ZED Depth and Motion Tracking Camera Supports NVIDIA Jetson Nano Board

ZED depth camera Jetson Nano

When NVIDIA launched their low cost Jetson Nano development board earlier this week, one reader asked whether it would support binocular depth mapping. It turns out Stereo Labs has updated the SDK (Software Development Kit) for the ZED depth and motion tracking camera in order to support the latest NVIDIA developer kit. Jetson Nano can manage depth and positional tracking at 30 fps in PERFORMANCE mode with 720p resolution, and while the more powerful and expensive Jetson TX2 achieves doubles the performance at 60 fps, it does so at a much higher cost. ZED depth and motion tracking camera specifications: Video 2.2K @ 15 fps (4416×1242 resolution) 1080p @ 30 fps (3840×1080 resolution) 720p @ 60 fps (2560×720 resolution) WVGA @ 100 fps (1344×376 resolution) Depth Resolution – Same as selected video resolution Range – 0.5 to 20 m Format – 32-bits Stereo Baseline – 120 mm Motion 6-axis Pose Accuracy Position – +/- 1mm Orientation – 0.1° Frequency – …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Inforce 6560 Snapdragon 660 Pico-ITX SBC Comes with 3 MIPI Camera Connectors

Inforce 6560

Inforce Computing has launched yet another Snapdragon-based single board computer with their Inforce 6560 SBC powered by Qualcomm Snapdragon 660 processor with stereoscopic depth sensing and deep learning capabilities made possible thanks to three MIPI camera connectors. The board also comes with to 3GB LPDDR4 RAM, 32GB flash, HDMI and MIPI DSI video outputs, Gigabit Ethernet, a wireless module, USB ports, sensors, and more. Inforce 6560 specifications: SoC – Qualcomm Snapdragon 660 (SDA660) with 8x Kryo ARMv8 compliant 64-bit CPUs arranged in two dual-clusters, running at 2.2GHz (Gold) and 1.8GHz (Silver) each, Adreno 512 GPU, Hexagon 680 DSP with dual-Hexagon vector processor (HVX-512) @ 787MHz for low-power audio and computer vision processing, Spectra 160 camera (dual) Image Signal Processors (ISPs) System Memory –     3GB onboard LPDDR4 RAM Storage – 32GB eMMC flash, 1x µSD card v3.0 socket Video Output / Display Interface HDMI V1.3a FullHD @ 60fps port 4-lane MIPI-DSI with FullHD+ capability UltraHD (4K) display on USB-C port Audio – …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Adding Machine Learning based Image Processing to your Embedded Product

Convert model tensorflow runtime to NNEF

CNXSoft: This is a guest post by Greg Lytle, V.P. Engineering, Au-Zone Technologies. Au-Zone Technologies is part of the Toradex Partner Network. Object detection and classification on a low-power Arm SoC Machine learning techniques have proven to be very effective for a wide range of image processing and classification tasks. While many embedded IoT systems deployed to date have leveraged connected cloud-based resources for machine learning, there is a growing trend to implement this processing at the edge. Selecting the appropriate system components and tools to implement this image processing at the edge lowers the effort, time, and risk of these designs. This is illustrated with an example implementation that detects and classifies different pasta types on a moving conveyor belt. Example Use Case For this example, we will consider the problem of detecting and classifying different objects on a conveyor belt. We have selected commercial pasta as an example but this general technique can be applied to most other …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Intel RealSense Tracking Camera T265 is Designed for Autonomous Devices

Intel RealSense Tracking Camera T265

Intel has just launched another smart camera with RealSense Tracking Camera T265 powered by the company’s Myriad 2 VPU (Vision Processing Unit) also found in the first Neural Compute Stick, and designed for autonomous robots, drones, and augmented/virtual reality applications. The T265 camera is said to use proprietary visual inertial odometry simultaneous localization and mapping (V-SLAM) technology “delivering high-performance guidance and navigation”. Intel RealSense tracking camera T265 hardware specifications: VPU – Intel Movidius Myriad 2 vision processing unit with 12 VLIW 128-bit vector SHAVE processors optimized to run V‑SLAM at low power Cameras – 2x Omnivision OV9282 high-speed image sensors with Fisheye lenses for a combined 163±5° FOV; infrared cut filter Sensor – Bosch BMI055 6-axis IMU (Inertial Measurement Unit) to measure rotation and acceleration of the device USB – 1x USB 3.1 Gen 1 Micro B port to transfer pose data, or pose + image data. Dimensions – 108 x 24.5 x 12.5 mm; 2x M3 0.5mm pitch mounting sockets (50 mm apart) The V-SLAM …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Intel RealSense D435i Stereo Depth Camera Supports 6 Degrees of Freedom Tracking

