Vision FPGA SoM Integrates Audio, Vision and Motion-Sensing with Lattice iCE40 FPGA (Crowdfunding)

tinyVision.ai’s Vision FPGA SoM is a tiny Lattice iCE40 powered FPGA module with integrated vision, audio, and motion-sensing capability with a CMOS image sensor, an I2S MEMS microphone and a 6-axis accelerometer & gyroscope. The module enables low power vision (10-20 mW) for battery-powered applications, can interface via SPI  to a host processor as a storage device, comes with open-source toolchain and sample code, and is optimized for volume production. Vision FPGA SoM specifications: FPGA – Lattice iCE40UP5k FPGA with 5K LUT’s, 1 Mb RAM, 8 MAC units Memory – 64 Mbit QSPI SRAM for temporary data Storage – 4 Mbit QSPI Flash for FPGA bitstream/code storage Sensors Himax HM01B0 CMOS image sensor Knowles MEMS I2S microphone, expandable to a stereo configuration with an off-board I2S microphone InvenSense IMU 60289 6-axis Gyro/accelerometer I/Os 4x GPIOs with programmable IO voltage SPI host interface with programmable IO voltage Misc – Tri-color LED, IR LED for low-light illumination Power Supply Single 3.3 V …

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Raspberry Pi SBC Now Supports OpenVX 1.3 Computer Vision API

OpenVX is an open, royalty-free API standard for cross-platform acceleration of computer vision applications developed by The Khronos Group that also manages the popular OpenGL ES, Vulkan, and OpenCL standards. After OpenGL ES 3.1 conformance for Raspberry Pi 4, and good progress on the Vulkan implementation, the Raspberry Pi Foundation has now announced that both Raspberry Pi 3 and 4 Model B SBC’s had achieved OpenVX 1.3 conformance (somehow dated 2020-07-23). Raspberry Pi OpenVX open-source sample implementation passes the Vision, Enhanced Vision, & Neural Net conformance profiles specified in OpenVX 1.3 standard. However, it is NOT intended to be a reference implementation, as it is not optimized, production-ready, nor actively maintained by Khronos publically. The sample can be built on multiple operating systems (Windows, Linux, Android) using either CMake or Concerto. Detailed instructions are provided for Ubuntu 18.04 64-bit x86 and Raspberry Pi SBC. Here’s the list of commands to retrieve the code, build it, and run it on Raspberry …

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ROScube Pico SBC Runs Ubuntu & ROS on Intel Atom or Rockchip PX30 Processor

ADLINK has launched ROScube Pico SBC designed for robotics projects and powered by either an Intel Atom x5 Apollo Lake processor or a Rockchip PX30 Arm Cortex-A35 processor via their SMARC-compliant system-on-modules namely LEC-AL and as LEC-PX30. Both models run Ubuntu and ROS/ROS-2 operating systems simultaneously, and the company also provides NeuronBot robotics development and demo kit based on the SBC. ROScube Pico SBC and Devkit If ROScube Pico looks similar it’s because it appears to be based entirely on ADLINK previously announced ADLINK Industrial-Pi (I-Pi) SMARC Development Kit based on Rockchip PX30, and Vizi-AI development starter kit based on Atom x5-E3940 SoC and Movidius Myriad X VPU. Those are the specifications listed for ROScube Pico: SMARC Module For ROScube Pico NPS-1 – LEC-AL with Intel Atom processor, Intel Movidius Myriad X AI accelerator, 8GB LPDDR4 RAM, 32GB eMMC For ROScube Pico NPS-4 – LEC-PX30 with Rockchip PX-30 quad-core Cortex-A35 processor, 2GB DDR3L RAM Storage – Optional 32GB Micro SD …

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Ryzen Embedded SBC is Made for Real-time AI Vision, Conveyor Belt Tracking

Axiomtek just recently introduced CAPA13R AMD Ryzen Embedded V1605B/V1807B SBC in 3.5″ embedded SBC form factor, and the company is now back with another, larger Ryzen Embedded SBC: Axiomtek MIRU130. Why would they launch yet another Ryzne Embedded board two weeks later? Different applications. While CAPA13R targets various graphics-intensive applications ranging from medical imaging to smart digital signage, MIRU130 appears to be especially focused on real-time vision-based AI applications with PoE and USB ports for cameras, and integrated “real-time vision I/Os” such as trigger inputs, LED lighting controllers, camera trigger outputs and an encoder input designed for conveyor tracking. MIRU130 SBC specifications: SoC (One or the other) – AMD Ryzen Embedded V1807B or V1605B quad-core processor with Radeon Vega 8 graphics; V1807B: 35-54W TDP; V1605B: 12-25W TDP System Memory – 2x 240-pin DDR4-2400 SO-DIMM, up to 16GB RAM Storage 1x SATA-600 1x M.2 Key B (SATA, USB 2.0, PCIe x2 optional) in 22×42, 22×80 or 30×42 BIOS AMI Display – …

