NoteMercy Extension is a sophisticated handwriting analysis and recognition system that can identify and analyze various styles of handwriting. The system provides detailed analysis of different handwriting characteristics including print, cursive, italic, calligraphic, shorthand, and block writing styles.

• Multiple Handwriting Style Analysis

  • Print Writing
  • Cursive Writing
  • Italic Writing
  • Calligraphic Writing
  • Shorthand Writing
  • Block Writing

• Advanced Analysis Components

  • Angularity Analysis
  • Aspect Ratio Analysis
  • Loop Detection
  • Stroke Width Variation
  • Curvature Analysis
  • Letter Spacing Analysis
  • And more specialized analyzers for each writing style

NoteMercy_Extension/
├── frontend/           # Next.js frontend application
├── backend/           # Python FastAPI backend
│   ├── atest/        # Test datasets
│   ├── lib_py/       # Analysis libraries
│   └── api.py        # Main API server
└── README.md

• Node.js 16.x or later
• Python 3.8 or later
• npm or yarn package manager

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install
   # or
   yarn install

3. Run the development server:

   npm run dev
   # or
   yarn dev

The frontend will be available at http://localhost:3000

1. Navigate to the backend directory:

   cd backend

2. Create and activate a virtual environment:

   python -m venv venv
   
   # Activate the virtual environment
   # On macOS/Linux:
   source venv/bin/activate
   # On Windows:
   .\venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run the backend server:

   python api.py

The project includes sample test images in the /backend/atest folder demonstrating various handwriting styles:

• Print Writing: print.jpg, print2.png
• Cursive Writing: cursive2.png, cursive3.jpg, cursive4.png
• Italic Writing: italic.jpg, italic2.png, italic3.png, italic4.png, italic5.png
• Calligraphic Writing: calligraphic.png, calligraphic2.png
• Shorthand Writing: shorthand1.png through shorthand5.png
• Block Writing: block1.png, block2.png, block3.png

These images serve as test cases for the handwriting recognition system and demonstrate the system's capability to handle various writing styles.

• Both frontend and backend servers must be running for the application to function properly
• The backend API is built with FastAPI and includes CORS support for frontend communication
• The frontend is built with Next.js and uses modern web technologies including Tailwind CSS
• The system implements various analyzers for different aspects of handwriting analysis

Feel free to submit issues and enhancement requests!