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December 3, 2023 by Debashis Das - No Comments

OpenMV CAM RT1062 camera for machine vision is programmable with MicroPython

Following the success of the OpenMV Cam H7 and the original OpenMV VGA Camera, OpenMV recently launched the OpenMV CAM RT1062 powered by NXP’s RT1060 processor. This new camera module integrates a range of features, including a high-speed USB-C (480Mbps) interface, an accelerometer, and a LiPo connector for portability. Similar to its predecessor, this camera module also features a removable camera system, and it is built around the OV5640 image sensor which is more powerful in terms of resolution and versatility. However, the previous Omnivision OV7725 sensor, used in the OpenMV Cam H7 has a far superior frame rate and low-light performance. OpenMV provides a Generic Python Interface Library for USB and WiFi Comms and an Arduino Interface Library for I2C, SPI, CAN, and UART Comms which can be used to interface your OpenMV Cam to other systems. To program the board, you can use MicroPython 3 with OpenMV IDE, […]

October 24, 2023October 24, 2023 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

CanMV-K230 AI development board features Kendryte K230 dual-core 64-bit RISC-V processor

CanMV-K230 is a credit card-sized development board for AI and computer vision applications based on the Kendryte K230 dual-core C908 64-bit RISC-V processor with built-in KPU (Knowledge Process Unit) and various interfaces such as MIPI CSI inputs and Ethernet. The first Kendryte RISC-V AI processor was launched in 2018 with the K210 which I tested with the Grove AI HAT and Maixduino board and found fun to experiment with, but noted that performance was limited. Since then the company introduced the K510 mid-range AI processor with a more powerful 3 TOPS AI accelerator, and the K230 entry-level successor to the K210 – which was planned for 2022 in a 2021 roadmap – has now just been launched and integrated into the CanMV-K230 development board. CanMV-K230 specifications: SoC – Kendryte K230 CPU 64-bit RISC-V processor @ 1.6GHz with RISC-V Vector Extension 1.0, FPU 64-bit RISC-V processor @ 800MHz with support for […]

October 17, 2023October 17, 2023 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Hummingboard 8P Edge AI SBC combines NXP i.MX 8M Plus SoC with Hailo-8 AI accelerator

Hummingboard 8P Edge AI Pico-ITX SBC combines an NXP i.MX 8M Plus processor – itself with a 2.3 TOPS NPU – with the 26 TOPS Hailo-8 AI accelerator for edge AI applications such as smart cameras and automated optical inspection. The compact board comes with up to 8GB RAM, up to 128GB eMMC flash, two gigabit Ethernet ports including one with PoE, WiFi 5, a MIPI camera interface, HDMI and micro HDMI ports, two USB 3.0 ports, and more. Hummingboard 8P Edge AI specifications: SoC – NXP i.MX 8M Plus quad-core Cortex-A53 @ up to 1.8 GHz with Arm Cortex-M7 @ up to 800 MHz, Vivante GC7000UL 3D GPU, Vivante GC520L 2D GPU, 2.3 TOPS NPU System Memory – Up to 8GB LPDDR4 Storage – Up to 128GB eMMC flash, microSD card slot AI accelerator – M.2 Hailo-8 module delivering up to 26 TOPS Video Output – HDMI and Micro […]

October 3, 2023October 2, 2023 by Jean-Luc Aufranc (CNXSoft) - No Comments

Renesas RZ/G2L and RZ/V2L SMARC 2.1 system-on-modules target HMI and Edge AI applications

SMARC 2.1 Evaluation Kit for Renesas RZ/G2L and RZ/V2L

ARIES Embedded has recently launched two SMARC-compliant MRZG2LS and MRZV2LS system-on-modules (SoM) powered by respectively a Renesas RZ/G2L dual-core Cortex-A55/M33 microprocessor with Arm Mali-G31 GPU and H.264 video codec (H.264) and a similar Renesas RZ/V2L MPU adding a built-in ‘DRP-AI’ AI accelerator for vision applications. Those are the first SMARC modules from the company and they are well-suited for applications such as entry-class industrial human machine interfaces (HMIs), embedded vision, edge artificial intelligence (edge-AI), real-time control, industrial Ethernet connectivity, and embedded devices with video capabilities. ARIES Embedded MRZG2LS and MRZV2LS key features and specifications: SoC – Renesas RZ/G2L or GZ-V2L with Application CPU – Single or dual Arm Cortex-A55 up to 1.2GHz Real-time core -Arm Cortex-M33 GPU – Arm Mali-G31 VPU – H.264 codec AI accelerator – DRP-AI on Renesas RZ/V2l only (MRZV2L SoM) System Memory – 512MB to 4GB DDR4 RAM Storage – SPI NOR flash, 4GB to 64GB […]

