Getting started

System requirements

  • A modern Linux distro

  • Nvidia or Intel graphics card (ATI has not been tested)

  • A graphics card driver supporting OpenGL 3+

  • For up-to-date hardware and driver requirements, see here.

  • An up-to-date valkka-core library

  • For Ubuntu-based distros, an automatic installation is provided

  • If you need to compile from source, refer to valkka-examples

Installing

We’ll be installing directly from github, so git is required:

sudo apt-get install git python3-pip

After that, install (or update) with:

pip3 install --user --upgrade git+git://github.com/elsampsa/valkka-live.git
install-valkka-core
valkka-tune

(the first script installs valkka-core modules, the second one tunes the maxmimum socket buffer sizes)

Be also aware of some issues regarding to numpy and OpenCV installation. You can test your libValkka installation with:

curl https://raw.githubusercontent.com/elsampsa/valkka-examples/master/quicktest.py -o quicktest.py
python3 quicktest.py

In the case that install-valkka-core etc. scripts refuse to work, you must fix your path with

export PATH=$PATH:$HOME/.local/bin

Finally, run with

valkka-live

If and when the program crashes (with “dangling” machine vision python multiprocesses), remember to clean the table with

valkka-kill

Command-line options

You can see a list of them with:

valkka-live -h

In particular, --playback=true will enable the experimental playback & recording features (warning: there might be crashes & freezes)

Hacky mode

If you want to install Valkka Live, hack it, add your own machine vision modules, etc., install it in the development mode:

git clone https://github.com/elsampsa/valkka-live.git
cd valkka-live
pip3 install --user -e .

Use that last command to update Valkka Live every now and then.