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comments	description	keywords
true	Optimize parking spaces and enhance safety with Ultralytics YOLOv8. Explore real-time vehicle detection and smart parking solutions.	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 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 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.

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 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.

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.

How can I define parking spaces using Ultralytics YOLOv8?

Defining parking spaces is straightforward with Ultralytics YOLOv8:

Capture a frame from a video or camera stream.
Use the provided code to launch a GUI for selecting an image and drawing polygons to define parking spaces.
Save the labeled data in JSON format for further processing. For comprehensive instructions, check the 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, 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.

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