Nvidia Jetson Nano Custom Object Detection

The purpose of this blog is to guide users on the creation of a custom object detection model with performance optimization to be used on an nvidia jetson nano.

Nvidia jetson nano custom object detection. Saving images for the dataset in data images folder. Run several object detection examples with nvidia tensorrt. Train model for custom object detection. Code your own real time object detection program in python from a live camera feed.

Nvidia jetson nano is a developer kit which consists of a som system on module and a reference carrier board. This is a report for a final project. It is primarily targeted for creating embedded systems that require high processing power for machine learning machine vision and vide. This article is a project showing how you can create a real time multiple object detection and recognition application in python on the jetson nano developer kit using the raspberry pi camera v2 and deep learning models and libraries that nvidia provides.

Setup your nvidia jetson nano and coding environment by installing prerequisite libraries and downloading dnn models such as ssd mobilenet and ssd inception pre trained on the 90 class ms coco dataset. Saving corresponding xml files for every images of the dataset using labelimg in.