EDATEC ED-AIC2020 is an IP67-rated, Raspberry Pi CM4-based industrial AI camera equipped with a fixed or liquid lens and LED illumination that leverages the Raspberry Pi Compute Module 4 to run computer vision applications using OpenCV, Python, And Qt. We’ve previously written about Raspberry Pi Compute Module-based smart cameras such as the Q-Wave Systems EagleEye camera (CM3+) working with OpenCV and LabVIEW NI Vision and the StereoPi v2 (CM4) with stereo vision. But the EDATEC ED-AIC2000 is the first ready-to-deploy Raspberry Pi CM4 AI camera we’ve covered so far. EDATEC “CM4 AI camera” (ED-AIC2020) specifications: SoM – Raspberry Pi Compute Module 4 up to 8GB RAM, up to 32GB eMMC flash Camera 2.0MP global shutter or 5.0MP rolling shutter Acquisition rate – Up to 70 FPS Aiming point – Red cross laser Built-in LED illumination (optional) Scanning field Electronic liquid lens Fixed focal length lens Networking Gigabit Ethernet M12 port Communication protocols – Ethernet/IP, PROFINET, Modbus […]
Open AI Lab EAIDK-610 devkit targets computer vision education with OpenCV
Open AI Lab EAIDK-610 is an embedded AI development kit powered by a Rockchip RK3399 processor, recently added to Linux 6.1 and described as “popularly used by university students” in the kernel changelog. But I had never heard about it, and it turns out it’s because it’s popular with students in China, and most documentation is written in Chinese. The development board is equipped with 4GB LPDDR3, a 16GB eMMC flash, HDMI video output, Gigabit Ethernet and WiFi 5, a few USB ports, a 40-pin GPIO header, and more. EAIDK-610 specifications: SoC – Rockchip RK3399 System Memory – 4GB LPDDR3 Storage – 16GB eMMC flash and MicroSD card slot Video Output HDMI 2.0 up to 4Kp60 MIPI DSI up to 1280×720 @ 60 fps 4-lane eDP 1.3 Audio – Speaker header, built-in microphone, 3.5mm audio jack, I2S header, digital audio via HDMI Camera I/F – 2x MIPI CSI up to […]
NVIDIA Jetson Nano based AI camera devkit enables rapid computer vision prototyping
ADLINK “AI Camera Dev Kit” is a pocket-sized NVIDIA Jetson Nano devkit with an 8MP image sensor, industrial digital inputs & outputs, and designed for rapid AI vision prototyping. The kit also features a Gigabit Ethernet port, a USB-C port for power, data, and video output up to 1080p30, a microSD card with Linux (Ubuntu 18.04), and a micro USB port to flash the firmware. As we’ll see further below it also comes with drivers and software to quickly get started with AI-accelerated computer vision applications. AI Camera Dev Kit specifications: System-on-Module – NVIDIA Jetson Nano with CPU – Quad-core Arm Cortex-A57 processor GPU – NVIDIA Maxwell architecture with 128 NVIDIA cores System Memory – 4 GB 64-bit LPDDR4 Storage – 16 GB eMMC Storage – MicroSD card socket ADLINK NEON-series camera module Sony IMX179 color sensor with rolling shutter Resolution – 8MP (3280 x 2464) Frame Rate (fps) – […]
Renesas RZ/V2MA microprocessor embeds AI & OpenCV accelerators for image processing
Renesas has launched the RZ/V2MA dual-core Arm Cortex-A53 microprocessor with a low-power (1TOPS/W) DRP-AI accelerator and one OpenCV accelerator for rule-based image processing enabling vision AI applications. The MPU also supports H.265 and H.264 video decoding and encoding, offers LPDDR4 memory and eMMC flash interfaces, as well as Gigabit Ethernet, a USB 3.1 interface, PCIe Gen 2, and more. The RZ/V2MA microprocessor targets applications ranging from AI-equipped gateways to video servers, security gates, POS terminals, and robotic arms. Renesas RZ/V2MA specifications: CPU – 2x Arm Cortex-A53 up to 1.0GHz Memory – 32-bit LPDDR4-3200 Storage – 1x eMMC 4.5.1 flash interface Vision and Artificial Intelligence accelerator DRP-AI at 1.0 TOPS/W class OpenCV Accelerator (DRP) Video H.265/H.264 Multi Codec Encoding: h.265 up to 2160p, h.264 up to 1080p Decoding: h.265 up to 2160p, h.264 up to 1080p Networking – 1x Gigabit Ethernet USB – 1x USB 3.1 Gen1 host/peripheral up to 5 […]
TI Sitara AM623 & AM625 Cortex-A53 SoCs offer low-power AI for HMI and IoT applications
