📚 Introduction

react-native-vision-camera-face-detector is a React Native library that integrates with the Vision Camera module to provide face detection functionality. It allows you to easily detect faces in real-time using the device's front and back camera. It also supports static image face detection.

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🏗️ Features

• Real-time face detection using front and back camera
• Adjustable face detection settings
• Optional native side face bounds, contour and landmarks auto scaling
• Can be combined with Skia Frame Processor

🧰 Installation

You need to install react-native-vision-camera following it's docs then:

yarn add [email protected]

[!WARNING] v2.0.0 is still in beta, but I think it's already usable in production apps if you only need portrait front-camera face detection. If your app depends on other device orientations, you’ll need to wait until #229 is resolved and a non-beta version is released.

Don't forget to add react-native-worklets plugin to babel.config.js. More details here.

🪲 Known Bugs

• Xcode is not showing IOS 26.0 Simulators: There's an excellent explanation about this issue here. TL;DR: Google needs to ship an ARM64 simulator slice for MLKit. Until then, the only workaround for IOS 26.0 is to test face detection on a physical device - thanks to @juanclaudiopardo.

💡 Usage

Recommended way (see Example App for Skia usage):

import { 
  StyleSheet, 
  Text, 
  View 
} from 'react-native'
import { 
  useEffect, 
  useState,
  useRef
} from 'react'
import {
  Frame,
  useCameraDevice
} from 'react-native-vision-camera'
import {
  Face,
  Camera
} from 'react-native-vision-camera-face-detector'

export default function App() {
  const device = useCameraDevice('front')

  useEffect(() => {
    (async () => {
      const status = await Camera.requestCameraPermission()
      console.log({ status })
    })()
  }, [device])

  function handleFacesDetected(
    faces: Face[]
  ) { 
    console.log('faces', faces.length)
  }

  return (
    <View style={{ flex: 1 }}>
      {!!device? <Camera
        runClassifications
        runContours
        runLandmarks
        performanceMode={'fast'}
        onFacesDetected={ handleFacesDetected }
        style={StyleSheet.absoluteFill}
        device={device}
      /> : <Text>
        No Device
      </Text>}
    </View>
  )
}

Or use it following vision-camera docs:

import { 
  StyleSheet, 
  Text, 
  View,
  NativeModules,
  Platform
} from 'react-native'
import { 
  useEffect, 
  useState,
  useRef
} from 'react'
import {
  Camera,
  runAsync,
  useCameraDevice,
  useFrameProcessor
} from 'react-native-vision-camera'
import { 
  Face,
  useFaceDetector,
  FaceDetectorOptions
} from 'react-native-vision-camera-face-detector'
import { Worklets } from 'react-native-worklets-core'

export default function App() {
  const device = useCameraDevice('front')
  // ❌ don't destruct hybrid objects ❌
  // const {detectFaces} = useFaceDetector(faceDetectorOptions)
  const faceDetector = useFaceDetector( {
    // detection options
  } )
  const asyncRunner = useAsyncRunner()
  const frameOutput = useFrameOutput({
    onFrame: (frame) => {
      'worklet'
      
      const wasHandled = asyncRunner.runAsync(() => {
        'worklet'

        const faces = faceDetector.detectFaces(frame)
        // ... do something with detected faces
        // ... chain something asynchronously

        // async task finished - dispose the Frame now.
        frame.dispose()
      })
      
      if (!wasHandled) {
        // `asyncRunner` is busy - drop this Frame!
        frame.dispose()
      } 
    }
  })

  useEffect(() => {
    (async () => {
      const status = await Camera.requestCameraPermission()
      console.log({ status })
    })()
  }, [device])

  return (
    <View style={{ flex: 1 }}>
      {!!device? <Camera
        style={StyleSheet.absoluteFill}
        device={device}
        isActive={true}
        outputs={[frameOutput]}
      /> : <Text>
        No Device
      </Text>}
    </View>
  )
}

As face detection is a heavy process you should run it in an asynchronously so it can be finished without blocking your camera preview. You should read vision-camera docs about this feature.

🖼️ Static Image Face Detection

You can detect faces in static images without the camera (picking images from your gallery/files) or you can use it to detect faces in photos taken from camera (see Example App):

Supported image sources:

• Requirings (require('path/to/file'))
• URI string (file://, content://, http(s)://)
• Object ({ uri: string })

import { useImageFaceDetector } from 'react-native-vision-camera-face-detector'

// ❌ don't destruct hybrid objects ❌
// const {detectFaces} = useImageFaceDetector({...})
const faceDetector = useImageFaceDetector( {
  // detection options
} )

// Using a bundled asset
const faces1 = await faceDetector.detectFaces(
  require('./assets/photo.jpg')
)
// Using a local file path or content URI (e.g. from an image picker)
const faces2 = await faceDetector.detectFaces(
  'file:///storage/emulated/0/Download/pic.jpg'
)
const faces3 = await faceDetector.detectFaces({ 
  uri: 'content://media/external/images/media/12345' 
})

console.log({ 
  faces1, 
  faces2, 
  faces3 
})

Face Detection Options

Image Face Detector

| Option | Description | Default | Options | | ------------- | ------------- | ------------- | ------------- | | performanceMode | Favor speed or accuracy when detecting faces. | fast | fast, accurate| | runLandmarks | Whether to attempt to identify facial landmarks: eyes, ears, nose, cheeks, mouth, and so on. | false | boolean | | runContours | Whether to detect the contours of facial features. Contours are detected for only the most prominent face in an image. | false | boolean | | runClassifications | Whether or not to classify faces into categories such as 'smiling', and 'eyes open'. | false | boolean | | minFaceSize | Sets the smallest desired face size, expressed as the ratio of the width of the head to width of the image. | 0.15 | number | | trackingEnabled | Whether or not to assign faces an ID, which can be used to track faces across images. Note that when contour detection is enabled, only one face is detected, so face tracking doesn't produce useful results. For this reason, and to improve detection speed, don't enable both contour detection and face tracking. | false | boolean |

Frame Face Detector (extends Image Face Detector)

| Option | Description | Default | Options | | ------------- | ------------- | ------------- | ------------- | | cameraFacing | Current active camera | front | front, back | | autoMode | Should handle auto scale (face bounds, contour and landmarks) and rotation on native side? If this option is disabled all detection results will be relative to frame coordinates, not to screen/preview. You should NOT use this option if you want to draw on screen using Skia Frame Processor. See this and this for more details. | false | boolean | | windowWidth | * Required if you want to use autoMode. You must handle your own logic to get screen sizes, with or without statusbar size, etc... | 1.0 | number | | windowHeight | * Required if you want to use autoMode. You must handle your own logic to get screen sizes, with or without statusbar size, etc... | 1.0 | number |

🔧 Troubleshooting

Here is a common issue when trying to use this package and how you can try to fix it:

• Regular javascript function cannot be shared. Try decorating the function with the 'worklet' keyword...:
  • If you're using react-native-reanimated maybe you're missing this step.
• Execution failed for task ':react-native-vision-camera-face-detector:compileDebugKotlin'...:
  • This error is probably related to gradle cache. Try this sollution first.
  • Also check this comment.

If you find other errors while using this package you're wellcome to open a new issue or create a PR with the fix.

👷 Built With

• React Native
• Google MLKit
• Vision Camera

📚 Author

Made with ❤️ by luicfrr