DeGirum ORCA M.2 and USB Edge AI accelerators support Tensorflow Lite and ONNX model formats

Degirum ORCA M.2 PCIe module

I’ve just come across an Atom-based Edge AI server offered with a range of AI accelerator modules namely the Hailo-8, Blaize P1600, Degirum ORCA, and MemryX MX3. I had never heard about the last two, and we may cover the MemryX module a little later, but today, I’ll have a closer at the Degirum ORCA chip and M.2 PCIe module. The DeGirum ORCA is offered as an ASIC, an M.2 2242 or 2280 PCIe module, or (soon) a USB module and supports TensorFlow Lite and ONNX model formats and INT8 and Float32 ML precision. They were announced in September 2023, and have already been tested in a range of mini PCs and embedded box PCs from Intel (NUC), AAEON, GIGABYTE, BESSTAR, and Seeed Studio (reComputer). DeGirum ORCA specifications: Supported ML Model Formats – ONNX, TFLite Supported ML Model Precision – Float32, Int8 DRAM Interface – Optional 1GB, 2GB, or 4GB […]

SolidRun launches Hailo-15 SOM with up to 20 TOPS AI vision processor

SolidRun Hailo 15H Powered Edge AI System on Module

In March last year, we saw Hailo introduce their quad-core Cortex-A53-based Hailo-15 AI Vision processor. The processor features an advanced computer vision engine and can deliver up to 20 TOPS of processing power. However, after that initial release, we didn’t find it in any commercial products with the SoC. But in a recent development, SolidRun has released a SOM that not only features the Hailo-15 SoC but also integrates up to 8GB LPDDR4 RAM and 256GB eMMC storage along with dual camera support with H.265/4 Video Encoder. This is not the first SOM that SolidRun has released. Previously, we wrote about the SolidRun RZ/G2LC SOM, and before that, SolidRun launched the LX2-Lite SOM along with the ClearFog LX2-Lite dev board. Last month, they released their first COM Express module based on the Ryzen V3000 Series APU. Specification of SolidRun’s Hailo-15 SOM: SoC – Hailo-15 with 4 x Cortex A53 @ 1.3GHz; […]

Edge Impulse machine learning platform adds support for NVIDIA TAO Toolkit and Omniverse

Edge Impulse NVIDIA TAO Models

Edge Impulse machine learning platform for edge devices has released a new suite of tools developed on NVIDIA TAO Toolkit and Omniverse that brings new AI models to entry-level hardware based on Arm Cortex-A processors, Arm Cortex-M microcontrollers, or Arm Ethos-U NPUs. By combining Edge Impulse and NVIDIA TAO Toolkit, engineers can create computer vision models that can be deployed to edge-optimized hardware such as NXP I.MX RT1170, Alif E3, STMicro STM32H747AI, and Renesas CK-RA8D1. The Edge Impulse platform allows users to provide their own custom data with GPU-trained NVIDIA TAO models such as YOLO and RetinaNet, and optimize them for deployment on edge devices with or without AI accelerators. NVIDIA and Edge Impulse claim this new solution enables the deployment of large-scale NVIDIA models to Arm-based devices, and right now the following object detection and image classification tasks are available: RetinaNet, YOLOv3, YOLOv4, SSD, and image classification. You can […]

Waveshare Jetson Nano powered mini-computer features a sturdy metal case

Waveshare Launches Jetson Nano Mini Computer

Waveshare has launched the Jetson Nano Mini Kit A, a mini-computer kit powered by Jetson Nano. This kit features the Jetson Nano Module, a cooling fan, and a WiFi module, all inside a sturdy metal case. The mini-computer is built around Nvidia’s Jetson platform housing the Jetson Nano module and features multiple interfaces, including USB connectors, an Ethernet port, an HDMI port, CSI, GPIO, I2C, and RS485 interfaces. It also has an onboard M.2 B KEY slot for installing either a WiFi or 4G module and is compatible with TensorFlow, and PyTorch which makes it well-suited for various AI applications. Waveshare Mini-Computer Specification: GPU – NVIDIA Maxwell  architecture with 128 NVIDIA CUDA cores CPU – Quad-core ARM Cortex-A57 processor @ 1.43 GHz Memory – 4 GB 64-bit LPDDR4 1600 MHz; 25.6 GB/s bandwidth Storage – 16 GB eMMC 5.1 Flash Storage, microSD Card Slot Display Output – HDMI interface with […]

Arducam KingKong – A Raspberry Pi CM4-based Edge AI camera with global shutter sensor, Myriad X AI accelerator

