NativeScript Yoonit Camera

A NativeScript plugin to provide:

• Modern Android Camera API Camera X
• Camera preview (Front & Back)
• PyTorch integration (Android)
• Computer vision pipeline
• Face detection, capture and image crop
• Understanding of the human face
• Frame capture
• Capture timed images
• QR Code scanning

More about...

The plugin's core is the native layer. Every change in the native layer, reflects here. This plugin, the Yoonit Camera, we can say that is an aggregation of many Yoonit's native libs:

• Android Yoonit Camera: Android core camera lib;
• iOS Yoonit Camera: iOS core camera lib;
• Android Yoonit Facefy: Android face detection and analysis;
• iOS Yoonit Facefy: iOS face detection and analysis;

All this native libs can be used independently.

Table Of Contents

• Installation
• Usage
  • VueJS Plugin
  • Vue Component
• API
  • Props
  • Methods
  • Events
  • Face Analysis
  • Head Movements
  • Image Quality
  • Messages
• Contribute

Installation

npm i -s @yoonit/nativescript-camera  

Usage

All the functionalities that the @yoonit/nativescript-camera provides is accessed through the YoonitCamera component, that includes the camera preview. Below we have the basic usage code, for more details, your can see the Methods, Events or the Demo Vue.

VueJS Plugin

main.js

import Vue from 'nativescript-vue'  
import YoonitCamera from '@yoonit/nativescript-camera/vue'  
  
Vue.use(YoonitCamera)  

After that, you can access the camera object in your entire project using this.$yoo.camera

Vue Component

App.vue

<template>
  <Page @loaded="onLoaded">
    <YoonitCamera
      ref="yooCamera"
      lens="front"
      captureType="face"
      imageCapture=true
      imageCaptureAmount=10
      imageCaptureInterval=500
      detectionBox=true
      @faceDetected="doFaceDetected"
      @imageCaptured="doImageCaptured"
      @endCapture="doEndCapture"
      @qrCodeContent="doQRCodeContent"
      @status="doStatus"
      @permissionDenied="doPermissionDenied"
    />
  </Page>
</template>

<script>
  export default {
    data: () => ({}),

    methods: {
      async onLoaded() {

        console.log('[YooCamera] Getting Camera view')
        this.$yoo.camera.registerElement(this.$refs.yooCamera)

        console.log('[YooCamera] Getting permission')
        if (await this.$yoo.camera.requestPermission()) {
          
          console.log('[YooCamera] Permission granted, start preview')
          this.$yoo.camera.preview()
        }
      },

      doFaceDetected({ 
        x, 
        y, 
        width, 
        height,
        leftEyeOpenProbability,
        rightEyeOpenProbability,
        smilingProbability,
        headEulerAngleX,
        headEulerAngleY,
        headEulerAngleZ
      }) {
        console.log(
          '[YooCamera] doFaceDetected',
          `
          x: ${x}
          y: ${y}
          width: ${width}
          height: ${height}
          leftEyeOpenProbability: ${leftEyeOpenProbability}
          rightEyeOpenProbability: ${rightEyeOpenProbability}
          smilingProbability: ${smilingProbability}
          headEulerAngleX: ${headEulerAngleX}
          headEulerAngleY: ${headEulerAngleY}
          headEulerAngleZ: ${headEulerAngleZ}
          `
        )
        if (!x || !y || !width || !height) {
          this.imagePath = null
        }
      },

      doImageCaptured({
        type,
        count,
        total,
        image: {
          path,
          source
        },
        inferences,
        darkness,
        lightness,
        sharpness
      }) {
        if (total === 0) {
          console.log('[YooCamera] doImageCreated', `${type}: [${count}] ${path}`)
          this.imageCreated = `${count}`
        } else {
          console.log('[YooCamera] doImageCreated', `${type}: [${count}] of [${total}] - ${path}`)
          this.imageCreated = `${count} de ${total}`
        }
        console.log('[YooCamera] Mask Pytorch', inferences)
        
        console.log('[YooCamera] Image Quality Darkness:', darkness)
        console.log('[YooCamera] Image Quality Lightness', lightness)
        console.log('[YooCamera] Image Quality Sharpness', sharpness)
        this.imagePath = source
      },

      doEndCapture() {
        console.log('[YooCamera] doEndCapture')
      },

      doQRCodeContent({ content }) {
        console.log('[YooCamera] doQRCodeContent', content)
      },

      doStatus({ status }) {
        console.log('[YooCamera] doStatus', status)
      },

      doPermissionDenied() {
        console.log('[YooCamera] doPermissionDenied')
      }
    }
  }
</script>

API

Props

Methods

Events

Face Analysis

The face analysis is the response send by the onFaceDetected. Here we specify all the parameters.

Head Movements

Here we're explaining the above gif and how reached the "results". Each "movement" (vertical, horizontal and tilt) is a state, based in the angle in degrees that indicate head direction;

Image Quality

The image quality is the classification of the three attributes: darkness, lightness and sharpness. Result available in the imageCapture event. Let's see each parameter specifications:

Messages

Pre-define message constants used by the status event.

Contribute and make it better

Clone the repo, change what you want and send PR.

For commit messages we use Conventional Commits.

Contributions are always welcome, some people that already contributed!

Code with ❤ by the Cyberlabs AI Front-End Team