Nvidia Jetson Nano Image Recognition

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Nvidia jetson nano image recognition. This tutorial takes roughly two days to complete from start to finish enabling you to configure and train your own neural networks. From jetbot import objectdetector model objectdetector ssd mobilenet v2 coco engine from jetbot import camera camera camera. In which opencv frontal face xml is used crop the face and encode the facial features in 128 vectors and train and store it in a pickle file and use it compare with the input faces. This video is based on the hello ai world demo provided.

We show you how to run inference train a cnn from scratch and do transfer learning with pytorch on nvidia s jetson nano. It includes all of the necessary source code. I used the one of face recognition tutorial by pyimage search. While no errors are displayed the image does not show running.

Two days to a demo is our introductory series of deep learning tutorials for deploying ai and computer vision to the field with nvidia jetson agx xavier jetson tx2 jetson tx1 and jetson nano. Jetson nano performing vision recognition on a live video stream using a deep neural network dnn. Nvidia academic partners and inception members present ai research at cvpr 2020. I use 20 images for each face.

This bot running on the nvidia jetson nano can ask for a toy identify and state its name and play videos related to it. I m following jetbot tutorials and trying to get object following notebook example working using both a standard raspberry pi and waveshare raspberry pi camera module g w fisheye lens. The nvidia jetson nano developer kit is a small ai computer for makers learners and developers. Utilize the nvidia jetson nano to run multiple deep neural networks on a single board including image classification object detection segmentation and more.

I used jetson nano ubuntu 18 04 official image with root account. The jetson nano board provides fp16 compute power and using tensorrt s graph optimizations and kernel fusion production level performance can be obtained for nlp image segmentation object detection and recognition applications.