Jetson Nano review and Object Detection ft. TensorRT

TL;DR

The Nvidia Jetson Nano Dev Kit is a powerful and affordable option for hobbyists and Raspberry Pi enthusiasts.

Transcript

what's going on everybody and welcome to a review slash overview of the new Nvidia Jetson nano dev kit now historically these dev kits have been on the more expensive side like 200 to 400 dollars or even more than that but the Nano comes in at $99 which in my opinion approaches more of the general hobbyist or the type of person who might be buying ... Read More

Key Insights

• 🇰🇳 The Nvidia Jetson Nano Dev Kit is an affordable option compared to previous dev kits from Nvidia.
• 💯 The Nano's 128 core Maxwell GPU, quad-core ARM CPU, and 4GB RAM make it a powerful computing platform.
• 🏂 The Nano requires extra cooling to prevent overheating, unlike Raspberry Pi boards.
• ❓ TensorRT optimization significantly improves the object detection capabilities of the Nano.
• 👻 The small size of the Nano allows for versatile applications.
• 💻 The Nano's performance and capabilities make it suitable for projects involving AI inference or computer vision.
• 😎 Additional cooling solutions, such as a fan or larger heatsink, are recommended for optimal performance.

Questions & Answers

Q: How does the Nvidia Jetson Nano Dev Kit compare to Raspberry Pi?

The Nano offers a 128 core Maxwell GPU, whereas Raspberry Pi does not have a dedicated GPU. It also provides better performance with its quad-core ARM CPU and 4GB of RAM.

Q: Does the Nano require additional cooling?

Yes, the Nano runs hotter compared to other dev kits, and even with a large heatsink, it still requires a fan or additional cooling solution to prevent overheating.

Q: Can the Nano be used in various applications?

Yes, the small size of the Nano makes it suitable for a wide range of applications, thanks to its powerful GPU, CPU, and extensive GPIO options.

Q: How does the Nano fare in terms of object detection capabilities?

The Nano demonstrated a frame rate of 1.3 frames per second when running a Tensorflow object detection model, but it significantly improved to 9.5 frames per second with the TensorRT optimization.

Summary & Key Takeaways

• The Nvidia Jetson Nano Dev Kit offers a 128 core Maxwell GPU, a quad-core ARM CPU, 4GB of RAM, and 4 USB 3.0 ports, making it a competitive option to Raspberry Pi.

• The size of the Nano board is comparable to the Raspberry Pi 3 but considerably smaller than older dev kit boards like the TK1 and TX1.

• The Nano requires extra cooling, such as a fan or bigger heatsink, due to its GPU running hotter compared to other dev kits.