Ara Vision Examples

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Multi-Stream YOLOv8 Object Detection 

This post shows a walkthrough of the ARA2 Vision Examples package and its multi-stream YOLOv8 object detection application.

The ara2-vision-examples package provides vision AI examples for NXP i.MX platforms using Ara240 DNPU acceleration. It demonstrates real-time video processing with AI/ML inference capabilities such as object detection, classification, pose estimation, and semantic segmentation.

This walkthrough focuses on the multistream_yolov8 application, which uses GStreamer to process up to eight simultaneous video streams, run YOLOv8 object detection on each stream, and display the results in a single mosaic view.

 

Key Features

• Multi-stream video processing from 1 to 8 streams
• YOLOv8 object detection accelerated by Ara240 DNPU
• Support for YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x models
• GStreamer-based video pipeline
• Mosaic display output with bounding boxes
• Runtime options for stream count, model selection, synchronization, and endpoint selection
• FPS and IPS performance overlay per stream

 

Running the Demo

Run the application with the default settings:

multistream_yolov8

Run with a specific number of streams:

multistream_yolov8 -s 4

Select a different YOLOv8 model:

multistream_yolov8 -s 4 --model yolov8s

Run eight streams for maximum throughput:

multistream_yolov8 -s 8 --sync false

Enable synchronized playback:

multistream_yolov8 -s 4 --sync true

 

Walkthrough Video

In the attached video, it is shown how to launch the application, configure the number of streams, select different YOLOv8 models, and view the object detection results in the mosaic display.

 

Links

• ARA2 Vision Examples repository:
  https://github.com/nxp-imx-support/ara2-vision-examples

• Multi-stream YOLOv8 README:
  https://github.com/nxp-imx-support/ara2-vision-examples/blob/main/tasks/object-detection/yolov8n/mul...