react-native-facerecognition

React Native Face Recognition [Android]

Summary

💥 New version with new features @3.0.0!

---

Do you ever want to detect and recognize faces? this is now possible especially in react native, This lib aims to provide best detection and recognition results as well as facial landmarks.

Important

• New to Face Recognition? We recommend you start with the default values which described below.
• Looking to contribute? feel free to join our community on Slack, and take a look into coming updates.
• If the library doesn't work with you, you need to check your mobile's CPU if it one of those:
  • x86 CPU Download this package Click here
  • x86_64 CPU Download this package Click here
  • arm64-v8a CPU Download this package Click here
    

After downloading you need to put that package into this location react-native-facerecognition/android/app/src/main/jniLibs and that's all!

⚠️ Since we're focusing our efforts on next updates, we are really welcome for any issues/pulls to improve the way we go.

Features

• Face Detection
• Face Recognition (LBPH Algorithm only)
• Tracking face
• Facial landmarks
• Train your own dataset
• Without any internet!
• All devices supported.

Upcoming updates

• Add EagenFace Algorithm ❌
• Add Fisherface Algorithm ❌
• UI Component ✔️

Real world examples

---

Code Example

import Camera from 'react-native-facerecognition';
...
<Camera
          ref={(cam) => {
            this.camera = cam;
          }}
          style={styles.preview}
          aspect={Camera.constants.Aspect.fill}
          captureQuality={Camera.constants.CaptureQuality.high}
          touchToFocus
          torchMode={Camera.constants.TorchMode.on}
          rotateMode={Camera.constants.RotateMode.on}
          cameraType={Camera.constants.CameraType.front}
          model = {Camera.constants.Model.lbp}
          dataset
          distance = {200}
          onTrained = {this.onTrained}
          onRecognized = {this.onRecognized}
          onUntrained = {this.onUntrained}
          onUnrecognized = {this.onUnrecognized}
        />

🔥 Checkout our main example to get the right way to start.

Get Started

npm install react-native-facerecognition --save
or
yarn add react-native-facerecognition

⚠️ We are highly recommend you to use Deamon gradle for building faster and ignore any error may happen.

• Inside build.gradle put this line in projectName/android/build.gradle.

repositories {
        ...
        google()
   }
   ...
   classpath 'com.android.tools.build:gradle:3.0.1'
   ...
   allprojects {
    repositories {
        ...
        maven { url "https://jitpack.io" }
        maven { url "https://maven.google.com" }
        ...
        }
       }
       

• And go to projectName/android/gradle/wrapper/gradle-wrapper.properties and change this.

distributionUrl=https\://services.gradle.org/distributions/gradle-4.4-all.zip

1.1 Direct Setup

• You would need to link the library once you install it.

react-native link react-native-facerecognition 

• Add this line into build.gradle and the path projectName/android/app/build.gradle.

compileSdkVersion 26
buildToolsVersion "26.0.2"
....
....

• Then put this lines into settings.gradle and the path projectName/android/settings.gradle.

include ':openCV'
project(':openCV').projectDir = new File(rootProject.projectDir, '../node_modules/react-native-facerecognition/android/openCV')

• You need to put permissions to use Camera on AndroidManifest.xml and remove the line below.

<uses-permission android:name="android.permission.CAMERA" />
<uses-feature android:name="android.hardware.camera" android:required="true"/>
<uses-feature android:name="android.hardware.camera.autofocus" android:required="false"/>
<uses-feature android:name="android.hardware.camera.front" android:required="true"/>
<uses-feature android:name="android.hardware.camera.front.autofocus" android:required="false"/>
...
<activity
  android:windowSoftInputMode="adjustResize" // remove this in order to make UI works well

1.2 Manual Setup

• First, put this line into MainApplication.java and its path projectName/android/app/src/main/java/com/projectName/MainApplication.java.

import opencv.android.FaceModulePackage;
...
return Arrays.<ReactPackage>asList(
  new FaceModulePackage()
);

• Then add this line into build.gradle and the path projectName/android/app/build.gradle.

compileSdkVersion 26
buildToolsVersion "26.0.2"
....
....
....
dependencies {
  compile project(':react-native-facerecognition')
  }

• Inside settings.gradle put these lines you can find the path at projectName/android/settings.gradle

include ':react-native-facerecognition'
project(':react-native-facerecognition').projectDir = new File(rootProject.projectDir, '../node_modules/react-native-facerecognition/android/app')
include ':openCV'
project(':openCV').projectDir = new File(rootProject.projectDir, '../node_modules/react-native-facerecognition/android/openCV')

• You need to put permissions to use Camera on AndroidManifest.xml and remove the line below.

<uses-permission android:name="android.permission.CAMERA" />
<uses-feature android:name="android.hardware.camera" android:required="true"/>
<uses-feature android:name="android.hardware.camera.autofocus" android:required="false"/>
<uses-feature android:name="android.hardware.camera.front" android:required="true"/>
<uses-feature android:name="android.hardware.camera.front.autofocus" android:required="false"/>
...
<activity
  android:windowSoftInputMode="adjustResize" // remove this in order to make UI works well

🔥 You're ready to go!

Documentation

How it works:

There's three main process you have to follow the first one is to detect the face first on the image, Then you do some training on every face (Person1 & Person2 & Person3) you will need to recognize later which is the second process. Then, you can now after training, Recognize all these faces by their names.

1.3 Props

model

• Camera.constants.Model.cascade [DEPRECATED]
  • Higher recall & More trained faces
• Camera.constants.Model.landmarks
  • Higher accuracy at recognition
• Camera.constants.Model.lbp
  • Higher precision & Faster & Less trained faces

cameraType

• Camera.constants.CameraType.front
• Camera.constants.CameraType.back

captureQuality

• Camera.constants.CaptureQuality.low
• Camera.constants.CaptureQuality.medium
• Camera.constants.CaptureQuality.high

aspect

• Camera.constants.Aspect.fit
• Camera.constants.Aspect.fill
• Camera.constants.Aspect.stretch

dataset (default: false)

• train your own images. copy Images to that location at android/app/src/main/assets/dataset inside that folder.

if you will use this, you need to use lbp model only in order to make it work. Please see the test photo there to know how to rename your photos according to that test photo every photo should be named like that name_number.jpg/png.

distance

<Camera distance = {200} />

• Distance between the face and the camera. This is very important to keep recognition always works and to help make the result mainly true (this effects the recognition result grossly).

rotateMode - (Landscape/Portrait)

• Camera.constants.RotateMode.on
• Camera.constants.RotateMode.off

1.4 Functions

• takePicture()

Take a picture then process it to detect face inside

• train(Object)

Train the algorithm with a new detected face

• identify()

Take a picture then predict whom face belongs to

• clear()

Clear all previous trained faces

1.5 Events

onTrained

• Called after success training

onUntrained

• If training fails this function will be called with the error

onRecognized You get details about recognized face:

• name The face name
• confidence This number indicates how much the result is true. Usually low number < 100 means a good result depends on the distance you put

onUnrecognized

• If recognition fails this function will be called with the error

Recommendations

If you're not familiar with OpenCV and face recognition you have to be in safe and use our default arguments as we care about all of the details for you. In case of using your own arguments please note that you may effect the accuracy depends on your settings.

• Recognition default arguments
  Arguments

  • distance = {200}

• Training images count
  Minimum

  • There's no maximum but the average is 3~4 photos per face to guarantee high accuracy

Updates

🚀 Updates you can find all previous versions and updates up to date!

Thank to

rn-openALPR rn-camera

Licence

MIT