image_to_pixle_params_yoloSAM/ultralytics-main/docs/en/guides/distance-calculation.md

---
comments: true
description: Learn how to calculate distances between objects using Ultralytics YOLO11 for accurate spatial positioning and scene understanding.
keywords: Ultralytics, YOLO11, distance calculation, computer vision, object tracking, spatial positioning
---

# Distance Calculation using Ultralytics YOLO11

## What is Distance Calculation?

Measuring the gap between two objects is known as distance calculation within a specified space. In the case of [Ultralytics YOLO11](https://github.com/ultralytics/ultralytics), the [bounding box](https://www.ultralytics.com/glossary/bounding-box) centroid is employed to calculate the distance for bounding boxes highlighted by the user.

<p align="center">
  <br>
  <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LE8am1QoVn4"
    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> Distance Calculation using Ultralytics YOLO11
</p>

## Visuals

|                                         Distance Calculation using Ultralytics YOLO11                                         |
| :---------------------------------------------------------------------------------------------------------------------------: |
| ![Ultralytics YOLO11 Distance Calculation](https://github.com/ultralytics/docs/releases/download/0/distance-calculation.avif) |

## Advantages of Distance Calculation?

- **Localization [Precision](https://www.ultralytics.com/glossary/precision):** Enhances accurate spatial positioning in [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) tasks.
- **Size Estimation:** Allows estimation of object size for better contextual understanding.
- **Scene Understanding:** Improves 3D scene comprehension for better decision-making in applications like [autonomous vehicles](https://www.ultralytics.com/glossary/autonomous-vehicles) and surveillance systems.
- **Collision Avoidance:** Enables systems to detect potential collisions by monitoring distances between moving objects.
- **Spatial Analysis:** Facilitates analysis of object relationships and interactions within the monitored environment.

???+ tip "Distance Calculation"

    - Click on any two bounding boxes with Left Mouse click for distance calculation
    - Mouse Right Click will delete all drawn points
    - Mouse Left Click can be used to draw points

???+ warning "Distance is Estimate"

        Distance will be an estimate and may not be fully accurate, as it is calculated using 2-dimensional data,
        which lacks information about the object's depth.

!!! example "Distance Calculation using Ultralytics YOLO"

    === "Python"

        ```python
        import cv2

        from ultralytics import solutions

        cap = cv2.VideoCapture("path/to/video.mp4")
        assert cap.isOpened(), "Error reading video file"

        # Video writer
        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 = cv2.VideoWriter("distance_output.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))

        # Initialize distance calculation object
        distancecalculator = solutions.DistanceCalculation(
            model="yolo11n.pt",  # path to the YOLO11 model file.
            show=True,  # display the output
        )

        # Process video
        while cap.isOpened():
            success, im0 = cap.read()

            if not success:
                print("Video frame is empty or processing is complete.")
                break

            results = distancecalculator(im0)

            print(results)  # access the output

            video_writer.write(results.plot_im)  # write the processed frame.

        cap.release()
        video_writer.release()
        cv2.destroyAllWindows()  # destroy all opened windows
        ```

### `DistanceCalculation()` Arguments

Here's a table with the `DistanceCalculation` arguments:

{% from "macros/solutions-args.md" import param_table %}
{{ param_table(["model"]) }}

You can also make use of various `track` arguments in the `DistanceCalculation` solution.

{% from "macros/track-args.md" import param_table %}
{{ param_table(["tracker", "conf", "iou", "classes", "verbose", "device"]) }}

Moreover, the following visualization arguments are available:

{% from "macros/visualization-args.md" import param_table %}
{{ param_table(["show", "line_width", "show_conf", "show_labels"]) }}

## Implementation Details

The `DistanceCalculation` class works by tracking objects across video frames and calculating the Euclidean distance between the centroids of selected bounding boxes. When you click on two objects, the solution:

1. Extracts the centroids (center points) of the selected bounding boxes
2. Calculates the Euclidean distance between these centroids in pixels
3. Displays the distance on the frame with a connecting line between the objects

The implementation uses the `mouse_event_for_distance` method to handle mouse interactions, allowing users to select objects and clear selections as needed. The `process` method handles the frame-by-frame processing, tracking objects, and calculating distances.

## Applications

Distance calculation with YOLO11 has numerous practical applications:

- **Retail Analytics:** Measure customer proximity to products and analyze store layout effectiveness
- **Industrial Safety:** Monitor safe distances between workers and machinery
- **Traffic Management:** Analyze vehicle spacing and detect tailgating
- **Sports Analysis:** Calculate distances between players, the ball, and key field positions
- **Healthcare:** Ensure proper distancing in waiting areas and monitor patient movement
- **Robotics:** Enable robots to maintain appropriate distances from obstacles and people

## FAQ

### How do I calculate distances between objects using Ultralytics YOLO11?

To calculate distances between objects using [Ultralytics YOLO11](https://github.com/ultralytics/ultralytics), you need to identify the bounding box centroids of the detected objects. This process involves initializing the `DistanceCalculation` class from Ultralytics' `solutions` module and using the model's tracking outputs to calculate the distances.

### What are the advantages of using distance calculation with Ultralytics YOLO11?

Using distance calculation with Ultralytics YOLO11 offers several advantages:

- **Localization Precision:** Provides accurate spatial positioning for objects.
- **Size Estimation:** Helps estimate physical sizes, contributing to better contextual understanding.
- **Scene Understanding:** Enhances 3D scene comprehension, aiding improved decision-making in applications like autonomous driving and surveillance.
- **Real-time Processing:** Performs calculations on-the-fly, making it suitable for live video analysis.
- **Integration Capabilities:** Works seamlessly with other YOLO11 solutions like [object tracking](../modes/track.md) and [speed estimation](speed-estimation.md).

### Can I perform distance calculation in real-time video streams with Ultralytics YOLO11?

Yes, you can perform distance calculation in real-time video streams with Ultralytics YOLO11. The process involves capturing video frames using [OpenCV](https://www.ultralytics.com/glossary/opencv), running YOLO11 [object detection](https://www.ultralytics.com/glossary/object-detection), and using the `DistanceCalculation` class to calculate distances between objects in successive frames. For a detailed implementation, see the [video stream example](#distance-calculation-using-ultralytics-yolo11).

### How do I delete points drawn during distance calculation using Ultralytics YOLO11?

To delete points drawn during distance calculation with Ultralytics YOLO11, you can use a right mouse click. This action will clear all the points you have drawn. For more details, refer to the note section under the [distance calculation example](#distance-calculation-using-ultralytics-yolo11).

### What are the key arguments for initializing the DistanceCalculation class in Ultralytics YOLO11?

The key arguments for initializing the `DistanceCalculation` class in Ultralytics YOLO11 include:

- `model`: Path to the YOLO11 model file.
- `tracker`: Tracking algorithm to use (default is 'botsort.yaml').
- `conf`: Confidence threshold for detections.
- `show`: Flag to display the output.

For an exhaustive list and default values, see the [arguments of DistanceCalculation](#distancecalculation-arguments).