Qengineering/YoloV5-ncnn-Raspberry-Pi-4
YoloV5 for a bare Raspberry Pi 4
This project helps embedded systems developers quickly implement object detection on a Raspberry Pi 4. It takes image or video data as input and outputs identified objects with bounding boxes, allowing for real-time analysis on low-power devices. Developers working on edge computing or embedded vision projects would use this.
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Use this if you need to perform object detection using the YoloV5 model on a Raspberry Pi 4 for embedded vision applications.
Not ideal if you require object detection on other hardware platforms, demand extremely high frame rates beyond the Raspberry Pi 4's capabilities, or prefer a different object detection model.
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55
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6
Language
C++
License
BSD-3-Clause
Category
Last pushed
Jun 04, 2024
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