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iWave Systems i.MX8M Mini Devkit Targets Low-cost Facial Recognition Systems

iWave Systems i.MX8M Mini Board is a development platform based on an update versions of the company’s iW-RainboW-G34M-SM i.MX 8M Mini system-on-module and designed specifically for low-cost facial recognition systems thanks to NXP eIQ ML software, and MIPI display and camera. iWave Systems i.MX8M Mini (aka iW-RainboW-G34D) specifications: SoM SoC – NXP i.MX8M Mini Q/QL/D/DL/S/SL with up to 4x Cortex-A53 cores,  1x Cortex-M4F real-time core, Vivante 3D and 2D GPUs System Memory – 1GB LPDDR4 (Expandable up to 4GB) Storage – 8GB eMMC Flash (Expandable), optional 2MB QSPI Flash optional Micro SD slot Wireless – Dual-band 802.11a/b/g/n/ac WiFi 5 and Bluetooth 5.0. PMIC – BD71847AMWV i.MX8M SODIMM Carrier Board Storage – MicroSD slot Display I/F – MIPI DSI display connector Camera I/F – MIPI CSI camera connector Audio – Audio codec, 3.5mm Line In/Out jack Networking – Up to 2x Gigabit Ethernet ports (One is Optional) USB – 2x USB 2.0 Host ports, 1x USB 2.0 device port Debugging – …

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4K Vision Edge Computing Platform Features Xilinx Zynq UltraScale+ ZU3EG MPSoC

Last year, MyIR Tech introduced MYD-CZU3EG development board powered by a Xilinx Zynq UltraScale+ ZU3EG MPSoC with Arm Cortex-A53 cores and FPGA fabric designed for applications such as cloud computing, machine vision, flight navigation, and other complex embedded applications. The company has now announced another Zynq Ultrascale+ ZU3EG based platform dedicated to machine vision. The VECP Starter Kit (Vision Edge Computing Platform) is comprised of MYD-CZU3EG-ISP development board fitted with the company’s MYC-CZU3EG Zynq UltraScale+ MPSoC CPU module, a fansink, and a SONY IMX334 4K camera sensor. MYD-CZU3EG-ISP development board specification: MYC-CZU3EG SoM MPSoC – Xilinx Zynq UltraScale+ XCZU3EG-1SFVC784E (ZU3EG, 784 Pin Package) MPSoC with quad-core Arm Cortex-A53 processor @ 1.2 GHz, dual-core Cortex-R5 processor @ 600 MHz, Arm Mali-400MP2 GPU, and 16nm FinFET+ FPGA fabric (154K logic cells, 7.6 Mb memory, 728 DSP slices) System Memory – 4GB DDR4 @ 2,400MHz Storage – 4GB eMMC Flash, 128MB QSPI Flash PS unit (Processing Subsystem i.e. Arm Cortex cores) Storage – …

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Boardcon RK1808 SBC Targets Smart Audio & Computer Vision Applications

Rockchip RK1808 neural network processing unit was initially an IP Block inside RK3399Pro, but the company eventually launched RK1808 Cortex-A35 processor as a standalone solution now providing up to 3.0 TOPS for AI inferencing in modules, USB sticks, and development kits. Boardcon offers another option with EM1808, a Rockchip RK1808 SBC equipped with the processor. The board should be suitable for two main types of AI applications, namely smart audio applications thanks to four audio ports, speaker header, & an onboard 4-mic array, and computer vision with MIPI CSI & DSI interfaces. Boardcon EM1808 board is comprised of a baseboard and CPU module with the following overall specifications: SoC – Rockchip RK1808 dual Cortex-A35 processor up to 1.6GHz with 3.0 TOPS (for INT8) NPU, VPU supporting H.264 1080p60 decode, 1080p30 encode System Memory- 2GB LPDDR3 Storage – 8GB eMMC flash, MicroSD slot, M.2 NVMe SSD interface Display I/F – 26-pin MIPI DSI header Camera I/F – 26-pin MIPI CSI header …

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ADLink Launches Vizi-AI Development Starter Kit for Industrial Machine Vision & Artificial Intelligence

ADLINK has recently launched Vizi-AI development starter kit for industrial machine vision and artificial intelligence (AI) at the edge in collaboration with Intel and Arrow Electronics. Vizi-AI is comprised of a carrier board that looks to be the same as used in the company’s I-Pi SMARC development kit equipped with an Intel Movidius Myriad X VPU and combined with LEC-AL Intel Atom Apollo Lake SMARC computer module. Vizi-AI SBC Let’s have a look at the hardware features and specifications of Vizi-AI SBC (aka VIZI-AI LEC-AL-E3940-AI-4G-32G): SoC – Intel Atom x5-E3940 quad-core Apollo Lake-I processor @ up to 1.6 / 1.8 GHz (Turbo) with 12EU Intel HD Graphics 500; 9.5W TDP System Memory – 4GB LPDDR4 (Option up to 8GB) Storage – 1x MicroSD card slot AI Accelerator – Intel Movidius Myriad-X VPU (Vision Processing Unit) Video – 1x HDMI port, single-channel LVDS/eDP interface via flat cable Audio – On-carrier audio codec; stereo audio jack; digital audio via HDMI Networking –  …

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