YoloV5-ncnn-Jetson-Nano and YoloX-ncnn-Jetson-Nano
These two tools are competitors, offering different YOLO architectures (YOLOv5 vs. YOLOX) optimized for inference on a Jetson Nano using the ncnn neural network inference framework.
About YoloV5-ncnn-Jetson-Nano
Qengineering/YoloV5-ncnn-Jetson-Nano
YoloV5 for Jetson Nano
This project helps you detect and identify multiple objects within live video feeds or images using a low-cost, energy-efficient Jetson Nano device. It takes an image or video frame as input and outputs the same image or frame with bounding boxes and labels around detected objects. Anyone building embedded computer vision applications for scenarios like surveillance, robotics, or smart cameras would use this.
About YoloX-ncnn-Jetson-Nano
Qengineering/YoloX-ncnn-Jetson-Nano
YoloX for a Jetson Nano using ncnn.
This project enables real-time object detection on embedded devices. It takes a video stream or image as input and identifies specific objects, outputting bounding boxes around them and their labels. It's designed for engineers and hobbyists building applications on NVIDIA Jetson Nano boards that require fast, localized image analysis.
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