September 17, 2023September 17, 2023 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Review of CM4 XGO Lite – A Raspberry Pi CM4 based smart robot dog with a robotic arm

The CM4 XGO Lite is a smart robot dog based on Raspberry Pi CM4 system-on-module and designed to learn to program using Blockly, Python, and ROS. This four-legged robot also happens to feature a 3-joint robot arm and a robot gripper installed on the back that can pick up light objects. The Raspberry Pi CM4 module drives the LCD screen and camera and performs AI and computer vision processing, while each joint is controlled with a servo motor, and a 6-axis tilt sensor ensures stable walking and movement. We’ve already discussed the capabilities of the CM4 XGO Lite, aka XGO Lite 2, when it was announced earlier this year, so we’re not going to go into details here, but some of the highlights include support for faster AI edge computing applications such as face detection and object classification, omnidirectional movement, six-dimensional posture control, posture stability, and multiple motion gaits. Robot […]

September 15, 2023September 18, 2023 by Jean-Luc Aufranc (CNXSoft) - No Comments

Cadence Neo NPU IP scales from 8 GOPS to 80 TOPS

Cadence Neo NPU (Neural Processing Unit) IP delivers 8 GOPS to 80 TOPS in single core configuration and can be scaled to multicore configuration for hundreds of TOPS. The company says the Neo NPUs deliver high AI performance and energy efficiency for optimal PPA (Power, Performance, Area) and cost points for next-generation AI SoCs for intelligent sensors, IoT, audio/vision, hearables/wearables, mobile vision/voice AI, AR/VR and ADAS. Some highlights of the new Neo NPU IP include: Scalability – Single-core solution is scalable from 8 GOPS to 80 TOPS, with further extension to hundreds of TOPS with multicore Supports 256 to 32K MACs per cycle to allow SoC architects to meet power, performance, and area (PPA) tradeoffs Works with DSPs, general-purpose microcontrollers, and application processors Support for Int4, Int8, Int16, and FP16 data types for CNN, RNN and transformer-based networks. Up to 20x higher performance than the first-generation Cadence AI IP, with […]

September 10, 2023September 9, 2023 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Andes launches AX45MPV RISC-V CPU core with Vector Extension 1.0

Andes Technology has recently announced the general availability of the AndesCore AX45MPV RISC-V CPU which builds upon the AX45MP multicore processor and adds RISC-V Vector Extension 1.0. Equipped with RISC-V vector processing and parallel execution capability, the new RISC-V CPU core targets SoCs processing large amounts of data for applications such as ADAS, AI inference and training, AR/VR, multimedia, robotics, and signal processing. AX45MPV key features and specifications: 64-bit in-order dual-issue 8-stage CPU core with up to 1024-bit Vector Processing Unit (VPU) – compliant with RISC-V V-extension (RVV) 1.0 + custom extensions Supports clusters of up to 8 cores L2 cache and coherence support High bandwidth vector local memory (HVM) AndeStar V5 Instruction Set Architecture (ISA) Compliant with RISC-V GCBPV extensions Andes performance extension Andes CoDense extension for further compaction of code size Separately licensable Andes Custom Extension (ACE) for customized scalar and vector instruction 64-bit architecture for memory space […]

August 21, 2023August 21, 2023 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

MediaPipe for Raspberry Pi released – No-code/low-code on-device machine learning solutions

Google has just released MediaPipe Solutions for no-code/low-code on-device machine learning for the Raspberry Pi (and an iOS SDK) following the official release in May for Android, web, and Python, but it’s been years in the making as we first wrote about the MediaPipe project back in December 2019. The Raspberry Pi port is an update to the Python SDK and supports audio classification, face landmark detection, object detection, and various natural language processing tasks. MediaPipe Solutions consists of three components: MediaPipe Tasks (low-code) to create and deploy custom end-to-end ML solution pipelines using cross-platform APIs and libraries MediaPipe Model Maker (low-code) to create custom ML models MediaPipe Studio (no-code) webpage to create, evaluate, debug, benchmark, prototype, and deploy production-level solutions. You can try it out directly in your web browser at least on PC and I could quickly test the object detection on Ubuntu 22.04. MediaPipe Tasks can be […]