rn-mlkit-custom-model

MLKit Custom Model bridge for React-native running on iOS and Android.

Native code inspired from the Firebase documentation: https://firebase.google.com/docs/ml-kit/use-custom-models

The example provided uses react-native camera and mobilenet_v1_1.0_224.

Getting started

$ npm install rn-mlkit-custom-model --save

Mostly automatic installation

$ react-native link rn-mlkit-custom-model

Don't forget to ...

• Bundle model assets to the app Android instructions / iOS instructions. You can download the files here.

• Connect your app to Firebase Android instructions / iOS instructions

• install CocoaPods in your react-native project and add the following line to your Podfile then run pod install (iOS only)

  	 ```
  pod 'Firebase/Analytics'
  pod 'Firebase/MLModelInterpreter'

Manual installation

iOS

1. In XCode, in the project navigator, right click Libraries ➜ Add Files to [your project's name]
2. Go to node_modules ➜ rn-mlkit-custom-model and add RNMlkitCustomModel.xcodeproj
3. In XCode, in the project navigator, select your project. Add libRNMlkitCustomModel.a to your project's Build Phases ➜ Link Binary With Libraries
4. Run your project (Cmd+R)<

Android

1. Open up android/app/src/main/java/[...]/MainActivity.java

• Add import com.reactlibrary.RNMlkitCustomModelPackage; to the imports at the top of the file
• Add new RNMlkitCustomModelPackage() to the list returned by the getPackages() method

2. Append the following lines to android/settings.gradle:

   include ':rn-mlkit-custom-model'
   project(':rn-mlkit-custom-model').projectDir = new File(rootProject.projectDir, 	'../node_modules/rn-mlkit-custom-model/android')

3. Insert the following lines inside the dependencies block in android/app/build.gradle:

     compile project(':rn-mlkit-custom-model')

Usage

import RNMlkitCustomModel from 'rn-mlkit-custom-model';

//init the model
RNMlkitCustomModel.initModel()

//run the model on the provided image
RNMlkitCustomModel.runModelInference(IMAGE_URI).then(results => {
	console.log(results)
})