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Fix mkdocs.yml raw image URLs (#14213)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com>
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docs/en/guides/distance-calculation.md
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@ -4,7 +4,7 @@ description: Learn how to calculate distances between objects using Ultralytics
keywords: Ultralytics, YOLOv8, distance calculation, computer vision, object tracking, spatial positioning
---
# Distance Calculation using Ultralytics YOLOv8 🚀
# Distance Calculation using Ultralytics YOLOv8
## What is Distance Calculation?
@ -101,3 +101,38 @@ Measuring the gap between two objects is known as distance calculation within a
| `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).