MagikEye Developer Kit enables 120 fps 3D sensing on Raspberry Pi

Raspberry Pi 3D Sensing development kit

MagikEye ILT001 developer kit (DK-ILT001) is a low-latency 3D sensing kit that connects to the Raspberry Pi’s MIPI CSI camera connector and features the company’s Invertible Light Technology (ILT) module with an infrared laser and a CMOS image sensor. The company says a “unique algorithm” developed in-house can generate 3D point cloud datasets acquired at high speeds (up to 120 fps) and with very low latency using simple hardware configuration. The kit targets researchers, students, and hobbyists working on machine vision, robotics, automated carriers, and other projects that can benefit from low-latency 3D sensing. MagikEye DK-ILT001 kit key features and specifications 850nm infrared light laser CMOS image sensor Range up to 1.5 meters (15 to 80 cm recommended) Compatibility – Raspberry Pi Zero W/3B/3B+/4 Power Supply – 3.3V (via MIPI Interface on Raspberry Pi) Power Consumption – 0.6W (average) Dimensions – 44 x 24 x 16 mm (within enclosure) Weight […]

Vecow EAC-2000 fanless embedded system is powered by NVIDIA Jetson Xavier NX

Vecow EAC-2000 fanless embedded-system-NVIDIA Jetson Xavier NX

Vecow  Vecow EAC-2000 series fanless embedded system features NVIDIA Jetson Xavier NX module for the deployment of AI vision and industrial applications including traffic vision, intelligent surveillance, auto optical inspection, Smart Factory, AMR/AGV, and other AIoT/Industry 4.0 applications. The computer comes with up to four Fakra-Z connectors to connect GMSL cameras,  as well as four Gigabit Ethernet ports, two of which with PoE+ support, takes 9V to 50V wide range DC input, and can operate in a wide temperature range from -25°C to 70°C. Two models part of Vecow EAC-2000 embedded system family are currently offered with the following specifications: System-on-Module – NVIDIA Jetson Xavier NX with CPU – 6-core NVIDIA Carmel ARM v8.2 64-bit CPU GPU -384-core NVIDIA Volta GPU with 48 Tensor Cores DL Accelerator -2x NVDLA Engines System Memory – 8GB LPDDR4x DRAM Storage – 16GB eMMC flash Storage – M.2 Key M Socket (2280) for SSD, […]

Jevois Pro small AI camera with Amlogic A311D SoC offers up to 13 TOPS (Crowdfunding)

JeVois Pro

Jevois-A33 smart camera was a tiny Linux camera with Allwinner A33 processor designed for computer vision applications and announced in 2016. I had the opportunity to review the computer vision camera the following year, and it was fun to use to learn about computer vision with many examples, but since it relied on the CPU for processing, it would not have been suitable for all projects due to the lag, as for example, object detection took 500ms and Yolo V3 around 3 seconds per inference. But time has passed, and great progress has been made in the computer vision and AI fields with the tasks now usually handled by a built-in NPU, or an AI accelerator card. So JeVois Pro deep learning camera has just been launched with an Amlogic A311D processor featuring a 5 TOPS NPU, and support for up to 13 TOPS via a Myriad X or Google […]

NVIDIA TAO Transfer Learning Toolkit (TLT) 3.0 released with pre-trained models

NVIDIA TAO Transfer Learning Toolkit

NVIDIA first introduced the TAO (Train, Adapt and Optimize) framework to eases AI model training on NVIDIA GPU’s as well as NVIDIA Jetson embedded platforms last April during GTC 2021. The company has now announced the release of the third version of the TAO Transfer Learning Toolkit (TLT 3.0) together with some new pre-trained models at CVPR 2021 (2021 Conference on Computer Vision and Pattern Recognition). The newly released pre-trained models are applicable to computer vision and conversational AI, and NVIDIA claims the release provides a set of powerful productivity features that boost AI development by up to 10 times. Highlights of TAO Transfer Learning Toolkit 3.0 Various computer vision pre-trained models for Computer vision: Body Pose estimation model that supports real-time inference on edge with 9x faster inference performance than the OpenPose model. Emotion recognition Facial landmark License plate detection and recognition Heart rate estimation Gesture recognition Gaze estimation […]

