Automatic License Plate Recognition System Final Year Project with Source Code

• Upload vehicle image through browser in this final year project
• Drag-and-drop image upload
• Click-to-browse image upload
• Live image preview
• Recognize vehicle license plate
• View detected plate number
• View OCR confidence score
• View plate detection confidence score
• View region/country code
• View region confidence
• View vehicle type when returned
• View vehicle colour when returned
• View vehicle orientation when returned
• View make/model when returned
• View multiple plate candidates
• View bounding-box overlay on image
• Copy plate number to clipboard
• Use optional region hints
• View success, warning, and error flash messages
• Use responsive desktop/mobile interface
• Access “How it works” section
• Access feature overview section

Recognition Features in this Final Year Project

• License plate text extraction
• ALPR / ANPR recognition workflow
• Vehicle image upload processing
• Plate confidence score display
• Detection score display
• Country/region detection
• Vehicle metadata extraction when available
• Multiple candidate readings
• Optional region hint support
• Bounding-box coordinates parsing
• Canvas-based visual plate overlay
• Structured API response parsing
• Legacy and current API response normalization

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Supported Region Hints in this Final Year Project

The interface supports region filters such as:

• United States — us
• US California — us-ca
• India — in
• United Kingdom — gb
• Germany — de
• Brazil — br
• Australia — au
• Canada — ca

Region hints help improve recognition accuracy by narrowing plate pattern matching.

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Backend Features in this Final Year Project

• Flask application entry point
• Server-side file validation
• File type validation
• File size validation
• Empty file validation
• 10 MB maximum upload limit
• Environment-variable-based API key configuration
• Plate Recognizer Snapshot API integration
• Requests-based HTTP client
• API response parsing
• Network failure handling
• Invalid API key handling
• Rate-limit handling
• No-plate-detected handling
• Flash message support
• Flask secret key configuration
• Development and production deployment support

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Frontend Features in this Final Year Project

• Modern dark-theme interface
• Responsive layout
• HTML5 templates
• CSS styling
• Vanilla JavaScript interactions
• Drag-drop upload support
• Image preview
• Canvas overlay for detected plates
• Clipboard copy logic
• Loading state during API processing
• User-friendly result cards
• Confidence bar display
• Feature overview UI
• Error/warning display

• Complete Automatic License Plate Recognition source code
• Suitable for final year project, major project, and minor project
• Project report content can be prepared from included modules
• Flask web application
• Plate OCR workflow
• Vehicle image upload
• ALPR / ANPR functionality
• Region-based recognition hints
• Bounding-box overlay
• Confidence score display
• Vehicle metadata display
• Copy plate number button
• API error handling
• Responsive dark-theme UI
• HTML Canvas overlay
• Environment-based configuration
• Production deployment guidance
• Useful for viva, source code review, project report writing, and project demonstration

• Open terminal in project folder:

  cd deep-license-plate-recognition

• Create virtual environment on Windows:

  python -m venv venv
  venv\Scripts\activate

• Create virtual environment on macOS/Linux:

  python3 -m venv venv
  source venv/bin/activate

• Install dependencies:

  pip install -r requirements-web.txt

• Set environment variables on Windows PowerShell:

  $env:PLATE_RECOGNIZER_API_KEY = "your-api-key-here"
  $env:FLASK_SECRET_KEY = "your-long-random-secret"
  python app.py

• Set environment variables on macOS/Linux:

  export PLATE_RECOGNIZER_API_KEY="your-api-key-here"
  export FLASK_SECRET_KEY="your-long-random-secret"
  python app.py

• Open project in browser:

  http://127.0.0.1:5000

• Upload vehicle image and click:

  Recognize plates

This project has no login credentials because it does not include user login, registration, admin panel, or authentication module.

Account Type	Username	Password
Administrator	Not required	Not required
User	Not required	Not required

Important access note:
The system requires a valid Plate Recognizer API key for recognition service access.

Copyright Notice Original Software: Copyright (c) 2018 Marc Belmont Licensed under the MIT License. Modifications, documentation, testing, configuration, packaging and additional components: Copyright (c) 2026 FileMakr.com The original copyright notice and MIT License remain applicable to the original software. FileMakr.com claims copyright only over its independently created modifications, documentation and additional materials. Recommended Website Disclosure This product contains open-source software originally developed by Marc Belmont and released under the MIT License. The original copyright notice and complete MIT License are included in the downloadable source-code package. FileMakr.com does not claim ownership of the original open-source software. The amount charged covers services and additional value provided by FileMakr.com, including project verification, testing, organization, documentation, packaging, configuration guidance, delivery and technical support. Customers receive the software subject to the terms of the MIT License. Third-party libraries, APIs, images, datasets, fonts and other external resources may be governed by their respective licences and terms of use.