pdf-corruption-lab / gen_training.js
islam ayoub
Add gen_training.js (training-set generator)
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#!/usr/bin/env node
/**
* Generates a labelled training set of randomized valid/damaged PDFs
* for the pdf-damage-classifier model.
*
* Usage: node gen_training.js [outputDir] [variantsPerClass]
* Output: <outputDir>/*.pdf and <outputDir>/labels.csv (file,label)
*/
const fs = require('fs');
const path = require('path');
const { PDFDocument, rgb, StandardFonts } = require('pdf-lib');
const { scenarios, toLatin1, fromLatin1 } = require('./generate');
const IMG = 'iVBORw0KGgoAAAANSUhEUgAAAAIAAAACCAYAAABytg0kAAAAFElEQVQIW2NkwAJGDjACU2M4wAgAJu4BCHgB5hQAAAAASUVORK5CYII=';
// Small seeded PRNG so the dataset is reproducible.
function rng(seed) {
let s = seed >>> 0;
return () => {
s = (s + 0x6d2b79f5) >>> 0;
let t = s;
t = Math.imul(t ^ (t >>> 15), t | 1);
t ^= t + Math.imul(t ^ (t >>> 7), t | 61);
return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
};
}
const WORDS = 'alpha beta gamma delta report invoice summary table chart data page section total value note draft final review'.split(' ');
async function randomPdf(r) {
const doc = await PDFDocument.create();
const font = await doc.embedFont(r() < 0.5 ? StandardFonts.Helvetica : StandardFonts.TimesRoman);
const pages = 1 + Math.floor(r() * 8);
const png = r() < 0.6 ? await doc.embedPng(Buffer.from(IMG, 'base64')) : null;
for (let p = 0; p < pages; p++) {
const page = doc.addPage([r() < 0.8 ? 595 : 612, r() < 0.8 ? 842 : 792]);
const lines = 1 + Math.floor(r() * 40);
for (let i = 0; i < lines; i++) {
const n = 3 + Math.floor(r() * 12);
const text = Array.from({ length: n }, () => WORDS[Math.floor(r() * WORDS.length)]).join(' ');
page.drawText(text, { x: 40, y: 800 - i * 14, size: 8 + Math.floor(r() * 5), font, color: rgb(r(), r(), r()) });
}
if (png && r() < 0.5) page.drawImage(png, { x: 60, y: 100, width: 40 + r() * 100, height: 40 + r() * 100 });
}
return doc.save({ useObjectStreams: false });
}
async function main() {
const outDir = path.resolve(process.argv[2] || path.join(__dirname, 'training'));
const perClass = parseInt(process.argv[3] || '200', 10);
fs.mkdirSync(outDir, { recursive: true });
const r = rng(42);
const rows = ['file,label'];
const classes = ['valid', ...scenarios.filter((s) => !s.id.startsWith('truncated')).map((s) => s.id), 'truncated'];
for (const label of classes) {
for (let i = 0; i < perClass; i++) {
const base = await randomPdf(r);
const text = toLatin1(base);
let out;
if (label === 'valid') out = base;
else if (label === 'truncated') out = base.slice(0, Math.floor(base.length * (0.3 + r() * 0.6)));
else out = scenarios.find((s) => s.id === label).apply(base, text);
const name = `${label}_${String(i).padStart(4, '0')}.pdf`;
fs.writeFileSync(path.join(outDir, name), out);
rows.push(`${name},${label}`);
}
console.log(`${label}: ${perClass}`);
}
fs.writeFileSync(path.join(outDir, 'labels.csv'), rows.join('\n') + '\n');
console.log(`labels.csv written to ${outDir}`);
}
main().catch((e) => {
console.error(e);
process.exit(1);
});