Tutorial: Configure NVIDIA Jetson Nano as an AI Testbed
In the last part of this tutorial series on the NVIDIA Jetson Nano development kit, I provided an overview of this powerful edge computing device. In the current installment, I will walk through the steps involved in configuring Jetson Nano as an artificial intelligence testbed for inference. You will learn how to install, configure, and use TensorFlow, OpenCV, and TensorRT at the edge.
Recommended Accessories for Jetson Nano
To get the best out of the device, you need an external power supply with a 5V 4A rating which is connected to the power barrel jack. The default MicroUSB is just not enough to drive the GPU and attached peripherals like a USB camera.
To force the board to draw power from an external adapter, you got to place a jumper on J48 which is located next to the camera interface on the board.
It is highly recommended that you use a 32GB micro SD card with Jetson Nano. This will be sufficient to mount the swap drive, downloading the required software and models.
Finally, use a compatible USB webcam for optimal performance. I use the Logitech 270 webcam but there are other models with higher resolution that may work with Nano.
Read the entire article at The New Stack
Janakiram MSV is an analyst, advisor, and architect. Follow him on Twitter, Facebook and LinkedIn.