Distributed computing
*********************

Distributed computing is useful for processors that take a long time to compute. E.g. FeatureExtraction
and feature matching. There are two methods to achieve distributed computing - one using the same machine multiple
cpu, and second - to use a remote machine on the same network.

Using Multiprocessing
=====================


Using PyroCapture
=================

Since FeatureExtraction doesn't scale properly on the same machine and is usually already parallelized inside
openCV it is possible to relay some lengthy processing to a different machine. This is really useful
for stereo processing, where two machines will capture and process images from left and right camera respectively.
Then ``CalibratedStereoCamera`` would capture those processed frames and return as a single frame for further processing
e.g. for Visual Odometry engine.

To achieve that, you need to have two machines on the same network, that run ``EasyVision.bin.server`` instances
for serving captured and processed images. One machine that serves as a NameServer and consumer of those images.

Internally this mechanism uses Pyro4 library.

In case you want to expose other Pyro4 objects, you can pass them to ``Server`` as ``Server(..., objects=my_objects_list)``.
You can expand on ``EasyVision/bin/server.py`` code.