--- comments: true description: Optimize parking spaces and enhance safety with Ultralytics YOLOv8. Explore real-time vehicle detection and smart parking solutions. keywords: parking management, YOLOv8, Ultralytics, vehicle detection, real-time tracking, parking lot optimization, smart parking --- # Parking Management using Ultralytics YOLOv8 🚀 ## What is Parking Management System? Parking management with [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) ensures efficient and safe parking by organizing spaces and monitoring availability. YOLOv8 can improve parking lot management through real-time vehicle detection, and insights into parking occupancy.



Watch: How to Implement Parking Management Using Ultralytics YOLOv8 🚀

## Advantages of Parking Management System? - **Efficiency**: Parking lot management optimizes the use of parking spaces and reduces congestion. - **Safety and Security**: Parking management using YOLOv8 improves the safety of both people and vehicles through surveillance and security measures. - **Reduced Emissions**: Parking management using YOLOv8 manages traffic flow to minimize idle time and emissions in parking lots. ## Real World Applications | Parking Management System | Parking Management System | | :----------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | ![Parking lots Analytics Using Ultralytics YOLOv8](https://github.com/ultralytics/docs/releases/download/0/parking-management-aerial-view-ultralytics-yolov8.avif) | ![Parking management top view using Ultralytics YOLOv8](https://github.com/ultralytics/docs/releases/download/0/parking-management-top-view-ultralytics-yolov8.avif) | | Parking management Aerial View using Ultralytics YOLOv8 | Parking management Top View using Ultralytics YOLOv8 | ## Parking Management System Code Workflow ### Selection of Points !!! Tip "Point Selection is now Easy" 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. !!! Warning "Image Size" Max Image Size of 1920 * 1080 supported !!! Example "Parking slots Annotator Ultralytics YOLOv8" === "Parking Annotator" ```python from ultralytics import solutions solutions.ParkingPtsSelection() ``` - After defining the parking areas with polygons, click `save` to store a JSON file with the data in your working directory. ![Ultralytics YOLOv8 Points Selection Demo](https://github.com/ultralytics/docs/releases/download/0/ultralytics-yolov8-points-selection-demo.avif) ### Python Code for Parking Management !!! Example "Parking management using YOLOv8 Example" === "Parking Management" ```python import cv2 from ultralytics import solutions # Path to json file, that created with above point selection app polygon_json_path = "bounding_boxes.json" # Video capture cap = cv2.VideoCapture("Path/to/video/file.mp4") assert cap.isOpened(), "Error reading video file" w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS)) # Video writer video_writer = cv2.VideoWriter("parking management.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) # Initialize parking management object management = solutions.ParkingManagement(model_path="yolov8n.pt") while cap.isOpened(): ret, im0 = cap.read() if not ret: break json_data = management.parking_regions_extraction(polygon_json_path) results = management.model.track(im0, persist=True, show=False) if results[0].boxes.id is not None: boxes = results[0].boxes.xyxy.cpu().tolist() clss = results[0].boxes.cls.cpu().tolist() management.process_data(json_data, im0, boxes, clss) management.display_frames(im0) video_writer.write(im0) cap.release() video_writer.release() cv2.destroyAllWindows() ``` ### Optional Arguments `ParkingManagement` | Name | Type | Default | Description | | ------------------------ | ------- | ----------------- | -------------------------------------- | | `model_path` | `str` | `None` | Path to the YOLOv8 model. | | `txt_color` | `tuple` | `(0, 0, 0)` | RGB color tuple for text. | | `bg_color` | `tuple` | `(255, 255, 255)` | RGB color tuple for background. | | `occupied_region_color` | `tuple` | `(0, 255, 0)` | RGB color tuple for occupied regions. | | `available_region_color` | `tuple` | `(0, 0, 255)` | RGB color tuple for available regions. | | `margin` | `int` | `10` | Margin for text display. | ### Arguments `model.track` | Name | Type | Default | Description | | --------- | ------- | -------------- | ----------------------------------------------------------- | | `source` | `im0` | `None` | source directory for images or videos | | `persist` | `bool` | `False` | persisting tracks between frames | | `tracker` | `str` | `botsort.yaml` | Tracking method 'bytetrack' or 'botsort' | | `conf` | `float` | `0.3` | Confidence Threshold | | `iou` | `float` | `0.5` | IOU Threshold | | `classes` | `list` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] | | `verbose` | `bool` | `True` | Display the object tracking results | ## FAQ ### How does Ultralytics YOLOv8 enhance parking management systems? Ultralytics YOLOv8 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). ### What are the benefits of using Ultralytics YOLOv8 for smart parking? Using Ultralytics YOLOv8 for smart parking yields numerous benefits: - **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). ### How can I define parking spaces using Ultralytics YOLOv8? Defining parking spaces is straightforward with Ultralytics YOLOv8: 1. Capture a frame from a video or camera stream. 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. ### Can I customize the YOLOv8 model for specific parking management needs? Yes, Ultralytics YOLOv8 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. ### What are some real-world applications of Ultralytics YOLOv8 in parking lot management? Ultralytics YOLOv8 is utilized in various real-world applications for parking lot management, including: - **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).