NOTE: As promised, this model is back in stock!
What is DepthAI?
DepthAI is a platform built to allow the power of Spatial AI to be embedded into products.
The DepthAI hardware, firmware, and software suite combine depth perception, object detection (neural inference), and object tracking and gives you this power in a simple, easy-to-use API.
About the LUX-ESP32 DepthAI Model
This is the Embedded Reference Design and the WiFi+Bluetooth-capable version of DepthAI. It can be used completely standalone, or via USB with a host like normal USB-only variants of DepthAI.
Features the BNO085 IMU over SPI.
The key difference between this BW1099EMB system on module and the standard BW1099 is that the standard BW1099 requires a host processor, running Linux, Mac, or Windows to operate, whereas this module can boot out of NOR flash - allowing SPI communication with microcontrollers which may be running no operating system at all (bare metal C or C++ code).
Where do I find the SPI APIs and reference code?
- depthai-spi-api - API of the SPI protocol
- depthai-spi-library - DepthAI SPI Library
- esp32-spi-message-demo - ESP32 reference app for interfacing with DepthAI over SPI
About the BW1099EMB
• All connectivity of the BW1099EMB is through single 100-pin connector (DF40C-100DP-0.4V(51))
- 2x 2-lane MIPI Camera Interface
- 1x 4-lane MIPI Camera Interface
- Quad SPI with 2 dedicated chip-selects
- Several GPIO (1.8 V and 3.3 V)
- Supports off-board eMMC or SD Card
- On-board NOR boot Flash (optional)
- On-board EEPROM (optional)
- All power regulation, clock generation, etc. on module
PCBA Part Number: BW1099EMB
- US version: LUX-ESP32-AB
- International version: LUX-ESP32-INTL
(The difference between the versions is simply the included power supply, and whether international power adapters are used or not.)
Note: This was previously referred to as the 'BW1092' & 'DM1092', and now is the 'LUX-ESP32-AB' and 'LUX-ESP32-INTL'
Documentation and Resources:
- Python Github: here
- C++ API Github: here
- SPI C Library: here
- SPI ESP32 Example App: here
- Hardware Github: here
- DepthAI Models Overview: here