A Day at Chiang Mai Maker Party 4.0

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 …

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 the camera, connect it to your computer via the USB …

Dragonwally is a Stereoscopic Computer Vision Mezzanine for 96Boards CE Boards

Hardware based on 96Boards specifications may not have the number of sales as Raspberry Pi or Orange Pi boards, but there’s heavily used by Linaro member and other developer working on bleeding edge software. More and more companies are designing boards compliant with the standard, and several new mezzanine expansion boards such as Secure96, were showcased at Linaro Connect SFO 2017, and are yet to be show up on 96Boards Mezzanine page. Another 96Boards mezzanine expansion board in development is Dragonwally, designed for stereoscopic computer vision, currently used with DragonBoard 410c board, and targetting applications such as object recognition,  people counting, access control, or driver identification and safety. DragonWally DW0 board specifications: MIPI DSI interface with high speed connector 2x 5MP cameras 1x USB port 96Boards CE compliant The two Brazilian developers working on the project interfaced it with DragonBoard 410c running Linaro Debian, and using OpenCV and Python for computer vision development. To demonstrate the capability of the board, …

Getting Started with OpenCV for Tegra on NVIDIA Tegra K1, CPU vs GPU Computer Vision Comparison

This is a guest post by Leonardo Graboski Veiga, Field Application Engineer, Toradex Brasil Introduction Computer vision (CV) is everywhere – from cars to surveillance and production lines, the need for efficient, low power consumption yet powerful embedded systems is nowadays one of the bleeding edge scenarios of technology development. Since this is a very computationally intensive task, running computer vision algorithms in an embedded system CPU might not be enough for some applications. Developers and scientists have noticed that the use of dedicated hardware, such as co-processors and GPUs – the latter traditionally employed for graphics rendering – can greatly improve CV algorithms performance. In the embedded scenario, things usually are not as simple as they look. Embedded GPUs tend to be different from desktop GPUs, thus requiring many workarounds to get extra performance from them. A good example of a drawback from embedded GPUs is that they are hardly supported by OpenCV – the de facto standard libraries …

Embedded Systems Conference 2017 Schedule – May 3-4

The Embedded Systems Conference 2017 will take place over two days in Boston, US on May 3-4, and the organizers have published the schedule of the event. Even if you’re not going to attend, you’ll often learn something or find new information by just checking out the talks and abstracts, so I’ve created my own virtual schedule with some of the most interesting sessions. Wednesday, May 3rd 08:00 – 08:45 – Combining OpenCV and High Level Synthesis to Accelerate your FPGA / SoC EV Application by Adam Taylor, Adiuvo Engineering & Training Ltd This session will demonstrate how you can combine commonly used Open source frameworks such as OpenCV with High Level Synthesis to generate a embedded vision system using FPGA / SoC. The combination of OpenCV and HLS allows for a much faster algorithm development time and consequently a faster time to market for the end application. 09:00 – 09:45 – Understanding the ARM Processor Roadmap by Bob Boys,   Product …

Open Source ARM Compute Library Released with NEON and OpenCL Accelerated Functions for Computer Vision, Machine Learning

GPU compute promises to deliver much better performance compared to CPU compute for application such a computer vision and machine learning, but the problem is that many developers may not have the right skills or time to leverage APIs such as OpenCL. So ARM decided to write their own ARM Compute library and has now released it under an MIT license. The functions found in the library include: Basic arithmetic, mathematical, and binary operator functions Color manipulation (conversion, channel extraction, and more) Convolution filters (Sobel, Gaussian, and more) Canny Edge, Harris corners, optical flow, and more Pyramids (such as Laplacians) HOG (Histogram of Oriented Gradients) SVM (Support Vector Machines) H/SGEMM (Half and Single precision General Matrix Multiply) Convolutional Neural Networks building blocks (Activation, Convolution, Fully connected, Locally connected, Normalization, Pooling, Soft-max) The library works on Linux, Android or bare metal on armv7a (32bit) or arm64-v8a (64bit) architecture, and makes use of  NEON, OpenCL, or  NEON + OpenCL. You’ll need an …

JeVois-A33 is a Small Quad Core Linux Camera Designed for Computer Vision Applications (Crowdfunding)

JeVois Neuromorphic Embedded Vision Toolkit – developed at iLab at the University of Southern California – is an open source software framework to capture and process images through a machine vision algorithm, primarily designed to run on embedded camera hardware, but also supporting Linux board such as the Raspberry Pi. A compact Allwinner A33 has now been design to run the software and use on robotics and other projects requiring a lightweight and/or battery powered camera with computer vision capabilities. JeVois-A33 camera: SoC – Allwinner A33  quad core ARM Cortex A7 processor @ 1.35GHz with  VFPv4 and NEON, and a dual core Mali-400 GPU supporting OpenGL-ES 2.0. System Memory – 256MB DDR3 SDRAM Storage – micro SD slot for firmware and data 1.3MP camera capable of video capture at SXGA (1280 x 1024) up to 15 fps (frames/second) VGA (640 x 480) up to 30 fps CIF (352 x 288) up to 60 fps QVGA (320 x 240) up to …

AVC8000nano mini PCIe Frame Grabber Captures up to 8 D1 Videos

There are plenty of solutions to stream or capture multiple video streams from cameras, but example for security purpose, but usually the equipment is relatively large and heavy. Advanced Micro Peripherals AVC8000nano mini PCIe capture card miniaturizes all that thanks to its form factor, and its 8 u.FL connectors used to capture eight D1 videos at full frame rate. AVC8000nano features: Video Inputs 8x Live NTSC/PAL video inputs with 8x 10-bit ADC and anti-aliasing filters 8x D1 size capture at full frame rate Formats – NTSC-M, NTSC-Japan, NTSC (4.43), RS-170, PAL-B,G,N, PAL-D, PAL-H, PAL-I, PAL-M, PAL-CN, PAL-60 SECAM Adjustments – Contrast, saturation, hue (or chroma phase), and brightness. Software adjustable Sharpness, Gamma and noise suppression Video Capture Formats – RGB555, RGB565, YCbCr 4:2:2, YCbCr 4:1:1 Windows support with Drivers and DirectShow/DirectDraw Linux with drivers and Video4Linux Form factor – Full height mini PCI Express Temperature Range – Commercial: 0°C to 60°C; Extended: –40°C to +85°C The specifications also mentions hardware …