El face-api.js predeterminado usa solo una imagen como referencia para el reconocimiento facial, pero a través de mis pruebas noté una brecha de error bastante alta. Entonces, me preguntaba, ¿cómo puedo lograr aumentar la cantidad de imágenes de referencia para reducir la brecha de error?
Asumiendo que mis imágenes están en la carpeta imgs/ , ¿cómo puedo hacer esto?
Aquí está la carpeta de mi proyecto:
Aquí está el archivo faceRecognition.ts:
import * as faceapi from 'face-api.js'; import { canvas, faceDetectionNet, faceDetectionOptions, saveFile } from './commons'; const REFERENCE_IMAGE = '../../imgs/test1.jpeg' const QUERY_IMAGE = '../../test/test.jpeg' // i want to have many images for the REFERENCE_IMAGE // in folder imgs, i have 5 images in a want to use all five images for increase // the result. Actually i have some bad prediction when i use only one image async function run() { await faceDetectionNet.loadFromDisk('../../weights') await faceapi.nets.faceLandmark68Net.loadFromDisk('../../weights') await faceapi.nets.faceRecognitionNet.loadFromDisk('../../weights') const referenceImage = await canvas.loadImage(REFERENCE_IMAGE) const queryImage = await canvas.loadImage(QUERY_IMAGE) const resultsRef = await faceapi.detectAllFaces(referenceImage, faceDetectionOptions) .withFaceLandmarks() .withFaceDescriptors() const resultsQuery = await faceapi.detectAllFaces(queryImage, faceDetectionOptions) .withFaceLandmarks() .withFaceDescriptors() const faceMatcher = new faceapi.FaceMatcher(resultsRef) const labels = faceMatcher.labeledDescriptors .map(ld => ld.label) const refDrawBoxes = resultsRef .map(res => res.detection.box) .map((box, i) => new faceapi.draw.DrawBox(box, { label: labels[i] })) const outRef = faceapi.createCanvasFromMedia(referenceImage) refDrawBoxes.forEach(drawBox => drawBox.draw(outRef)) saveFile('referenceImage.jpg', (outRef as any).toBuffer('image/jpeg')) const queryDrawBoxes = resultsQuery.map(res => { const bestMatch = faceMatcher.findBestMatch(res.descriptor) return new faceapi.draw.DrawBox(res.detection.box, { label: bestMatch.toString() }) }) const outQuery = faceapi.createCanvasFromMedia(queryImage) queryDrawBoxes.forEach(drawBox => drawBox.draw(outQuery)) saveFile('queryImage.jpg', (outQuery as any).toBuffer('image/jpeg')) } run()Alguien puede ayudar ?
const path = require('path') import * as faceapi from 'face-api.js'; import { canvas, faceDetectionNet, faceDetectionOptions, saveFile } from './commons'; async function start() { await faceDetectionNet.loadFromDisk('../../weights') await faceapi.nets.faceLandmark68Net.loadFromDisk('../../weights') await faceapi.nets.faceRecognitionNet.loadFromDisk('../../weights') const labeledFaceDescriptors = await loadLabeledImages() const faceMatcher = new faceapi.FaceMatcher(labeledFaceDescriptors, 0.6) const queryImage = await canvas.loadImage(`test/test.jpeg`) //absolute link to image const detections = await faceapi.detectAllFaces(queryImage ).withFaceLandmarks().withFaceDescriptors() const queryDrawBoxes = detections.map(res => { const bestMatch = faceMatcher.findBestMatch(res.descriptor) return new faceapi.draw.DrawBox(res.detection.box, { label: bestMatch.toString() }) }) const outQuery = faceapi.createCanvasFromMedia(queryImage) queryDrawBoxes.forEach(drawBox => drawBox.draw(outQuery)) saveFile('queryImage.jpg', (outQuery as any).toBuffer('image/jpeg')) console.log('done, saved results to out/queryImage.jpg') } function loadLabeledImages() { const labels = ['imgs'] return Promise.all( labels.map(async label => { const descriptions = [] for (let i = 1; i <= 5; i++) { const img = await canvas.loadImage(`/imgs/test${i}.jpeg` ) // for example if you are test1 , test2, etc. like image's names const detections = await faceapi.detectSingleFace(img).withFaceLandmarks().withFaceDescriptor() descriptions.push(detections.descriptor) } return new faceapi.LabeledFaceDescriptors(label, descriptions) }) ) } start()