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justadudewhohacksjustadudewhohacks
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added some more nodejs examples + move all examples into examples directory
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‎.gitignore

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@@ -5,4 +5,5 @@ tmp
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proto
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weights_uncompressed
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docs
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docs
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out

‎.npmignore

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.rpt2_cache
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examples
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examples-nodejs
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proto
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weights
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weights_uncompressed

‎examples-nodejs/faceDetection.ts

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‎examples-nodejs/faceLandmarkDetection.ts

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‎examples/package-lock.json renamed to ‎examples/examples-browser/package-lock.json

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‎examples/package.json renamed to ‎examples/examples-browser/package.json

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‎examples/public/github_link_icon.png renamed to ‎examples/examples-browser/public/github_link_icon.png

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‎examples/public/js/bbt.js renamed to ‎examples/examples-browser/public/js/bbt.js

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const classes = ['amy', 'bernadette', 'howard', 'leonard', 'penny', 'raj', 'sheldon', 'stuart']
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function getFaceImageUri(className, idx) {
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return `images/${className}/${className}${idx}.png`
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return `${className}/${className}${idx}.png`
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}
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function renderFaceImageSelectList(selectListId, onChange, initialValue) {

‎examples/public/js/commons.js renamed to ‎examples/examples-browser/public/js/commons.js

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function getImageUri(imageName) {
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return `images/${imageName}`
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}
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async function requestExternalImage(imageUrl) {
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const res = await fetch('fetch_external_image', {
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method: 'post',

‎examples/public/js/drawing.js renamed to ‎examples/examples-browser/public/js/drawing.js

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‎examples/public/js/faceDetectionControls.js renamed to ‎examples/examples-browser/public/js/faceDetectionControls.js

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‎examples/public/js/imageSelectionControls.js renamed to ‎examples/examples-browser/public/js/imageSelectionControls.js

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@@ -17,15 +17,15 @@ function renderImageSelectList(selectListId, onChange, initialValue) {
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renderOption(
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select,
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imageName,
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getImageUri(imageName)
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imageName
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)
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)
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}
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renderSelectList(
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selectListId,
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onChange,
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getImageUri(initialValue),
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initialValue,
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renderChildren
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)
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}

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‎examples/public/styles.css renamed to ‎examples/examples-browser/public/styles.css

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‎examples/server.js renamed to ‎examples/examples-browser/server.js

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@@ -10,10 +10,10 @@ app.use(express.urlencoded({ extended: true }))
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const viewsDir = path.join(__dirname, 'views')
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app.use(express.static(viewsDir))
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app.use(express.static(path.join(__dirname, './public')))
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app.use(express.static(path.join(__dirname, '../weights')))
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app.use(express.static(path.join(__dirname, '../weights_uncompressed')))
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app.use(express.static(path.join(__dirname, '../dist')))
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app.use(express.static(path.join(__dirname, './node_modules/axios/dist')))
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app.use(express.static(path.join(__dirname, '../images')))
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app.use(express.static(path.join(__dirname, '../media')))
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app.use(express.static(path.join(__dirname, '../../weights')))
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app.use(express.static(path.join(__dirname, '../../dist')))
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app.get('/', (req, res) => res.redirect('/face_and_landmark_detection'))
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app.get('/face_and_landmark_detection', (req, res) => res.sendFile(path.join(viewsDir, 'faceAndLandmarkDetection.html')))

‎examples/views/batchFaceLandmarks.html renamed to ‎examples/examples-browser/views/batchFaceLandmarks.html

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‎examples/views/batchFaceRecognition.html renamed to ‎examples/examples-browser/views/batchFaceRecognition.html

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‎examples/views/bbtFaceLandmarkDetection.html renamed to ‎examples/examples-browser/views/bbtFaceLandmarkDetection.html

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‎examples/views/bbtFaceMatching.html renamed to ‎examples/examples-browser/views/bbtFaceMatching.html

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‎examples/views/bbtFaceRecognition.html renamed to ‎examples/examples-browser/views/bbtFaceRecognition.html

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‎examples/views/bbtFaceSimilarity.html renamed to ‎examples/examples-browser/views/bbtFaceSimilarity.html

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‎examples/views/faceAndLandmarkDetection.html renamed to ‎examples/examples-browser/views/faceAndLandmarkDetection.html

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‎examples/views/faceExtraction.html renamed to ‎examples/examples-browser/views/faceExtraction.html

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‎examples/views/faceRecognition.html renamed to ‎examples/examples-browser/views/faceRecognition.html

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‎examples/views/videoFaceTracking.html renamed to ‎examples/examples-browser/views/videoFaceTracking.html

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<div class="indeterminate"></div>
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</div>
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<div style="position: relative" class="margin">
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<video src="media/bbt.mp4" id="inputVideo" autoplay muted loop></video>
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<video src="bbt.mp4" id="inputVideo" autoplay muted loop></video>
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<canvas id="overlay" />
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</div>
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‎examples/examples-nodejs/commons/env.ts

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// import nodejs bindings to native tensorflow,
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// not required, but will speed up things drastically (python required)
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import '@tensorflow/tfjs-node';
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// implements nodejs wrappers for HTMLCanvasElement, HTMLImageElement, ImageData
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import * as canvas from 'canvas';
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import * as faceapi from '../../../src';
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// patch nodejs environment, we need to provide an implementation of
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// HTMLCanvasElement and HTMLImageElement, additionally an implementation
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// of ImageData is required, in case you want to use the MTCNN
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const { Canvas, Image, ImageData } = canvas
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faceapi.env.monkeyPatch({ Canvas, Image, ImageData })
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export { canvas, faceapi }

