https://github.com/yasinefeee/parkspotter
This project uses AI-powered vehicle detection to enable customizable and efficient parking space management.
https://github.com/yasinefeee/parkspotter
ai-systems artificial-intelligence cv2 firebase firebase-database image-processing image-recognition parking-management parking-slot-detection parking-spot-detection parking-spots pyqt5 python
Last synced: 3 months ago
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This project uses AI-powered vehicle detection to enable customizable and efficient parking space management.
- Host: GitHub
- URL: https://github.com/yasinefeee/parkspotter
- Owner: YasinEfeee
- Created: 2024-12-02T19:49:39.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-18T07:47:36.000Z (over 1 year ago)
- Last Synced: 2025-05-28T07:45:52.839Z (about 1 year ago)
- Topics: ai-systems, artificial-intelligence, cv2, firebase, firebase-database, image-processing, image-recognition, parking-management, parking-slot-detection, parking-spot-detection, parking-spots, pyqt5, python
- Language: Python
- Homepage:
- Size: 54.6 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# ParkSpotter
This project aims to make the parking search process faster, more efficient, and accessible with an AI-supported system.
The system stands out with real-time monitoring in marketplaces, shopping malls, and private parking lots, providing priority access for individuals with disabilities, anomaly detection, and a low-cost technology infrastructure.
Developed using Python and the YOLOv8 model, the project contributes to environmental sustainability goals while optimizing traffic flow.
## Firebase Integration Warning !!
This project uses Firebase as its database to efficiently store and manage parking data.
Make sure to configure your Firebase account and provide the `serviceAccountKey.json` file for seamless integration.
## Project Purpose
As urbanization increases, finding available parking spaces has become a significant challenge, leading to time loss, financial costs, and environmental concerns. The ParkSpotter system was developed to:
- **Optimize the parking search process**, making it faster and more efficient.
- **Improve accessibility for disabled individuals**, ensuring designated spots are used correctly.
- **Provide a cost-effective and scalable AI-based solution** for municipalities and private parking lots.
- **Detect parking anomalies**, such as unauthorized usage of reserved spots.
## Features
- **Image Analysis:** Parking lot occupancy analysis through camera images, videos, or photos.
- **Parking Spot Selection:** Select parking areas via videos, live cameras, or photos.
- **Real-Time Detection:** Analyze live camera streams and video recordings.
- **Disability-Friendly Design:** Dedicated parking spot selection, tracking, and alert systems for individuals with disabilities.
- **Firebase Integration:** Storing analysis results in the cloud using a database connection.
- **User-Friendly Interface:** Easy-to-use PyQt5-based graphical user interface.
- **Monitoring:** Efficient parking lot management and anomaly detection.
- **Parking Lot Redesign:** Empowers users to redesign their parking lots, with all changes automatically saved to Firebase.
## Technologies Used
- **Programming Language:** Python
- **Machine Learning Model:** Ultralytics YOLOv8
- **GUI Development:** PyQt5
- **Image Processing:** OpenCV
- **Database:** Firebase
- **IDE:** PyCharm
## Usage
1. **Upload Visuals:** Start analysis by uploading camera images or photos.
2. **Parking Spot Selection:** Select parking areas via videos, live cameras, or photos.
3. **Real-Time Analysis:** Monitor parking lot occupancy using live camera streams.
4. **Analysis Results:** View results both visually and in the Firebase database.
5. **Disabled Parking Spots:** Select and monitor parking spots designated for individuals with disabilities.
6. **Save to database** Storge analysis results in the cloud using a database connection.
## Application Main Window
## Application Analysis Example
## Parking Spot Selecting
## Future Improvements
- Enhance user experience and improve system accuracy.
- Improve **real-time performance** of the AI model.
- Optimize **database operations** for faster response times.
- Expand to a **mobile app** version for user-friendly interaction.
## Contribute and Support
We are open to your suggestions and ideas to make the ParkSpotter project even better. You can contribute to the project in the following ways:
- **Report Issues and Suggestions:** If you encounter any problems or have improvement ideas, please open an "issue." Every piece of feedback is invaluable to us!
- **Spread the Word:** Share the project with your friends and anyone who might be interested, helping us reach a broader audience.
### Contact
Feel free to reach out to us for more information or to share your contributions. Thank you in advance for your support!