RealSense D435i Camera

First unveiled in CES 2014, Intel RealSense Technology was introduced for perceptual computing application with hardware such as 3D sensing cameras, as well Nuance Dragon Assistant voice technology. Since then the company release various 3D sensing camera models and kits such as Realsense R200 Depth Camera robotics development kit, and just announced the new RealSense D435i stereo depth camera which adds 6 DoF (Degrees of Freedom) tracking over D435 model thanks to an inertial measurement unit (IMU). Intel RealSense Depth Camera D435i key features and specifications: Intel RealSense Vision Processor D4 – Purpose-built ASIC designed to deliver stereo depth data at up to 90fps at VGA resolutions or up to 1280×720 resolution at 30fps Intel RealSense module D430 – Depth camera imaging sub-system featuring a wide field of view (91.2 horizontal x 65.5 degrees vertical), global shutter stereo image sensors and an IR projector Depth Technology – Active IR stereo Inertial Measurement Unit (IMU) Image Sensor Technology – Global Shutter; …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

$50 Kendryte KD233 Board Features K210 Dual Core RISC-V SoC

Kendryte KD223 RISC-V Board

RISC-V is talked about a lot, and we’re started to see a few development boards coming to market, or at least being announced with some based on SiFive processors such as HiFive Unleashed or Arduino Cinque, as well as other like GAPUINO GAP8 for low power A.I. applications. The Arduino board is not for sale yet, and HiFive Unleashed and GAPUINO GAP8 are fairly expensive at $999 and $229. Kendryte KD233 board is another RISC-V development board, based on  Kendryte K210 dual core 64-bit RISC-V processor designed for machine vision and “machine hearing”. The board goes for $49.99 on AnalogLamb. Kendryte KD233 board specifications: SoC – Kendryte K210 dual core 64-bit RISC-V processor, KPU  Convolutional Neural Network (CNN) hardware accelerator, APU audio hardware accelerator, 6MiB of on-chip general-purpose SRAM memory and 2MiB of on-chip AI SRAM memory, AXI ROM to load user program from SPI flash Storage – 128 Mbit SPI NOR flash, micro SD card slot Display – TFT …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

iBASE Introduces MI988 Ryzen Embedded V1000 Mini-ITX Motherboard

iBase MI988 Mini ITX Motherboard

iBASE has recently announced the MI988 Mini-ITX motherboard based on the latest AMD Ryzen Embedded V1000 processor family. The motherboard is equipped with two DDR4-2666 SO-DIMM slots that support up to 32GB ECC memory, M.2 NVMEe storage (NVMe), two Gigabit Ethernet ports, and various display options. iBASE MI988 motherboard specifications: SoC – AMD Ryzen Embedded V1000 processor with AMD Radeon Vega GPU System Memory – 2x DDR4-2666 SO-DIMM, supports ECC, up to 32GB Storage – 1x M.2 SSD (NVMe), 2x SATA III Display Interfaces 1x HDMI 2.0a, 1x DisplayPort 1.4 1x eDP or 1x 24-bit dual channel LVDS Audio – Built-in HD audio w/ALC662 codec for 5.1 channel; 3x 3.5mm audio jacks Connectivity – 2x RJ45 Gigabit Ethernet connectors via 2x Intel I211AT USB – 2x USB 3.1 Gen2 (10Gbps) on board, 2x USB 3.1 Gen1 (5Gbps) on board Serial – 2x RS232/422/485 (Jumperless selection), 4x RS232 Expansion Slots 1x PCI-E(x8), 1x Mini PCI-E, 1x M.2 (M-key, type:2230) 8x Digital …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

OpenMV Cam H7 MicroPython Machine Vision Camera Launched on Kickstarter

OpenMV CAM H7

OpenMV team has launched an upgrade to their popular OpenMV CAM M7 machine vision camera, with OpenMV CAM H7 replacing the STMicro STM32F7 micro-controller by a more powerful STM32H7 MCU clocked at up to 400 MHz. Beside having twice the processing power, the new camera board also features removable camera modules for thermal vision and global shutter support. OpenMV CAM H7 camera board specifications: MCU – STMicro STM32H743VI Arm Cortex M7 microcontroller @ up to 400 MHz with 1MB RAM, 2MB flash. External Storage – micro SD card socket supporting up to 100 Mbps read/write to record videos and store machine vision assets. Camera modules Omnivision OV7725 image sensor (default) capable of taking 640×480 8-bit Grayscale /  16-bit RGB565 images at 60 FPS when the resolution is above 320×240 and 120 FPS when it is below; 2.8mm lens on a standard M12 lens mount Optional Global Shutter camera module to capture high quality grayscale images not affected by motion blur Optional …

Support CNX Software – Donate via PayPal or become a Patron on Patreon