Arducam KingKong

ArduCam KingKong is a Smart Edge AI camera based on the Raspberry Pi CM4 and system-on-module based on Intel Myriad X AI accelerator that follows the Raspberry Pi 5-powered Arducam PiINSIGHT camera introduced at the beginning of the year. The new product launch aims to provide a complete Raspberry Pi-based camera rather than an accessory for the Raspberry Pi 4/5. Smart cameras built around the Raspberry Pi CM4 are not new as we previously covered the EDATEC ED-AIC2020 IP67-rated industrial AI Edge camera and the StereoPi v2 stereoscopic camera used to create 3D video and 3D depth maps. The ArduCam KingKong adds another option suitable for computer vision applications with an AR0234 global shutter module, PoE support, and a CNC metal enclosure. ArduCam KingKong specifications: SoM – Raspberry Pi Compute Module 4 (CM4) by default CM4104000 Wireless 4GB RAM Lite (0GB eMMC). AI accelerator – Luxonis OAK SOM BW1099 based on Intel […]

$16 Grove Vision AI V2 module features WiseEye2 HX6538 Arm Cortex-M55 & Ethos-U55 AI microcontroller

Grove Vision AI V2 XIAO ESP32-C3 OV5647 camera

Seeed Studio’s Grove Vision AI V2 module is based on the HiMax WiseEye2 HX6538 dual-core Cortex-M55 AI microcontroller with an Arm Ethos-U55 microNPU and features a MIPI CSI connector for an OV5647 camera. It is designed for AI computer vision applications using TensorFlow and PyTorch frameworks and connects to hosts such as Raspberry Pi SBCs, ESP32 IoT boards, Arduino, and other maker boards over I2C. We tested the previous generation Grove Vision AI module based on the 400 MHz HX6537-A DSP-based AI accelerator using the SenseCAP K1100 sensor prototype kit with LoRaWAN connectivity, and managed to have the kit perform face detection and send the data over LoRaWAN. The Grove Vision AI V2 builds on that but with a modern Arm MCU core and more powerful AI accelerator that can run models such as Mobilenet V1/V2, Efficientnet-lite, and Yolo v5 & v8 using the SenseCraft low-code/no-code platform. Grove Vision AI […]

Firefly CT36L AI Smart Camera Features Rockchip RV1106G2 with 0.5 TOPS NPU, 100Mbps Ethernet with PoE support

CT36L AI Smart Camera with POE

Firefly CT36L AI Smart Camera (PoE) features a Rockchip RV1106G2 CPU with 0.5 TOPS NPU, a 5-megapixel ISP, and a 3-megapixel HD lens. It supports 100Mbps Ethernet with PoE and includes advanced image enhancements like HDR, WDR, and noise reduction, all while maintaining low power consumption and high image integration. We’ve previously explored various AI cameras such as Tokay Lite, EDATEC ED-AIC2020, ThinkCore TC-RV1126, Orbbec Persee+, M5Stack UnitV2 among others. Feel free to check them out for more information. Firefly CT36L AI Smart Camera (PoE) specifications: CPU – Rockchip RV1106G2 Arm Cortex-A7 @ 1.2GHz, with Neon and FPU NPU – 0.5 TOPS, supports INT4/INT8/INT16, TensorFlow/MXNet/PyTorch/Caffe/Onnx NN ISP – 5MP high-performance, HDR, WDR, 3DNR, 2DNR, sharpening, defogging, fisheye and gamma correction, feature detection VPU – 3072×1728 (5M) @ 30fps H.265/H.264 encoding, 16M@60FPS JPEG snapshot RAM – 128MB DDR3 built-in Storage – 16MB SPI Flash built-in Camera specifications: Type – Color Camera Image Sensor – SC3336 CMOS Size […]

Tokay Lite – A battery-powered no-code AI camera based on ESP32-S3 WiSoC (Crowdfunding)

Tokay Lite ESP32-S3 no-code AI camera

Maxlab’s Tokay Lite is an OHSWA-certified AI camera based on ESP32-S3 WiFI and Bluetooth SoC that can be used for computer vision (e.g. facial recognition & detection) and robotics applications without the need to know programming languages since a web interface is used for configuration. The WiFi and Bluetooth AI camera also features night vision with four IR LEDs, an IR cut filter, light and PIR motion sensors, a 20-pin expansion connector with SPI and UART, support for an external RTC, and can take power from USB-C or a LiPo battery. Tokay Lite specifications: Wireless module ESP32-S3-WROOM-1 MCU – ESP32-S3 dual-core LX7 microprocessor @ up to 240 MHz with Vector extension for machine learning, 512 KB SRAM Memory – 8MB PSRAM Storage – 8MB SPI flash Connectivity – WiFi 4 and Bluetooth 5 with LE/Mesh PCB antenna Certifications – FCC/CE certification Camera OV2640 camera sensor (replaceable) via DVP interface Image Capabilities: […]