Qengineering/YoloV8-ncnn-Raspberry-Pi-4
YoloV8 for a bare Raspberry Pi 4 or 5
This project enables real-time object detection directly on a Raspberry Pi 4 or 5, transforming live camera feeds or images into identified objects with bounding boxes. It's designed for hobbyists, educators, or engineers who need to deploy computer vision solutions on low-cost, embedded hardware without cloud services. You provide video frames or images, and it outputs recognized objects and their locations.
118 stars. No commits in the last 6 months.
Use this if you need to perform fast object detection on an edge device using a Raspberry Pi 4 or 5 and want to deploy YoloV8 models for tasks like monitoring or automation.
Not ideal if you require extremely high frame rates beyond what a bare Raspberry Pi can achieve, or if you prefer a system that leverages dedicated AI accelerators found in more powerful embedded systems like a Jetson Nano.
Stars
118
Forks
13
Language
C++
License
BSD-3-Clause
Category
Last pushed
Jun 16, 2024
Commits (30d)
0
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