Prototype EvaluationDevOps Briefing

Aadhaar Masking Solution Overview

A working Python-based utility for automated Aadhaar detection and masking — deployable today as a baseline, with a clear path to production-grade accuracy.

Aadhaar Masking

What the Utility Does Today

The current implementation combines PaddleOCR and YOLO to deliver an end-to-end masking pipeline on Linux.

Region Detection

YOLO-based detection of Aadhaar-related regions within scanned documents and images.

OCR Extraction

PaddleOCR reads and extracts Aadhaar number text from identified regions.

Automated Masking

Masking logic is applied on extracted PII, redacting Aadhaar identifiers in the output.

Batch Execution

Folder-based, batch-mode processing via Linux cron scheduler — no manual intervention needed.

Current Accuracy

Performance Baseline

Current Accuracy:

60–70%

Accuracy is functional but variable — influenced by several real-world document factors.

Scan & Image Quality

Low-resolution scans, poor lighting, or compression artefacts reduce OCR confidence significantly.

Card Placement & Background

Skewed, rotated, or busy-background documents affect YOLO detection reliability.

Document Format Variation

Different Aadhaar layouts, generations, and laminated copies introduce variance in pipeline output.

Deployment Readiness

How to Position This Utility

Position As
  • Working prototype ready for internal use
  • Proof-of-concept / controlled pilot
  • Accelerator foundation for further enhancement
  • Baseline Aadhaar masking for known document formats
Do Not Position As
  • Fully production-grade deployment
  • High-accuracy enterprise PII solution
  • A replacement for validated, annotated model pipelines
  • Guaranteed masking across all real-world document types

Important: Current accuracy of 60–70% must be disclosed upfront before any deployment commitment.

Baseline Deployment:

Ready Within 1 Week

The existing utility can be stood up rapidly in a Linux environment for pilot or PoC use.

01

Dependency Installation

Install packages and configure services.

02

Environment Setup

Provision Linux VM and network.

03

Scheduler & Path Setup

Configure scheduler and data paths.

04

Testing & Validation

Run pilot tests and verify results.

Ready to pilot Aadhaar masking in your environment?

Deploy the baseline utility within a week — and build toward production-grade accuracy on your own data.

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