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November 30, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

AWS DeepLens is a $249 Deep Learning Video Camera for Developers

Amazon Web Services (AWS) has launched Deeplens, the “world’s first deep learning enabled video camera for developers”. Powered by an Intel Atom X5 processor with 8GB, and featuring a 4MP (1080p) camera, the fully programmable system runs Ubuntu 16.04, and is designed expand deep learning skills of developers, with Amazon providing tutorials, code, and pre-trained models. AWS Deeplens specifications: SoC – Intel Atom X5 Processor with Intel Gen9 HD graphics (106 GFLOPS of compute power) System Memory – 8GB RAM Storage – 16GB eMMC flash, micro SD slot Camera – 4MP (1080p) camera using MJPEG, H.264 encoding Video Output – micro HDMI port Audio – 3.5mm audio jack, and HDMI audio Connectivity – Dual band WiFi USB – 2x USB 2.0 ports Misc – Power button; camera, WiFi and power status LEDs; reset pinhole Power Supply – TBD Dimensions – 168 x 94 x 47 mm Weight – 296.5 grams The […]

November 22, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

Hisilicon Hi3559A V100ES is an 8K Camera SoC with a Neural Network Accelerator

Earlier today, I published a review of JeVois-A33 machine vision camera, noting that processing is handled by the four Cortex A7 cores of Allwinner A33 processor, but in the future we can expect such type of camera to support acceleration with OpenCL/Vulkan capable GPUs, or better, Neural network accelerators (NNA) such Imagination Tech PowerVR Series 2NX. HiSilicon already launched Kirin 970 SoC with such similarIP, except they call it an NPU (Neural-network Processing Unit). However, while looking for camera SoC with NNA, I found a list of deep learning processors, including the ones that go into powerful servers and autonomous vehicles, that also included a 8K Camera SoC with a dual core CNN (Convolutional Neural Network) acceleration engine made by Hisilicon: Hi3559A V100ES. Hisilicon Hi3559A V100ES specifications: Processor Cores 2x ARM Cortex A73 @ 2 GHz, 32 KB I cache, 64KB D cache or 512 KB L2 cache 2x ARM […]

November 22, 2017November 23, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

JeVois-A33 Linux Computer Vision Camera Review – Part 2: Setup, Guided Tour, Documentation & Customization

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 […]

November 15, 2017November 17, 2018 by Jean-Luc Aufranc (CNXSoft) - 12 Comments

Xiaomi Mi A1 Smartphone Review – Part 2: Android 7.1.2 Firmware

Google recently announced several Android One smartphones, which are supposed to get 2 years of firmware updates, including to the latest version of Android, such as HTC U11 Life and Android One Moto X4. Many of those phones are limited to some specific countries, but Xiaomi Mi A1 will be launched in over 40 countries, and thanks to Chinese online shops is really available worldwide. GearBest sent me the latter last month, and in the first part of Xiaomi Mi A1 review I simply went through unboxing, booted the phone, perform an OTA update, and ran Antutu 6.x on the phone for a quick estimate of performance. Since then, I’ve had around four weeks to play with the smartphone running Android 7.1.2 (still), so I’m ready to report my experience in the second part of the review. General Impressions In the past year, I used Vernee Apollo Lite smartphone powered […]

November 12, 2017November 12, 2017 by Jean-Luc Aufranc (CNXSoft) - 36 Comments

NanoPi Fire2A & Fire3 Boards Released with Samsung/Nexell Quad & Octa Core Processors

FriendlyElec previously launched NanoPi 2 Fire board powered by Samsung (Nexell) S5P4418 quad core Cortex A9 SoC, mostly interesting because of its small form factor, camera and LCD interfaces. The company has now launched two new boards based on S5Pxx18 processors, namely NanoPi Fire2A powered by S5P4418 SoC, and NanoPi Fire3 based on S5P6818 octa-core Cortex-A53 SoC. Both boards share the same form factor, which remains quite similar to the one of NanoPi 2 Fire, except the HDMI connector now makes place for a micro HDMI port, the USB 2.0 has moved into vertical position, and a few other tweaks have been made to positions of buttons and components. NanoPi Fire2A / Fire3 specifications: SoC Fire2A – Samsung S5P4418 quad core Cortex A9 processor @ up to 1.4GHz, Mali-400MP GPU Fire3 – Samsung S5P6818 octa core Cortex A53 processor @ up to 1.4 GHz, Mali-400MP GPU System Memory Fire2A – 512MB DDR3 […]

October 24, 2017October 24, 2017 by Jean-Luc Aufranc (CNXSoft) - No Comments

JeVois Smart Machine Vision Camera Review – Part 1: Developer / Robotics Kit Unboxing

JeVois-A33 computer vision camera was unveiled at the end of last year through a Kickstarter campaign. Powered by an Allwinner A33 quad core Cortex A7 processor, and a 1.3MP camera sensor, the system could detect motion, track faces and eyes, detect & decode ArUco makers & QR codes, follow lines for autonomous cars, etc.. thanks to JeVois framework. Most rewards from KickStarter shipped in April of this year, so it’s quite possible some of the regular readers of this blog are already familiar the camera. But the developer (Laurent Itti) re-contacted me recently, explaining they add improves the software with Python support, and new features such as the capability of running deep neural networks directly on the processor inside the smart camera. He also wanted to send a review sample, which I received today, but I got a bit more than I expected, so I’ll start the review with an […]

October 20, 2017October 30, 2017 by Jean-Luc Aufranc (CNXSoft) - 14 Comments

Banana Pi M2 Magic Board Now Sold with Allwinner A33 Processor for $23

Banana Pi M2 Magic development board was first unveiled in February of this year with an Allwinner R16 SoC, 512 MB RAM, and 8GB eMMC flash, and its main selling points were support for MIPI DSI LCD displays, CSI cameras, and 3.7V LiPo batteries. AFAIK SinoVoIP never sold that version of the board, at least on Aliexpress. Possibly due to the intricacies of Allwinner business units, the company has now officially launched Banana Pi M2 Magic (aka BPI M2M), but replaced Allwinner R16 by the similar Allwinner A33 processor, and removed the 8GB eMMC flash to bring the price down to $23 plus shipping. The “old” Allwinner R16 based Banana Pi M2 Magic board will apparently be sold as M2 Magic Plus soon. Banana Pi BPI-M2 Magic (A33) specifications: SoC – Allwinner A33 quad core ARM Cortex-A7 processor with ARM Mali 400 MP2 GPU System Memory – 512MB DDR3 Storage […]

October 18, 2017 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Google Pixel Visual Core is a Custom Designed Co-Processor for Smartphone Cameras

Google unveiled their latest Pixel 2 & Pixel 2 XL premium smartphones powered by Snapdragon 835 SoC earlier this month, and while they are expected to go on sale tomorrow, reviewers have got their hands on samples, and one of the key feature is the camera that takes really good photos and videos as reported here and there. You’d think the ISP and DSP inside Snapdragon 835 SoC would handle any sort of processing required to take photos. But apparently that was not enough, as Google decided to design their own custom co-processor – called Pixel Visual Core -, and integrated it into Pixel 2 phones. The co-processor features a Cortex A53 core, an LPDDR4 memory interface, PCIe interface and MIPI CSI interface, as well as an image processing unit (IPU) IO block with 8 IPU cores. Google explains the IPU block will allow 3rd party applications to leverage features […]