Eazy-Park is an advanced parking management system designed to streamline the parking process and enhance the user experience. Leveraging the power of Object Detection (Masked R-CNN) image segmentation technique, it offers an intuitive platform for users to monitor and manage parking spaces with enhanced accuracy and efficiency.
The application is designed to automate the parking process and provide real-time parking space availability information to users. It utilizes sophisticated image processing techniques for accurate analysis and offers a user-friendly interface for seamless interaction.
- Automated Parking Management: Quick and automated detection of parking spaces and vehicle occupancy.
- Notification System: Provides a simple text-based notification system to alert users about parking space availability.
- Language: Python
- Machine Learning Model: Mask R-CNN
- Image Processing: OpenCV, NumPy
- Provide the path to the video file to be analyzed in the Hackathon (1).ipynb file.
- Run the notebook to initiate the analysis.
- View the cell output to see the parking space detection and vehicle occupancy results.
INITIAL STAGE:
FINAL STAGE:
This was a project made by the team coding_capitals3:
1. Vandit Gupta
2. Akshit Diwan
3. Karan Garg
for the hackathon : Micrsoft sponsored Skillenza Student Hackday 2019, New Delhi
Contributions are welcome! Please feel free to submit a Pull Request. Please read the CONTRIBUTING.md file for more details.
This project is licensed under the MIT License. Please read the LICENSE.md file for more details.
For any inquiries or contributions, please contact me at gupta.vandi@northeastern.edu
Development for this project has completed. There are no plans for future updates or releases.