--- 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.



Watch: Distance Calculation using Ultralytics YOLO11

## 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).