linux - Yi Systems

Setup Development environment for ROS and OpenCV on Raspberry Pi


In my rover car project, ROS is the framework to communicate among all components, including motors, camera, user input and algorithms. OpenCV is the framework for image processing like lane detection and line following. ROS Indego is the TLS version, which is easy to install with Ubuntu 14.04. ROS Jade is easy to install, too. If you install Ubuntu 15 or later, then you need to build ROS from sources. This article shows how to install ROS Jade.

Install Ubuntu on Raspberry Pi


This is to install Ubuntu 14.04 on Raspberry Pi, instead of Raspbian. With Ubuntu installed, it is much easier to install ROS from package repositories, or we need to build ROS from sources, which is a lot of work.

Development experience between Windows and Linux

It all started in 2012 when I had a chance to port my all image processing codes from Windows to Linux. That includes all C++ codes with lots of GUI implementation, not to mention several COM model architecture and several Windows-only technologies. For now, I'm very happy to work between these two platforms under the same code base. This might be very normal to some of you, but with 10+ years of Windows codes, it is still a struggle to migrate all to Linux in 4 months. Here is the story:

Yi ToolSets

There are four comprehensive tools included in Yi-ToolSet, please follow download link to try. Yi-ToolSet is a C++ SDK which serves several basic and advanced image processing needs, including:

  • Brightness, Contract, Exposure

    Highlight/Shadow recovery

    Tone Curve adjustment


    Color space conversion

    Local Details

    Local Contrast/Local Tone mapping

    Split tone

In this toolset, we utilize Qt to implement cross platform UI. OpenCV, OpenMP and Intel TBB are used to make parallel computing possible. We also implement our own memory management, such that it is ok to handle virtually any size of bitmap in resource limited environment (Android, iOS or embedde systems.)

They are available in source codes or SDK, on Windows, Linux, iOS and Android. These demo programs are currently available in Windows platform, will provide Linux/Android platform later.

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