Distance Calculation using Ultralytics YOLO11

Q: 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: For an exhaustive list and default values, see the arguments of DistanceCalculation.

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, the 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

Advantages of Distance Calculation?

Localization Precision: Enhances accurate spatial positioning in computer vision tasks.
Size Estimation: Allows estimation of object size for better contextual understanding.

Distance Calculation

Click on any two bounding boxes with Left Mouse click for distance calculation

Distance Calculation using YOLO11 Example

Video Stream

import cv2

from ultralytics import solutions

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
distance = solutions.DistanceCalculation(model="yolo11n.pt", show=True)

# Process video
while cap.isOpened():
    success, im0 = cap.read()
    if not success:
        print("Video frame is empty or video processing has been successfully completed.")
        break
    im0 = distance.calculate(im0)
    video_writer.write(im0)

cap.release()
video_writer.release()
cv2.destroyAllWindows()

Note

Mouse Right Click will delete all drawn points
Mouse Left Click can be used to draw points

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.

Arguments `DistanceCalculation()`

`Name`	`Type`	`Default`	Description
`model`	`str`	`None`	Path to Ultralytics YOLO Model File
`line_width`	`int`	`2`	Line thickness for bounding boxes.
`show`	`bool`	`False`	Flag to control whether to display the video stream.

Arguments `model.track`

Argument	Type	Default	Description
`source`	`str`	`None`	Specifies the source directory for images or videos. Supports file paths and URLs.
`persist`	`bool`	`False`	Enables persistent tracking of objects between frames, maintaining IDs across video sequences.
`tracker`	`str`	`botsort.yaml`	Specifies the tracking algorithm to use, e.g., `bytetrack.yaml` or `botsort.yaml`.
`conf`	`float`	`0.3`	Sets the confidence threshold for detections; lower values allow more objects to be tracked but may include false positives.
`iou`	`float`	`0.5`	Sets the Intersection over Union (IoU) threshold for filtering overlapping detections.
`classes`	`list`	`None`	Filters results by class index. For example, `classes=[0, 2, 3]` only tracks the specified classes.
`verbose`	`bool`	`True`	Controls the display of tracking results, providing a visual output of tracked objects.

FAQ

How do I calculate distances between objects using Ultralytics YOLO11?

To calculate distances between objects using Ultralytics YOLO11, 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.

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.

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, running YOLO11 object detection, and using the DistanceCalculation class to calculate distances between objects in successive frames. For a detailed implementation, see the video stream example.

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.

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: Model file path.
show: Flag to indicate if the video stream should be displayed.
line_width: Thickness of bounding box and the lines drawn on the image.

For an exhaustive list and default values, see the arguments of DistanceCalculation.

📅 Created 11 months ago ✏️ Updated 1 month ago