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exploring, building, coding, innovating, etc
Miguel Xochicale, PhD
mxochicale
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exploring, building, coding, innovating, etc
Research Engineer @UCL-ARC, previously postdoc @KCL-BMEIS. Passion for real-time AI, Medical Imaging Synthesis, MedTech, Medical Robotics & Clinical Translation
A script to convert SVG to a TIFF acceptable to PLOS
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Switching from Mendeley Desktop 1.13 to an earlier version
Since this is a major update, it is unfortunately not backwards compatible with Mendeley Desktop 1.12.
If you encounter problems with the preview release and need to go back to 1.12 whilst we fix
the issue, please read this carefully.
In particular do not use the 'Restore Backup' feature for this.
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Ubuntu 16.04 LTS Xenial Xerus - Basic packages i usually install
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how to add more utilities to git bash for windows, wget, make
How to add more to Git Bash on Windows
Git for Windows comes bundled with the "Git Bash" terminal which is incredibly handy for unix-like commands on a windows machine.
It is missing a few standard linux utilities, but it is easy to add ones that have a windows binary available.
The basic idea is that C:\Program Files\Git\mingw64\ is your / directory according to Git Bash (note: depending on how you installed it, the directory might be different. from the start menu, right click on the Git Bash icon and open file location. It might be something like C:\Users\name\AppData\Local\Programs\Git, the mingw64 in this directory is your root. Find it by using pwd -W).
If you go to that directory, you will find the typical linux root folder structure (bin, etc, lib and so on).
If you are missing a utility, such as wget, track down a binary for windows and copy the files to the corresponding directories.
Sometimes the windows binary have funny prefixes, so
Cross compile opencv3.3.0 for your raspberry pi and similar ARM devices with python support
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This is a note on how to cross compile opencv for pretty much any ARM device(HardFP supported in this case) and deploy. Native
compiling in ARM devices can be painfully slow and they seem to hang often during build(mine got stuck at 43%). So if you happen
to have a desktop/laptop/server running ubuntu or similar linux distro, u can build opencv in fractionth of the time taken for
native compiling without any issues.
Building opencv3 with TBB and NEON and VFP support can boost opencv performance. Thanks to Adrian at pyimagesearch for pointing
that out.
Both my PC and target machine aka orange pi zero are running ubuntu 16.04 with python2.7 and python 3.5.
Let us use the term "build machine" for your PC where you are building opencv and "target machine" for the ARM single board computer.
1.Run the following commands in both machines(I think installing these in target machine only would do) to install the necessary libraries etc.(mine worked with them,so they should be enough