GEPARD - Gepard-Enabled PARticle Detection for Raman microscopes.

Copyright (C) 2018 Lars Bittrich and Josef Brandt, Leibniz-Institut für Polymerforschung Dresden e. V. bittrich-lars@ipfdd.de

Requirements:

• python 3.6, PyQt5, OpenCV 3.4.1, numpy 1.14, scikit-image 0.13.1, scipy 1.1.0, win32com, pythoncom, cython 0.28
• we advise the use of Anaconda (python 3.6): https://www.anaconda.com/download this package contains most of the python libraries however, opencv and scikit-image are missing start anaconda prompt and install opencv: pip install opencv-python conda install scikit-image
• we recommend working with a 64bit OS and also a python interpreter compiled for 64bit as many use cases require a lot of memory (16 GB better 32 GB recommended)
• the tsp module in externalmodules can be built with python setuptsp.py please note: for this step a valid compiler needs to be installed in the system; Otherwise use the precompiled tsp-module If you plan on using the WITec Raman interface to control your device, please note: You use this interface at your OWN RISK! Make sure, that no obstacles block the objective and that you UNDERSTAND and VALIDATE the code, that controls the microscope! Start with "witectesting.py", which should read and move within small margins.

At the moment the program is an executable python script. Copy the folder with all its content to some place and run (e.g. using anaconda prompt): python gepard.py

It is possible to create a windows link file, that executes python with the gepard script as an argument and the working directory pointing to the folder containing gepard for convenience.

Working Principle

The working principle is explained here