Parking management with [Ultralytics YOLO11](https://github.com/ultralytics/ultralytics/) ensures efficient and safe parking by organizing spaces and monitoring availability. YOLO11 can improve parking lot management through real-time vehicle detection, and insights into parking occupancy.
Choosing parking points is a critical and complex task in parking management systems. Ultralytics streamlines this process by providing a tool that lets you define parking lot areas, which can be utilized later for additional processing.
- Capture a frame from the video or camera stream where you want to manage the parking lot.
- Use the provided code to launch a graphical interface, where you can select an image and start outlining parking regions by mouse click to create polygons.
Ultralytics YOLO11 greatly enhances parking management systems by providing **real-time vehicle detection** and monitoring. This results in optimized usage of parking spaces, reduced congestion, and improved safety through continuous surveillance. The [Parking Management System](https://github.com/ultralytics/ultralytics) enables efficient traffic flow, minimizing idle times and emissions in parking lots, thereby contributing to environmental sustainability. For further details, refer to the [parking management code workflow](#python-code-for-parking-management).
- **Efficiency**: Optimizes the use of parking spaces and decreases congestion.
- **Safety and Security**: Enhances surveillance and ensures the safety of vehicles and pedestrians.
- **Environmental Impact**: Helps in reducing emissions by minimizing vehicle idle times. More details on the advantages can be seen [here](#advantages-of-parking-management-system).
2. Use the provided code to launch a GUI for selecting an image and drawing polygons to define parking spaces.
3. Save the labeled data in JSON format for further processing. For comprehensive instructions, check the [selection of points](#selection-of-points) section.
Yes, Ultralytics YOLO11 allows customization for specific parking management needs. You can adjust parameters such as the **occupied and available region colors**, margins for text display, and much more. Utilizing the `ParkingManagement` class's [optional arguments](#optional-arguments-parkingmanagement), you can tailor the model to suit your particular requirements, ensuring maximum efficiency and effectiveness.
- **Parking Space Detection**: Accurately identifying available and occupied spaces.
- **Surveillance**: Enhancing security through real-time monitoring.
- **Traffic Flow Management**: Reducing idle times and congestion with efficient traffic handling. Images showcasing these applications can be found in [real-world applications](#real-world-applications).