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---
comments: true
description: Optimize parking spaces and enhance safety with Ultralytics YOLO11. Explore real-time vehicle detection and smart parking solutions.
keywords: parking management, YOLO11, Ultralytics, vehicle detection, real-time tracking, parking lot optimization, smart parking
---
# Parking Management using Ultralytics YOLO11 🚀
## What is Parking Management System?
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.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/WwXnljc7ZUM"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to Implement Parking Management Using Ultralytics YOLO 🚀
</p>
## Advantages of Parking Management System?
- **Efficiency**: Parking lot management optimizes the use of parking spaces and reduces congestion.
- **Safety and Security**: Parking management using YOLO11 improves the safety of both people and vehicles through surveillance and security measures.
- **Reduced Emissions**: Parking management using YOLO11 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 YOLO11](https://github.com/ultralytics/docs/releases/download/0/parking-management-aerial-view-ultralytics-yolov8.avif) | ![Parking management top view using Ultralytics YOLO11](https://github.com/ultralytics/docs/releases/download/0/parking-management-top-view-ultralytics-yolov8.avif) |
| Parking management Aerial View using Ultralytics YOLO11 | Parking management Top View using Ultralytics YOLO11 |
## 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 YOLO11"
=== "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 YOLO11 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 YOLO11 Example"
=== "Parking Management"
```python
import cv2
from ultralytics import solutions
# 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
parking_manager = solutions.ParkingManagement(
model="yolo11n.pt", # path to model file
json_file="bounding_boxes.json", # path to parking annotations file
)
while cap.isOpened():
ret, im0 = cap.read()
if not ret:
break
im0 = parking_manager.process_data(im0)
video_writer.write(im0)
cap.release()
video_writer.release()
cv2.destroyAllWindows()
```
### Optional Arguments `ParkingManagement`
| Name | Type | Default | Description |
| ----------- | ----- | ------- | -------------------------------------------------------------- |
| `model` | `str` | `None` | Path to the YOLO11 model. |
| `json_file` | `str` | `None` | Path to the JSON file, that have all parking coordinates data. |
### Arguments `model.track`
{% include "macros/track-args.md" %}
## FAQ
### How does Ultralytics YOLO11 enhance parking management systems?
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).
### What are the benefits of using Ultralytics YOLO11 for smart parking?
Using Ultralytics YOLO11 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 YOLO11?
Defining parking spaces is straightforward with Ultralytics YOLO11:
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 YOLO11 model for specific parking management needs?
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.
### What are some real-world applications of Ultralytics YOLO11 in parking lot management?
Ultralytics YOLO11 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).