World's fastest ANPR / ALPR implementation for CPUs, GPUs, VPUs and NPUs using deep learning (Tensorflow, Tensorflow lite, TensorRT, OpenVX, OpenVINO). Multi-Charset (Latin, Korean, Chinese) & Multi-OS (Jetson, Android, Raspberry Pi, Linux, Windows) & Multi-Arch (ARM, x86).

'24 Capstone project 날아오르라 졸작이여 Team

ROSMASTER X1 ROS Robot for Jetson NANO 4GB/RaspberryPi 5

How to: Monitor SD card health and status using Raspberry Pi and NVIDIA Jetson

📊 Simple package for monitoring and control your NVIDIA Jetson [Orin, Xavier, Nano, TX] series

Open source hardware and software platform to build a small scale self driving car.

Open-Source. With deep learning to neuroscience world with shield for jetson nano - JNEEG (In progress)

JetGuard: A smart and agile robot powered by AI and the Nvidia Jetson Nano platform. Mastering autonomous navigation and obstacle avoidance

C library to manage the GPIO header of the Nvidia Jetson boards

A c++ implementation of yolov5 and deepsort

Hardware accelerated OpenCV, Torch & Tensorrt Ubuntu 20.04 docker images for Jetson Nano containing any python version you need up until the latest 3.12

Example of data callection / generation / training process / inference on a camera

Setup guide for jetson nano

Vision Components MIPI CSI-2 driver for NVIDIA Jetson Nano, Xavier NX, AGX Xavier, TX2 and Orin Nano, Orin NX

Computer Vision Gateway for real-time stream processing

Get ready to work with a powerful combination of technologies! This project involves setting up your Jetson Nano, installing the Jetpack SDK, and mastering image processing with OpenCV. For the machine learning component, you'll be using TensorFlow.

An easy to use PyTorch to TensorRT converter

Shared code for the AI Racing League

A 6 degree of freedom (DOF) robot arm is controlled using the ROS2 robotic manipulation platform, MoveIt 2. The ROS2 Humble version of MoveIt 2 is used, which runs in a Docker container on an Nvidia Jetson Nano board. The robot arm is equipped with an Intel Realsense D415 depth camera used to detect ArUco markers on objects to be picked up.

This repository contains the content for a proof of concept implementation of computer vision systems in industry. The project explores scalability and performance using the NVIDIA ecosystem, aiming to create an example scaffold for implementing a system accessible to non-technical users.