I built a privacy-first PDF dark mode converter that runs entirely in your browser

Source: Dev.to

TL;DR

I shipped pdfdark.org – a browser‑side PDF dark‑mode converter. Files never leave your browser; the entire conversion happens client‑side using PDF.js, a Web Worker, and pdf‑lib. It’s open source (MIT), free, and requires no signup.

Why I Built It

Reading long PDFs at night was straining my eyes. The existing solutions had major drawbacks:

• Web‑based dark‑mode tools – required uploading the file, which felt unsafe for research papers, contracts, or medical records.
• OS‑level “invert colors” – ruined photos and charts, turning faces into X‑rays and graphs into noise.

Core Principles

1. Zero data leaving the browser – PDF.js parses the file, a Web Worker applies the dark‑mode pass, and pdf‑lib stitches the result. You can verify the process in DevTools → Network.
2. Preserve image colors – a saturation classifier detects photos and figures and leaves them untouched while darkening text and UI elements.

How It Works

Drop PDF
   ↓
PDF.js renders pages to canvas
   ↓
Web Worker classifies each pixel by saturation
   ├─ Saturated pixels (images, charts) → preserved
   └─ Low‑saturation pixels (text, UI) → themed
   ↓
pdf‑lib assembles a new PDF
   ↓
User downloads the result

• The classifier runs on an OffscreenCanvas inside a Web Worker, keeping the UI thread responsive even for large PDFs.
• The output is a real PDF (image‑based, one JPEG per page), so the dark mode persists when you email, sync to an iPad, or open it on a Kindle. It’s not just a viewer toggle.

Costs

Development took a few weekends.

Open Questions

• Does the “no‑upload” angle resonate beyond privacy enthusiasts?
• How to handle edge cases that break the algorithm (e.g., weird embedded fonts, scanned PDFs).
• Whether to add a vector‑preserving mode for text‑only PDFs (the current output is image‑based, so text isn’t selectable).

Links

• Live site:
• GitHub repository:
• Privacy policy: