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 USB 2.0 Type-A ports, 1x USB 2.0 interface on header […]
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 sure it’s actually used) Expansion – 8-pin terminal block for […]
iWave Systems i.MX8M Mini Board is a development platform based on an update versions of the company’s iW-RainboW-G34M-SM i.MX 8M Mini system-on-module and designed specifically for low-cost facial recognition systems thanks to NXP eIQ ML software, and MIPI display and camera. iWave Systems i.MX8M Mini (aka iW-RainboW-G34D) specifications: SoM SoC – NXP i.MX8M Mini Q/QL/D/DL/S/SL with up to 4x Cortex-A53 cores, 1x Cortex-M4F real-time core, Vivante 3D and 2D GPUs System Memory – 1GB LPDDR4 (Expandable up to 4GB) Storage – 8GB eMMC Flash (Expandable), optional 2MB QSPI Flash optional Micro SD slot Wireless – Dual-band 802.11a/b/g/n/ac WiFi 5 and Bluetooth 5.0. PMIC – BD71847AMWV i.MX8M SODIMM Carrier Board Storage – MicroSD slot Display I/F – MIPI DSI display connector Camera I/F – MIPI CSI camera connector Audio – Audio codec, 3.5mm Line In/Out jack Networking – Up to 2x Gigabit Ethernet ports (One is Optional) USB – 2x USB 2.0 Host ports, 1x USB 2.0 device port Debugging – […]
MediaPipe is an open-source perception pipeline framework introduced by Google, which helps to build multi-modal machine learning pipelines. A developer can build a prototype, without really getting into writing machine learning algorithms and models, by using existing components. This framework can be used for various vision & media processing applications (especially in VR) such as Object Detection, Face Detection, Hand Tacking, Multi-hand Tracking and Hair Segmentation. MediaPipe supports various hardware and operating system platforms such as Android, iOS & Linux by offering API’s in C++, Java, Objective-c, etc. And this framework also capable of utilizing GPU resources. MediaPipe Components The framework is comprised of three major components A framework for inference from the pipeline data Tools for evaluation And a collection of reusable inference and processing components It follows the approach of Graph-based frameworks in OpenCV and all processing happens with the context of the Graph. The Graph contains a collection of nodes and each node is implemented as a […]
We previously covered Q-Wave Systems’ Melon S3 board combining a Xilinx Spartan 3E FPGA with ESP8266, but the Thai company is back is a completely different product: EagleEye Smart Camera. The board is powered by Raspberry Pi Compute Module 3+ (CM3+) with 16GB or 32GB flash, and equipped with a 5 MP camera for machine vision and robotics applications. There are two version of the board Uno and Industrial with the latter adding 24V digital input and outputs, circuit protections and support for industrial temperature range. EagleEye smart camera key features & specifications: SoM – Raspberry Pi CM3+ with Broadcom BCM2837B0 quad core cortex-A53 processor, 1 GB RAM, and 16GB or 32 GB flash Camera – 5 MP OV5647 image sensor, CS/M12 lens holder + 4mm CS lens Video Output – mini HDMI port Networking – 10/100M Ethernet USB – 1x USB 2.0 host port up to 1.2A Expansion Uno – 4x 3.3V digital input; 4x 3.3V digital output; both […]
Allwinner V5 V100 is a new quad core Cortex A7 processor targeting 4K 30 fps (Linux) cameras, and integrating AIE intelligent analytic acceleration engine handling motion detection, perimeter defense video diagnosis, and face detection. Usually, it’s pretty hard to get a development board based on a new processor, but Lindenis V5 single board computer based on the processor is already available in China, and comes with 1 to 2GB RAM, HDMI 1.4 and MIPI DSI video outputs, dual MIPI CSI video inputs, Gigabit Ethernet and more. Lindevis V5 SBC specifications: SoC – Allwinner V5 Quad-core Arm Cortex-A7 processor @ up to 1,512 MHz with NEON, VFPv4 FPU 4K @ 30 fps H.265/H.264 encoder and decoder Dual ISP [email protected] + [email protected] AIE (AI Engine) Architecture – Built-in with intelligent analytics acceleration engine with support for motion detection, perimeter defense, video diagnosis, face detection, flow statistics. Supports binocular depth map. System Memory – 1 or 2GB RAM Storage – Micro SD card […]
The Chiang Mai Maker Party 4.0 is now taking place until December 9, and I went there today, as I was especially interested in the scheduled NB-IoT talk and workshop to find out what was the status about LPWA in Thailand. But there are many other activities planned, and if you happen to be in Chiang Main in the next few days, you may want to check out the schedule on the event page or Facebook. I’m going to go though what I’ve done today to give you a better idea about the event, or even the maker movement in Thailand. Booth and activity area should be the same over the 4 days, but the talks, open activity, and workshop will be different each day. Today, people could learn how to solder in the activity area. The even was not really big with manufacturers/sellers like ThaiEasyElec, INEX, or Gravitech closer to the entrance… … and slighter higher up in a […]
Computer Vision, Artificial Intelligence, Machine Learning, etc.. are all terms we hear frequently those days. JeVois-A33 smart machine vision camera powered by Allwinner A33 quad core processor was launched last year on Indiegogo to bring such capabilities in a low power small form factor devices for example to use in robotics project. The company improved the software since the launch of the project, and has now sent me their tiny Linux camera developer kit for review, and I’ve already checked out the hardware and accessories in the first post. I’ve now had time to test the camera, and I’ll explained how to set it up, test some of the key features via the provided guided tour, and show how it’s possible to customize the camera to your needs with one example. Getting Started with JeVois-A33 In theory, you could just get started by inserting the micro SD card provided with the camera, connect it to your computer via the USB […]
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