YOLO 11 with NCNN: setup for Raspberry Pi and RDK boards

This tutorial, uploaded April 26, 2025, covers YOLO 11 object detection with a Logitech USB camera on edge hardware. The speaker says the workflow applies to Raspberry Pi, Jetson Nano, RDK X3 and RDK X5. The software examples and setup steps reflect that upload's context; the source does not specify an operating system release.

The demonstration starts with a laggy, unoptimized detector, then shows an NCNN version that the speaker reports runs at 3 to 4 frames per second. That is a result from the demonstration, not a benchmark for every listed board or a guarantee of real-time performance. The conversion example loads a YOLO 11 model and exports it with the format set to ncnn. The speaker then loads the exported model folder for inference. He suggests other YOLO models may work but does not establish their compatibility.

For the on-device camera output, the tutorial uses Supervision to turn Ultralytics detections into labels and bounding boxes. The hardware portion examines RDK X3 ports, its camera ribbon connection and a metal case with a thermal pad. It also covers RDK X5 specifications, including 4 GB and 8 GB RAM options and a 5 V, 5 A power supply. The final setup example downloads an RDK X3 OS image and flashes it to a microSD card with Balena Etcher.