‎examples/examples-nodejs/commons/faceDetection.ts

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import { NeuralNetwork } from 'tfjs-image-recognition-base';
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import { faceapi } from './env';
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export const faceDetectionNet = faceapi.nets.ssdMobilenetv1
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// export const faceDetectionNet = tinyFaceDetector
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// export const faceDetectionNet = mtcnn
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// SsdMobilenetv1Options
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const minConfidence = 0.5
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// TinyFaceDetectorOptions
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const inputSize = 408
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const scoreThreshold = 0.5
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// MtcnnOptions
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const minFaceSize = 50
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const scaleFactor = 0.8
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function getFaceDetectorOptions(net: NeuralNetwork<any>) {
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return net === faceapi.nets.ssdMobilenetv1
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? new faceapi.SsdMobilenetv1Options({ minConfidence })
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: (net === faceapi.nets.tinyFaceDetector
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? new faceapi.TinyFaceDetectorOptions({ inputSize, scoreThreshold })
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: new faceapi.MtcnnOptions({ minFaceSize, scaleFactor })
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)
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}
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export const faceDetectionOptions = getFaceDetectorOptions(faceDetectionNet)

‎examples/examples-nodejs/commons/index.ts

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export { canvas, faceapi } from './env';
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export { faceDetectionNet, faceDetectionOptions } from './faceDetection';
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export { saveFile } from './saveFile';

‎examples/examples-nodejs/commons/saveFile.ts

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import * as fs from 'fs';
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import * as path from 'path';
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const baseDir = path.resolve(__dirname, '../out')
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export function saveFile(fileName: string, buf: Buffer) {
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if (!fs.existsSync(baseDir)) {
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fs.mkdirSync(baseDir)
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}
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fs.writeFileSync(path.resolve(baseDir, fileName), buf)
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}

‎examples/examples-nodejs/faceDetection.ts

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import { canvas, faceapi, faceDetectionNet, faceDetectionOptions, saveFile } from './commons';
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async function run() {
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await faceDetectionNet.loadFromDisk('../../weights')
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const img = await canvas.loadImage('../images/bbt1.jpg')
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const detections = await faceapi.detectAllFaces(img, faceDetectionOptions)
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const out = faceapi.createCanvasFromMedia(img) as any
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faceapi.drawDetection(out, detections)
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saveFile('faceDetection.jpg', out.toBuffer('image/jpeg'))
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}
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run()

‎examples/examples-nodejs/faceLandmarkDetection.ts

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import { canvas, faceapi, faceDetectionNet, faceDetectionOptions, saveFile } from './commons';
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async function run() {
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await faceDetectionNet.loadFromDisk('../../weights')
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await faceapi.nets.faceLandmark68Net.loadFromDisk('../../weights')
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const img = await canvas.loadImage('../images/bbt1.jpg')
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const results = await faceapi.detectAllFaces(img, faceDetectionOptions)
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.withFaceLandmarks()
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const out = faceapi.createCanvasFromMedia(img) as any
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faceapi.drawDetection(out, results.map(res => res.detection))
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faceapi.drawLandmarks(out, results.map(res => res.faceLandmarks), { drawLines: true, color: 'red' })
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saveFile('faceLandmarkDetection.jpg', out.toBuffer('image/jpeg'))
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}
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run()

‎examples/examples-nodejs/faceRecognition.ts

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import { canvas, faceapi, faceDetectionNet, faceDetectionOptions, saveFile } from './commons';
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const REFERENCE_IMAGE = '../images/bbt1.jpg'
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const QUERY_IMAGE = '../images/bbt4.jpg'
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async function run() {
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await faceDetectionNet.loadFromDisk('../../weights')
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await faceapi.nets.faceLandmark68Net.loadFromDisk('../../weights')
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await faceapi.nets.faceRecognitionNet.loadFromDisk('../../weights')
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const referenceImage = await canvas.loadImage(REFERENCE_IMAGE)
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const queryImage = await canvas.loadImage(QUERY_IMAGE)
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const resultsRef = await faceapi.detectAllFaces(referenceImage, faceDetectionOptions)
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.withFaceLandmarks()
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.withFaceDescriptors()
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const resultsQuery = await faceapi.detectAllFaces(queryImage, faceDetectionOptions)
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.withFaceLandmarks()
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.withFaceDescriptors()
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const faceMatcher = new faceapi.FaceMatcher(resultsRef)
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const labels = faceMatcher.labeledDescriptors
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.map(ld => ld.label)
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const refBoxesWithText = resultsRef
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.map(res => res.detection.box)
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.map((box, i) => new faceapi.BoxWithText(box, labels[i]))
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const outRef = faceapi.createCanvasFromMedia(referenceImage) as any
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faceapi.drawDetection(outRef, refBoxesWithText)
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saveFile('referenceImage.jpg', outRef.toBuffer('image/jpeg'))
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const queryBoxesWithText = resultsQuery.map(res => {
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const bestMatch = faceMatcher.findBestMatch(res.descriptor)
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return new faceapi.BoxWithText(res.detection.box, bestMatch.toString())
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})
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const outQuery = faceapi.createCanvasFromMedia(queryImage) as any
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faceapi.drawDetection(outQuery, queryBoxesWithText)
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saveFile('queryImage.jpg', outQuery.toBuffer('image/jpeg'))
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}
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run()

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‎examples/public/images/bbt1.jpg

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