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comments | description | keywords |
---|---|---|
true | Learn how to calculate distances between objects using Ultralytics YOLO11 for accurate spatial positioning and scene understanding. | Ultralytics, YOLO11, distance calculation, computer vision, object tracking, spatial positioning |
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
Distance Calculation using Ultralytics YOLO11 |
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???+ tip "Distance Calculation"
- Click on any two bounding boxes with Left Mouse click for distance calculation
!!! example "Distance Calculation using YOLO11 Example"
=== "Video Stream"
```python
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
???+ 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.
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. |
model.track
{% include "macros/track-args.md" %}
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.
Using distance calculation with Ultralytics YOLO11 offers several advantages:
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.
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.
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.
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