QUICKSTART.md

🚀 Quick Start Guide

Get the Certificate Verification System running in 5 minutes!

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⚡ Fastest Way to Run

Option 1: Demo Mode (No Setup Required)

# Clone repository
git clone https://github.com/YourUsername/certificate-verifier.git
cd certificate-verifier

# Install dependencies
pip install -r requirements.txt

# Run app
streamlit run main.py

That's it! App runs in demo mode - no API keys needed.

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🔧 Full Setup (With OCR API)

1. Install Dependencies

pip install -r requirements.txt

2. Get Free OCR API Key

1. Visit: https://ocr.space/ocrapi
2. Sign up (free)
3. Copy your API key

3. Configure Environment

Create .env file:

OCRSPACE_API_KEY=your_api_key_here

4. Initialize Database (Optional)

python init_db.py

5. Run Application

streamlit run main.py

6. Open Browser

http://localhost:8501

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📱 Usage

Basic Workflow:

1. Upload certificate image (JPG/PNG)
2. Click "Verify Certificate"
3. View results with confidence scores
4. Download verification report (JSON)

Demo Mode Testing:

1. Enable "Demo Mode" in sidebar
2. Upload any certificate image
3. System uses sample OCR data
4. See how verification works!

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🎯 What Happens on First Run?

Automatic Downloads:

1. YOLOv8 Model (~6 MB)

   • Downloads from Hugging Face
   • Takes ~10 seconds
   • Cached for future runs

2. ViT Model (~1 GB) (Only if seal verification enabled)

   • Downloads from Hugging Face
   • Takes ~5 minutes (depending on bandwidth)
   • Cached for future runs

After first run: Everything loads instantly from cache!

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✅ Verification Steps

The system performs 3-layer verification:

Layer 1: OCR Text Verification

• Extracts text from certificate
• Finds registration number
• Matches against database
• Calculates confidence score

Layer 2: YOLOv8 Seal Detection

• Detects seals/stamps in image
• 99% detection accuracy
• Returns bounding boxes

Layer 3: ViT Seal Classification

• Classifies each seal as Real/Fake
• Uses Vision Transformer AI
• Provides confidence scores

Final Decision:

• Combines all layers
• Security-first logic
• High-confidence fake → Rejection

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🔍 Test Certificates

The database includes sample certificates you can test:

Sample Registration Numbers:

• ABC2023001 - Saksham Sharma, DevLabs Institute
• ABC2022007 - Prisha Verma, Global Tech University
• 1BG19CS100 - Vikram Verma, VTU (from demo mode)

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🎮 Features to Try

In Sidebar:

✅ Demo Mode - Test without API keys ✅ Seal Verification - Enable AI seal detection ✅ OCR Language - Select certificate language ✅ System Status - Check all components

After Verification:

✅ Detailed Results - Step-by-step breakdown ✅ Confidence Scores - For each verification layer ✅ Download Report - JSON export ✅ Detected Seals - View cropped seal images

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🚨 Troubleshooting

Issue: ModuleNotFoundError

pip install -r requirements.txt

Issue: OCR API Error

• Enable "Demo Mode" in sidebar, or
• Check API key in .env file

Issue: Models not downloading

• Check internet connection
• Models download automatically on first run
• Look for download progress in terminal

Issue: Database error

python init_db.py

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📚 Next Steps

Deploy to Cloud:

See DEPLOYMENT.md for Streamlit Cloud deployment

Customize:

• Edit certs.db to add your certificates
• Modify verification thresholds in verifier.py
• Add custom regex patterns for registration numbers

Integrate:

• Use as Python library
• Build REST API wrapper
• Integrate with existing systems

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🤝 Need Help?

• Documentation: README.md
• Deployment: DEPLOYMENT.md
• Issues: Open on GitHub
• Questions: Contact maintainer

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🎉 You're Ready!

Start verifying certificates with AI-powered accuracy!

streamlit run main.py

Happy verifying! 🎓✨