NOTE: CURRENTLY UNDERGOING SERIOUS REFACTORING, THE MASTER BRANCH IS NOT IN A WORKING STATE. PLEASE STICK TO THE 1bab4b9c60ad43302e460a24de14a0ac136bea7f COMMIT FOR WORKING WITH THE ARCAN 0.5.2 VERSION.
It current runs on Linux/BSDs and OSX. IRC chat @ #arcan on irc.freenode.net.
First make sure that you have a working build of arcan and durden. Familiarize yourself with the UI input and window management scheme before moving further.
On voidlinux, most of this is packaged, you can simply go from the linux console (won't cooperate with Xorg, for that you need to rebuild with an SDL based backend):
xbps-install durden durden
Senseye itself and its support scripts have not yet been included in the same packaging. Simply do this:
ln -s /path/to/senseye/senseye $HOME/.arcan/appl/durden/tools ln /path/to/senseye/senseye.lua $HOME/.arcan/appl/durden/tools/senseye.lua
And either restart or activate global/system/reset=yes. You can then find the different analysis tools under the target/senseye path, though the set of options and features will vary with the source you are using it on.
The individual senses should work fine with any other Arcan based window management system though, and the scripts themselves should require little repurposing.
For other settings, you can wait for the project to mature enough to be packaged in your environment, and be brave and install/build from source.
The short version for building arcan on a system that has native graphics already is something like:
git clone https://github.com/letoram/arcan.git mkdir arcan/build ; cd arcan/external/git; ./clone.sh ; cd ../../build cmake -DVIDEO_PLATFORM=sdl -DSTATIC_FREETYPE=ON -DSTATIC_SQLITE3=ON -DSTATIC_OPENAL=ON ../src make -j 12 sudo make install
This one requires libsdl1.2-dev (or whatever the package is called on your system).
For starting durden:
git clone https://github.com/letoram/durden.git /usr/local/bin/arcan /path/to/durden/durden
When you are the stage where Arcan is up and running, durden has started, you can spawn a terminal (default: meta1+enter) window. These terminals will have the environment setup for the senseye sensors to connect and start providing data.
Now you are ready to build the sensors and translators:
git clone https://github.com/letoram/senseye.git mkdir senseye/build ; cd senseye/build cmake ../senses
It is possible to avoid installing arcan and using an in-source build with:
cmake -DARCAN_SOURCE_DIR=/path/to/arcan/src ../senses
Senseye uses Capstone engine for providing disassembly translators. If it is not installed, its current master branch will be cloned and linked statically. To disable disassembly support, add -DENABLE_CAPSTONE=OFF (or use an interactive cmake interface for better control).
Senseye is divided up into UI tool scripts, sensors and translators.
Copy or symlink the tools/senseye.lua and the subfolder tools/senseye into the corresponding durden/durden/tools/senseye.lua and durden/durden/tools/senseye.
If you have durden active while you do it, you can rescan/reload the scripts by going into the global menu (meta1+g), pick system and then reset.
These scripts hook into the 'target window' menu for windows that have identified as senseye data sources and take aggressive control over the settings and behavior of the window.
The current toolscripts are:
Missing: [ ] Create a mapping window that allows zoom / etc. [ ] Use a vertex shader or LUT based approach [ ] Alpha channel only- shader [ ] Save buffer
A histogram window is created via target/senseye/histogram. By default, it will be capped to 256x256 linear sampled version of the source window in order to not make the UI responsive in the event of a big source.
In the histogram window, you have the following options:
- Imposition-mode (merge, full) : if r,g,b channels should be averaged or separated
- Size-mode (capped, full) :
Missing: [ ] define reference histogram and pause or log on match [ ] mouse / pattern selection feedback into mapping window [ ] counter in titlebar [ ] keyboard input
Missing: [ ] Mapping window but with 3D navigation options (rotate/zoom/step point-sz)
Pattern Matching / Searching
[ ] Basic feature, use browser to load reference [ ] trigger action
[ ] Basic Feature [ ] Color space management
samples input data and packages it in a form where the UI can make sense of it.
The current sensors are:
Translators are windowed- parsers that take an incoming data stream and provide some kind of non-native representation of the contents of the data stream. This output comes in two forms, a separate data- window, and a controlable overlay that is presented on top of the visualization of the incoming data source in itself.
The current translators are: