The Developer's Dilemma
If you search GitHub for "aadhaar masking," you'll find Python scripts, OpenCV-based solutions, and CLI tools. But are they the right choice? Let's compare.
GitHub / Code-Based Tools
How They Work
Most GitHub tools use OCR (Tesseract) or regex to detect the 12-digit number, then overlay a black rectangle on the image using OpenCV or Pillow.
Pros
- Full control over the masking logic
- Can be integrated into automated pipelines
- Open source — you can audit the code
Cons
- Requires Python/Node.js setup
- Dependencies (Tesseract, OpenCV) can be hard to install
- No GUI — not usable by non-developers
- Often unmaintained or poorly documented
- May not handle all Aadhaar formats (bilingual, old vs new layout)
No-Code Browser Tools
How They Work
Tools like CleverTools Aadhaar Masker run JavaScript in the browser to detect and mask the Aadhaar number. No installation needed.
Pros
- Zero setup — open and use
- Works on any device (phone, tablet, laptop)
- No technical knowledge required
- Client-side — as private as running code locally
- Handles multiple Aadhaar formats
Cons
- Can't be integrated into automated workflows
- Processing happens one document at a time
When to Use Which?
| Use Case | Best Option |
|---|---|
| One-off masking for KYC | No-code browser tool |
| Bulk processing 100+ documents | GitHub/code tool |
| Building into your app | GitHub library as dependency |
| Non-technical users (HR, admin) | No-code browser tool |
| Quick masking on mobile | No-code browser tool |