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| comments: true | |
| description: Learn how to calculate distances between objects using Ultralytics YOLOv8 for accurate spatial positioning and scene understanding. | |
| keywords: Ultralytics, YOLOv8, distance calculation, computer vision, object tracking, spatial positioning | |
| # Distance Calculation using Ultralytics YOLOv8 | |
| ## What is Distance Calculation? | |
| Measuring the gap between two objects is known as distance calculation within a specified space. In the case of [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics), the 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 YOLOv8 | |
| </p> | |
| ## Visuals | |
| | Distance Calculation using Ultralytics YOLOv8 | | |
| | :---------------------------------------------------------------------------------------------------------------------------------------------: | | |
| |  | | |
| ## Advantages of Distance Calculation? | |
| - **Localization Precision:** Enhances accurate spatial positioning in computer vision tasks. | |
| - **Size Estimation:** Allows estimation of physical sizes for better contextual understanding. | |
| - **Scene Understanding:** Contributes to a 3D understanding of the environment for improved decision-making. | |
| ???+ tip "Distance Calculation" | |
| - Click on any two bounding boxes with Left Mouse click for distance calculation | |
| !!! Example "Distance Calculation using YOLOv8 Example" | |
| === "Video Stream" | |
| ```python | |
| import cv2 | |
| from ultralytics import YOLO, solutions | |
| model = YOLO("yolov8n.pt") | |
| names = model.model.names | |
| 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("distance_calculation.avi", cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h)) | |
| # Init distance-calculation obj | |
| dist_obj = solutions.DistanceCalculation(names=names, view_img=True) | |
| while cap.isOpened(): | |
| success, im0 = cap.read() | |
| if not success: | |
| print("Video frame is empty or video processing has been successfully completed.") | |
| break | |
| tracks = model.track(im0, persist=True, show=False) | |
| im0 = dist_obj.start_process(im0, tracks) | |
| video_writer.write(im0) | |
| cap.release() | |
| video_writer.release() | |
| cv2.destroyAllWindows() | |
| ``` | |
| ???+ tip "Note" | |
| - Mouse Right Click will delete all drawn points | |
| - Mouse Left Click can be used to draw points | |
| ### Arguments `DistanceCalculation()` | |
| | `Name` | `Type` | `Default` | Description | | |
| | ------------------ | ------- | --------------- | --------------------------------------------------------- | | |
| | `names` | `dict` | `None` | Dictionary of classes names. | | |
| | `pixels_per_meter` | `int` | `10` | Conversion factor from pixels to meters. | | |
| | `view_img` | `bool` | `False` | Flag to indicate if the video stream should be displayed. | | |
| | `line_thickness` | `int` | `2` | Thickness of the lines drawn on the image. | | |
| | `line_color` | `tuple` | `(255, 255, 0)` | Color of the lines drawn on the image (BGR format). | | |
| | `centroid_color` | `tuple` | `(255, 0, 255)` | Color of the centroids drawn (BGR format). | | |
| ### 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 do I calculate distances between objects using Ultralytics YOLOv8? | |
| To calculate distances between objects using [Ultralytics YOLOv8](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. You can refer to the implementation in the [distance calculation example](#distance-calculation-using-ultralytics-yolov8). | |
| ### What are the advantages of using distance calculation with Ultralytics YOLOv8? | |
| Using distance calculation with Ultralytics YOLOv8 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. | |
| ### Can I perform distance calculation in real-time video streams with Ultralytics YOLOv8? | |
| Yes, you can perform distance calculation in real-time video streams with Ultralytics YOLOv8. The process involves capturing video frames using OpenCV, running YOLOv8 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-yolov8). | |
| ### How do I delete points drawn during distance calculation using Ultralytics YOLOv8? | |
| To delete points drawn during distance calculation with Ultralytics YOLOv8, 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-yolov8). | |
| ### What are the key arguments for initializing the DistanceCalculation class in Ultralytics YOLOv8? | |
| The key arguments for initializing the `DistanceCalculation` class in Ultralytics YOLOv8 include: | |
| - `names`: Dictionary mapping class indices to class names. | |
| - `pixels_per_meter`: Conversion factor from pixels to meters. | |
| - `view_img`: Flag to indicate if the video stream should be displayed. | |
| - `line_thickness`: Thickness of the lines drawn on the image. | |
| - `line_color`: Color of the lines drawn on the image (BGR format). | |
| - `centroid_color`: Color of the centroids (BGR format). | |
| For an exhaustive list and default values, see the [arguments of DistanceCalculation](#arguments-distancecalculation). | |