Texas Instruments has just launched the new Sitara AM62 family with AM623 and AM625 single to quad-core Cortex-A53 processors designed to provide IoT gateways and HMI applications with AI processing at low power, in some cases with up to 50% reduction in power consumption. The AM623 processor specifically targets Internet of Things (IoT) applications and gateways that may benefit from object and gesture recognition, while the AM625, equipped with a 3D GPU, should power HMI applications with edge AI and up to two full-HD displays. Sitara AM623 and AM625 processors Sitara AM623/AM625 key features and specifications: CPU – Single, dual, or quad-core Arm Cortex-A53 processor @ up to 1,400 MHz with 512KB L2 shared cache, plus 32KB I+D cache per core Co-processor – 1x Arm Cortex-M4F real-time core at up to 400 MHz with 256KB SRAM with SECDED ECC GPU (AM625 only) – Unnamed 3D GPU with support for OpenGL […]
Inforce 68A1 SoM supports up to seven 4Kp120 cameras, dual 4Kp120 video encoding/decoding
SMART Wireless Computing has announced the Inforce 68A1, a compact system-on-module based on Qualcomm QCS8250 IoT processor with support for up to seven concurrent 4Kp120 camera inputs, and decode/encode two 4Kp120 video streams simultaneously. Equipped with 8GB PoP DDR5 memory, 64GB UFS storage, a wireless module supporting 802.11ax Wi-Fi 6E and Bluetooth 5.1, the module is designed for high-end IoT applications such as smart cameras, video collaboration, AI hubs, connected healthcare, and smart retail. Inforce 68A1 specifications: SoC – Qualcomm QCS8250 octa-core Kryo 585 processor up to 2.84 GHz (high-performance cores) or 1.8 GHz (low power cores) with Adreno 650 GPU, Adreno 665 VPU, Adreno 995 DPU, Hexagon DSP with quad HVX, NPU230 neural processing unit, Spectra 480 ISP; 15 TOPS AI processing power System Memory – 8GB LPDDR5 (PoP) Storage – 64GB UFS flash Wireless – Qualcomm QCA6391 with 802.11 a/b/g/n/ac/ax Wi-Fi 6 2×2 MIMO, Bluetooth 5.1 Audio – […]
Mini Pupper – Raspberry Pi 4-based robot dog teaches ROS, SLAM, navigation, computer vision (Crowdfunding)
Mini Pupper is a Raspberry Pi 4 powered robot dog inspired by Stanford Pupper open-source quadruped robot, and designed in “light collaboration” with Nathan Kau, the original creator of Stanford Pupper. Just like the original design, MangDang’s Mini Pupper is open-source, based on Ubuntu and ROS (Robot Operating System), and designed for robotics education in schools, homeschool families, enthusiasts and others, with notably students being able to learn out to use ROS, SLAM, navigation, and OpenCV computer vision through online courses that will come with the robot. Mini Pupper key features and specifications: SBC – Raspberry Pi 4 Model B with 2GB RAM Storage – 2GB microSD card Display – 320×240 LCD for facial animation Camera – Support for OpenCV AI Kit Lite 12 DOF via MangDang’s custom servos Optional Lidar module for SLAM (Simultaneous localization and mapping) Battery – 800 mAh Charger – Input voltage – 100-240V AC 50/60Hz, […]
OpenCV AI Kit Lite – A compact 4K Tri-camera kit for computer vision applications (Crowdfunding)
The OpenCV AI Kit “OAK-D” now has a little brother with the OpenCV AI Kit Lite equipped with the same Intel Myriad X-based DepthAI solution with three cameras, but in a much compact form factor and a price slashed to as low as $79 and up. Like its predecessor, the OpenCV AI Kit leverage the Myriad X AI accelerator’s capabilities to provide a wide range of real-time computer vision applications, and can be programmed with C++ or Python APIs, as well as graphical user interfaces. OpenCV AI Kit Lite (OAK-D Lite) specifications: Intel Myriad X-based DepthAI with 4 TOPS of AI performance Cameras (made by ArduCam) Color Camera IMX214 (PLCC) with 4208×3120 resolution, 1.348:1 aspect ratio 1/3.1 inch Lens size 81.3 degrees DFOV Focus range 8cm – ∞ Stereo Camera specifications: Omnivision OV07251-G04A-1E (COB) with 640 x 480 resolution, 1.333:1 aspect ratio 1/7.5 inch lens size DFOV: 85.6,HFOV: 72.9, VFOV: […]