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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, the bounding box centroid is employed to calculate the distance for bounding boxes highlighted by the user.


Distance Calculation using Ultralytics YOLOv8
Ultralytics YOLOv8 Distance Calculation

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.
Distance Calculation
  • Click on any two bounding boxes with Left Mouse click for distance calculation

Distance Calculation using YOLOv8 Example

from ultralytics import YOLO
from import distance_calculation
import cv2

model = YOLO("")
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",
                               (w, h))

# Init distance-calculation obj
dist_obj = distance_calculation.DistanceCalculation()
dist_obj.set_args(names=names, view_img=True)

while cap.isOpened():
    success, im0 =
    if not success:
        print("Video frame is empty or video processing has been successfully completed.")

    tracks = model.track(im0, persist=True, show=False)
    im0 = dist_obj.start_process(im0, tracks)

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

Optional Arguments set_args

Name Type Default Description
names dict None Classes names
view_img bool False Display frames with counts
line_thickness int 2 Increase bounding boxes thickness
line_color RGB (255, 255, 0) Line Color for centroids mapping on two bounding boxes
centroid_color RGB (255, 0, 255) Centroid color for each bounding box

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

Created 2024-01-05, Updated 2024-02-10
Authors: (4), glenn-jocher (2), AyushExel (1)