Video & Cameras
FPGA Boards
Machine Learning

Vision FPGA SoM

An FPGA-based SoM with integrated vision, audio, and motion-sensing capability

$6,970 raised

of $6,300 goal

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Low-power Computer Vision

Embedded Computer Vision is a highly multi-disciplinary field that requires expertise in optics, image sensors, hardware, firmware and so on. As a result, the bar to playing with technology in this field is quite high.

The Vision FPGA SoM is a Lattice FPGA based System on Module that integrates an ultra-low-power vision sensor, a 3-axis accelerometer/gyroscope, and an I²S MEMS microphone in a small form-factor (3 cm x 2 cm).

This device is built for developers who want to not only play with this technology, but also have a path to integrating it into real world products. We designed the device with the following thoughts in mind:

The modular concept is summarized in a talk given at a tinyML meetup in 2019.

Flexible and Tightly Integrated

By including most commonly used sensors in a configurable platform utilizing an FPGA with an open source toolchain, this device enables developers to experiment and build quickly. Sample FPGA, as well as host code will be provided as a jumping off point for backers.

Features & Specifications

Accessories for Development and Prototyping

SoM Developer Board

The Developer Board provides the following functionality that enables application development using the module:

The Developer board also has a Raspberry Pi Hat connector. This leverages the extensive RPi ecosystem to develop applications using the Vision FPGA SoM. This enables new use cases for a Raspberry Pi Zero W (including the ones as shown in Adafruit Pi Hat:

SoM Breakout Board

The breakout board is in the Adafruit Feather form factor and has the following features:

Note: the FPGA programming must be done using an external SPI master. The USB port is purely to supply power.

Comparisons

ItemFPGA Vision SoMiCEBreakerTinyFPGA BXTomu FPGA
OSHW? OSHWOSHWOSHWOSHWClosed
Price $100$69$38$45$49.49
Schematics Published? YesYesYesNot yetYes
Design Files Published? Not YetYesYesNot yetNo
Volume Production Friendly? YesNoNoNoNo
FPGA
FPGA Model iCE40UP5KiCE40UP5KiCE40LP8KiCE40UP5KiCE40HX1K
Logic Capacity (LUTs) 52805280768052801280
Internal RAM (bits) 120k + 1024k120k + 1024k128k120k + 1024k64k
Multipliers 88080
Peripherals
USB Interface FTDI 2232HQ (dev kit)FTDI 2232HQOn FPGA bootloaderOn FPGA bootloaderFTDI 2232HL
User IOs 827 + 741 + 24 + 218
Pmod Connectors 1 (dev board)3001
User Buttons 01 tactile + 3 tactile on breakoff Pmod1 reset2 capacitive0
User LED 1 tricolor, high-power IR LED2 on-board4 on dev board2 + 5 on breakoff Pmod5
Onboard Clock 12 MHz, shared with FTDI12 MHz, shared with FTDI16 MHz12 MHz12 MHz, shared with FTDI
Flash 8 Mb QSPI128 Mbit QSPI DDR8 Mbit SPI16 Mbit SPI32 Mbit SPI
SRAM 64 Mbit QSPI PSRAMNoNoNoNo
IMU InvenSense 6 DOF (accellerometer + gyroscope)NoNoNoNo
Mic MEMS I²S microphoneNoNoNoNo
Power Measurement On dev kitNoNoNoNo
Open Source Toolchain YesYesYesYesYes
APIO YesYesYesYesYes
Icestudio YesYesYesNot yetYes
Migen NoYesYesNoYes

Support & Documentation

All data about the SoM is captured in the Vision FPGA SoM GitHub repo and will be updated over time with sample code, Colab notebooks, etc.

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Produced by tinyVision.ai in San Diego, CA.

Sold and shipped by Crowd Supply.

Vision FPGA SoM

A FPGA Vision SoM to play with!

$100 $8 US Shipping / $18 Worldwide

SoM Breakout Board

The SoM breakout board brings all SoM pins to 2.54 mm pitch pins for breadboarding, can't do without it! SoMe assembly required to solder the 2.54 mm headers on. Note: SoM is not included.

$25 Shipping Priced By Weight Worldwide

SoM Developer Board

One developer board that breaks out SoM IO with in-line LEDs, includes a Raspberry Pi HAT connector, allows for USB power (with power monitoring) and programming, includes PMOD and QWIIC connectors, and has room for prototyping. Note: SoM is NOT included.

$90 $8 US Shipping / $18 Worldwide

About the Team

tinyVision.ai

tinyVision.ai works closely with clients to incorporate low power CV into their devices. We are enabling CV with hardware in the form of tightly integrated CV modules with a clean API.

See Also

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