https://github.com/shantikumarigautam/idassure

IDAssure is a face-matching-based identity verification system that ensures secure and reliable user authentication. It’s built for seamless integration into platforms that require trust and visual identity validation.
https://github.com/shantikumarigautam/idassure

easyocr identity-verification opencv pdf-parser python reactjs streamlit

Last synced: about 1 month ago
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IDAssure is a face-matching-based identity verification system that ensures secure and reliable user authentication. It’s built for seamless integration into platforms that require trust and visual identity validation.

• Host: GitHub
• URL: https://github.com/shantikumarigautam/idassure
• Owner: ShantiKumariGautam
• Created: 2025-06-25T18:21:07.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-07-25T18:33:38.000Z (8 months ago)
• Last Synced: 2026-01-22T14:46:42.366Z (about 2 months ago)
• Topics: easyocr, identity-verification, opencv, pdf-parser, python, reactjs, streamlit
• Language: JavaScript
• Homepage: https://ida-ssure-by-team-pretty-pixels.vercel.app
• Size: 6.95 MB
• Stars: 2
• Watchers: 0
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# IDAssure: From Image to Face, We Trace with Grace

**IDAssure** is a smart identity verification system developed by **Team Pretty Pixels** at **Indira Gandhi Delhi Technical University for Women (IGDTUW)**. The platform verifies user identity and age using a combination of Aadhar document analysis and live facial recognition.

Deployed here: [https://ida-ssure-by-team-pretty-pixels.vercel.app](https://ida-ssure-by-team-pretty-pixels.vercel.app)

YouTube Tutorial: [https://youtu.be/0k3FhwTyRK4](https://youtu.be/0k3FhwTyRK4)

---



  



---

## Table of Contents

- [Project Overview](#project-overview)

- [Live Demo](#live-demo)

- [Features](#features)

- [How It Works](#how-it-works)

- [Tech Stack](#tech-stack)

- [Installation Guide](#installation-guide)

- [Future Scope](#future-scope)

- [About the Team](#about-the-team)

- [License](#license)

---

## Project Overview

IDAssure simplifies identity verification by allowing users to upload their Aadhar card (image or PDF) and capture a selfie. The system then performs facial recognition and OCR-based DOB extraction to confirm both identity and age. It is suitable for portals requiring KYC, digital onboarding, or age-restricted services.

---

## Features

- Face matching using MTCNN and FaceNet

- OCR-based DOB extraction from Aadhar using EasyOCR

- Age estimation based on DOB

- PDF and image upload support

- PAN card support added

- Modern React dashboard with sidebar navigation

- Streamlit-based AI backend with JSON API

---

## How It Works

1. **User Input**  

   - Upload Aadhar Card or PAN Card (Image or PDF)  

   - Capture live selfie using webcam  

2. **Face Detection and Comparison**  

   - Detects face in both inputs using MTCNN  

   - Extracts 512-d embeddings using InceptionResNetV1  

   - Compares faces using cosine similarity  

3. **DOB Extraction and Age Estimation**  

   - Uses EasyOCR to read text from document  

   - Applies regex to extract date formats  

   - Computes estimated age using datetime  

4. **Verification Logic**  

   - If Match > 75% and Age ≥ 18 → Identity Verified  

   - If Match > 75% but Age < 18 → Underage Warning  

   - If Match < 50% → Identity Rejected  

5. **Output**  

   - Face Match Percentage  

   - Extracted DOB  

   - Estimated Age  

   - Final Verdict (Verified / Underage / Rejected)  

---

## Tech Stack

### Backend (ML & OCR)

- Python  

- Streamlit  

- Facenet-Pytorch (MTCNN + InceptionResNetV1)  

- EasyOCR  

- PyMuPDF  

- NumPy, Pillow, OpenCV  

- Firebase  

### Frontend (UI)

- React.js  

- TailwindCSS  

- Webcam.js  

- React Router  

- Fetch API  

---

---

## Installation Guide

If you download the IDAssure ZIP file to your system, follow these steps:

1. Open terminal and navigate to the backend folder where `app.py` exists  

   Example:  

   `cd C:\Users\shant\Downloads\client\IDAssure\backend`

2. Run the backend:  

   `python app.py`

   You should see something like:  

   `PS C:\Users\shant\Downloads\client\IDAssure\backend> python app.py`

3. Open a new terminal tab and navigate to the frontend folder  

   Example:  

   `cd ..\frontend`

4. Start the frontend using:  

   `npm run dev`

5. Open the link provided in the terminal  

   Example:  

   `http://localhost:5173/`

6. The application will open in your browser.

7. Refer to the YouTube video for additional help.

---

## Future Scope

- Multilingual OCR  

- Smart document classification  

- Third-party API integration for SaaS use cases  

- Blockchain-based identity ledger  

---

## About the Team

This project was developed by **Team Pretty Pixels** from **IGDTUW**.

Team Members:

- Shanti Kumari  

- Sneha Kumari  

- Sadhya Gupta

---

## License

This project is licensed under the **Apache License 2.0**.