Luxonis OAK-1 (LUX-1) kit with enclosure
Luxonis OAK-1 (LUX-1) kit with enclosure
Luxonis OAK-1 (LUX-1) kit with enclosure
Luxonis OAK-1 (LUX-1) kit with enclosure
Luxonis OAK-1 (LUX-1) kit with enclosure

Luxonis OAK-1 (LUX-1) kit with enclosure

Regular price
$149.00
Sale price
$149.00
Unit price
per 
Shipping calculated at checkout.


USUALLY SHIPS WITHIN 3 BUSINESS DAYS

Luxonis OAK-1 isn’t a standard USB camera.  It’s a 4-trillion-operations-per-second AI powerhouse that performs your AI models on-board, so that your host is free to do whatever you need it to do.  

Its integrated 12 MegaPixel camera module communicates over an on-board 2.1 Gbps MIPI interface directly to the Myriad X, which ingests this data and performs neural inference on it, returning the results over USB.

Such a data path offloads the host processor from all of this work.  In the common use case of object detection from a 12MP image, this means your host is now dealing with a 24 Kbps stream of what the objects are and where they are in the image, instead of a 2.1 Gbps stream of video.  So an 87,500 reduction in data your host has to deal with.

And such a reduction means that even on relatively-slow hosts, one can use dozens of Luxonis OAK-1 without burdening the host CPU.

As an example, below is an example of running MobileNet-SSD:

OAK-1 + Raspberry Pi: 50+FPS, 0% RPi CPU Utilization

NCS2 + Raspberry Pi: 8FPS, 225% CPU Utilization


SHIPPING 

Shipping cost is based on destination. Just add products to your cart and use the Shipping Calculator to see the shipping price.

RETURNS

We want you to be 100% satisfied with your purchase. Items can be returned or exchanged within 30 days of delivery.

HELP

For help, please contact support@luxonis.com

Part Number: LUX-1

Note: This was previously referred to as the 'MEGAAI-KIT' and now is the 'LUX-1' 

 

Documentation and Resources:

  • Product Brief: here
  • DepthAI Documentation: here
  • DepthAI Discussion Forum: here
  • Discord Community: here
  • Python Github: here
  • C++ API Github: here
  • Hardware Github: here
  • DepthAI Models Overview: here