Object detection - YOLOv8 Python lib

YOLOv8 - detection, segmentation and pose estimation with Pipeless

This example makes use of the Ultralytics YOLO Python package to perform object detection.


This example uses YOLOv8 by importing the Ultralytics Python library, unlinke the onnx-yolo example, which loads the YOLO model into the ONNX Runtime.


  • Pipeless: Check the installation guide.

  • Python OpenCV, NumPy and Ultralytics packages. Install them by running:

pip install opencv-python numpy ultralytics

Run the example

Create an empty Pipeless project

pipeless init my-project --template empty # Using the empty template we avoid the interactive shell
cd my-project

Feel free to change my-project by any name you want.

Download the stage folder

wget -O - https://github.com/pipeless-ai/pipeless/archive/main.tar.gz | tar -xz --strip=2 "pipeless-main/examples/yolo"

Start Pipeless

The following command leaves Pipeless running on the current terminal

pipeless start --stages-dir .

Provide a stream

Open a new terminal and run:

pipeless add stream --input-uri "v4l2" --output-uri "screen" --frame-path "yolo"

This command assumes you have a webcam available, if you don't just change the input URI.