Modelplace.AI is an app store for OpenCV compatible AI models

modelplace.ai

OpenCV open-source computer vision library is used in a wide variety of projects and products, and last year, the community also launched the OpenCV AI Kit (OAK) Myriad X-based hardware solution for computer vision. However there’s a learning curve to use the library, especially in combination with artificial intelligence models, and it can be challenging and time-consuming to newcomers. So in order to broaden the reach of the solution, OpenCV has now introduced Modelplace.AI, an app store/marketplace for AI models working with the OpenCV library. The AI model marketplace is a store and try-before-you-buy service for artificial intelligence models, many of which are certified to work with the OpenCV AI Kit. There are currently over 40 models for detection (e.g. person, pedestrian…), classification, segmentation (e.g. extraction of objects from a scene), pose estimation, people counting, text detection, tracking, and more. Right now all models are free, but developers will be […]

OpenMV PureThermal STM32H7 board overlays thermal map on RGB image

OpenMV PureThermal Camera

We’ve been writing about OpenMV open-source camera boards programmable with MicroPython at least since 2015, with the latest model OpenMV Cam H7 based on STM32H7 Cortex-M7 microcontroller introduced in 2018. But the company has now gone a step further with OpenMV PureThermal board equipped with a more powerful STM32H7 dual-core Arm Cortex-M7/M4microcontroller, and supporting FLIR Lepton 2 to 3.5 thermal imagers, allowing the system to overlay the thermal map on top of the image like an augmented reality app would do. It can do so on the integrated LCD display or on an HDMI display. OpenMV PureThermal features & specifications: MCU – STMicro STM32H7 Arm Cortex-M7 @ 480 MHz) and Cortex-M4 @ 240 MHz microcontroller Memory – 64MB SDRAM Storage – 32 MB of QSPI flash for the firmware, a microSD card slot for saving pictures and machine vision assets Display 800×480 touch Screen LCD DVI out for driving an […]

NEON-2000-JNX series AI Camera Features NVIDIA Jetson Xavier NX SOM for AIoT Applications

NEON-2000-JNX series AI camera

Machine vision applications highlight the complexity of implementation due to the requirement of interfacing several devices. These devices include image sensor modules, cables, GPU modules, and memory units, thus increasing the time for development and deployment. ADLINK’s NEON-2000-JNX series AI camera aims to simplify the deployment of edge machine vision and AIoT use cases. NEON-2000-JNX series AI camera comes with an inbuilt ADLINK’s new edge vision analytics software known as the EVA SDK. The software reduces the time in designing and creating proofs-of-concept, which leads to quicker deployment of applications. Users get a wide range of options for selecting field-ready “application plug-ins and ADLINK-optimized AI models”. This ensures the quality of vision AI and eases the building of use cases with lesser software code and programs. Additionally, the preview function allows quicker verification of AI Inference flow. We saw the launch of NVIDIA’s Jetson Xavier NX SOM in April 2020 […]

Imago “VisionAI” Smart AI Camera supports Tensorflow Lite & AutoML Vision Edge

Imago VisionAI Smart AI Camera

Imago Technologies GmbH “VisionAI” is a programmable Smart AI camera that combines a quad-core Cortex-A53 processor @ 1.8 GHz together with Google Edge TPU, and designed for embedded image processing applications in the fields of AI, Deep Learning, and Machine Learning. The smart camera supports TensorFlow Lite and AutoML Vision Edge frameworks, and is suited for tasks such as pattern recognition, classification, anomaly or defect detection in inspection applications, code reading, and other machine vision applications. Imago VisionAI (VisionSensor PV3 AI) camera specifications: SoC – Unnamed quad-core Arm Cortex-A53 processor @ 1.8 GHz (likely NXP i.MX 8M Mini) AI Accelerator – Google Edge TPU with up to 4 TOPS of AI processing power System Memory – 2 GB DDR4 RAM Storage – MicroSD card up to 32GB Connectivity – Gigabit Ethernet M12 connector Camera 1/1.8” 5MP mono or color CMOS sensor with 2560 × 1936 pixels resolution, up to 65 […]