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justadudewhohacksjustadudewhohacks
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init server + train and test data split
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‎tools/train/faceExpressions/public/js/fetchData.js

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export function getImageUrl({ db, img }) {
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if (db === 'kaggle') {
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return `kaggle-face-expressions-db/${label}/${id}.png`
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}
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const dirNr = Math.floor(id / NUM_IMAGES_PER_DIR)
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return `cropped-faces/jpgs${dirNr + 1}/${id}.jpg`
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}

‎tools/train/faceExpressions/public/testData.json

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‎tools/train/faceExpressions/public/trainData.json

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‎tools/train/faceExpressions/server.js

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require('./.env')
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const express = require('express')
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const path = require('path')
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const fs = require('fs')
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const app = express()
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const publicDir = path.join(__dirname, './public')
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app.use(express.static(publicDir))
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app.use(express.static(path.join(__dirname, '../shared')))
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app.use(express.static(path.join(__dirname, '../node_modules/file-saver')))
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app.use(express.static(path.join(__dirname, '../../../examples/public')))
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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.use(express.static(path.resolve(process.env.DATA_PATH)))

‎tools/train/faceExpressions/splitDataSet.js

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const dataDistribution = {
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angry: {
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db: 1147,
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kaggle: 4953
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},
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disgusted: {
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db: 690,
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kaggle: 547
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},
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fearful: {
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db: 844,
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kaggle: 5121
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},
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happy: {
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db: 8634,
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kaggle: 8989
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},
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neutral: {
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db: 1262,
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kaggle: 6198
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},
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sad: {
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db: 929,
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kaggle: 6077
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},
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surprised: {
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db: 1264,
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kaggle: 4002
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}
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}
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const MAX_TRAIN_SAMPLES_PER_CLASS = 2000
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require('./.env')
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const { shuffleArray } = require('../../../')
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const fs = require('fs')
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const createImageNameArray = (db, num, ext) =>
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Array(num).fill(0)
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.map((_, i) => `${i}${ext}`)
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.map(img => ({ db, img }))
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const splitArray = (arr, idx) => [arr.slice(0, idx), arr.slice(idx)]
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const trainData = {}
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const testData = {}
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Object.keys(dataDistribution)
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.forEach(label => {
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const { db, kaggle } = dataDistribution[label]
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// take max 0.7 percent of db, take rest from kaggle db
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const numDb = Math.floor(Math.min(0.7 * MAX_TRAIN_SAMPLES_PER_CLASS, 0.7 * db))
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const numKaggle = Math.floor(Math.min(MAX_TRAIN_SAMPLES_PER_CLASS - numDb, 0.7 * kaggle))
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const dbImages = shuffleArray(createImageNameArray('db', db, '.jpg'))
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const kaggleImages = shuffleArray(createImageNameArray('kaggle', kaggle, '.png'))
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const [dbTrain, dbTest] = splitArray(dbImages, numDb)
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const [kaggleTrain, kaggleTest] = splitArray(kaggleImages, numKaggle)
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console.log()
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console.log('%s:', label)
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console.log('train data - db: %s, kaggle: %s', dbTrain.length, kaggleTrain.length)
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console.log('test data - db: %s, kaggle: %s', dbTest.length, kaggleTest.length)
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trainData[label] = dbTrain.concat(kaggleTrain)
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testData[label] = dbTest.concat(kaggleTest)
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})
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fs.writeFileSync('trainData.json', JSON.stringify(trainData))
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fs.writeFileSync('testData.json', JSON.stringify(testData))
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