Inforce 68A1 SoM supports up to seven 4Kp120 cameras, dual 4Kp120 video encoding/decoding

Inforce 68A1 QCS8250 module

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 Raspberry Pi 4 Robot Dog

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)

OpenCV AI Kit LIte

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: […]

Qualcomm Flight RB5 5G Platform is a high-end drone reference design with 7 cameras

Qualcomm Flight RB5 5G Platform

Leveraging its involvement in the Ingenuity Mars helicopter, Qualcomm has introduced the Qualcomm Flight RB5 5G platform, a high-end drone reference design with 5G and WIFi 6 connectivity, seven cameras up to 8K resolution, and 15 TOPS of AI performance. The platform is based on Qualcomm QRB5165 octa-core processor, a variant of Snapdragon 865 for robotics, also found in Qualcomm Robotics RB5 Platform with support for Intel RealSense D435i (that should reach end-of-life soon), and provides an upgrade to the company’s Flight Pro drone based on Qualcomm Snapdragon 820 platform. Qualcomm Flight RB5 5G Platform key features and specifications: SoC – Qualcomm QRB5165 with eight Kryo 585 cores up to 2.84 GHz, GPU Adreno 650 GPU with support for Open GL ES and OpenCL, Hexagon 698 DSP with HVX, Hexagon Tensor Accelerator, Qualcomm Spectra 480 ISP with dual 14-bit image signal processing Memory – LPDDR5 up to 2750 MHz, LPDDR4x up […]

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 […]

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

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 […]

StereoPi v2 stereoscopic camera is powered by Raspberry Pi CM4 (Crowdfunding)

StereoPi v2 Raspberry Pi CM4 camera

StereoPi stereoscopic camera based on Raspberry Pi Compute Module 3 was introduced in late 2019 on Crowd Supply.  The camera can record 3D video, create 3D depth maps with OpenCV, and benefits from the Raspberry Pi software ecosystem. The developers are now back with an upgraded model. StereoPi v2 comes with many of the same features, but as it is based on Raspberry Pi CM4 (Compute Module 4) it offers better performance, Gigabit Ethernet, Wifi & Bluetooth connectivity out of the box, while other features like PoE, TFT screen, shot button, etc.. are optional. StereoPi v2 specifications: Supported SoM – Raspberry Pi CM4 or CM4Lite modules Storage – MicroSD card socket Video Output – Micro HDMI port Camera I/F – 2x MIPI CSI camera connector plus “hackable camera lines” Networking – Gigabit Ethernet RJ45 port, plus optional WiFi 5 and Bluetooth 5.0 on Raspberry Pi CM4 module USB – 2x […]

Vizy AI camera runs Tensorflow, OpenCV, PyTorch on Raspberry Pi 4 (Crowdfunding)

Vizy AI Camera

We previously covered Charmed Labs PIXY2 computer vision camera based on an NXP LPC4330 microcontrollers that worked with Arduino, Raspberry Pi, and other development boards. The company is now back with a fully integrated more powerful solution with Vizy AI camera featuring a Raspberry Pi 4 SBC with up to 8GB RAM. Vizy AI camera key features and specifications: SBC – Raspberry Pi 4 with Broadcom BCM2711 quad-core Arm Cortex-72 processor, up to 8 GB RAM Camera – High-resolution camera based on Sony iMX477 12.3 MP sensor that can capture at over 300 frames/second and support both daytime and nighttime viewing; Both M12 and C/CS lenses are supported Video Output – 2x micro HDMI ports Audio – Analog stereo audio port Networking – Gigabit Ethernet, dual-band WiFi 5, and Bluetooth 5.0 USB – 2x USB 3.0 ports, 2x USB 2.0, 1x USB Type-C port from Raspberry Pi 4 (But not […]