Installing and launching GEPARD requires a minimal knowledge of command line navigation. Everything you need can be found here.
Prepare Python environment
Method 1 (recommended)
Download Miniconda from https://docs.conda.io/en/latest/miniconda.html. Choose the Python 3.8 version and follow the installer instructions. For help regarding installation, please refer to the Anaconda installation guide.
Open the Anacoda prompt, navigate to the folder you stored the
yml file and type the following command, replacing
xxx.yml with the name of the file you just downloaded:
conda env create -f xxx.yml
You have now created a new environment that contains everything you need to run GEPARD. To activate the new environment (assuming you are working in Windows) type:
conda activate GepardEnv-windows
The compilation of tsp modules and running GEPARD will need to be performed in this environment.
We strongly advise against modifying this environment for any purpose as this could interfere with the functionality of GEPARD.
Download Anaconda from https://www.anaconda.com/download. Choose the Python 3.8 version and follow the installer instructions. For help regarding installation, please refer to the Anaconda installation guide. Anaconda includes most of the required python libraries, however some packages need to be installed manually. To do that, start an Anaconda prompt from the Start Menu (Windows) or re-open a terminal (Linux, MacOS) and type the following:
pip install opencv-python conda install scikit-image dill cython
Download the Gepard bundle from the repository at https://gitlab.ipfdd.de/GEPARD/gepard. Be careful to download the master branch, unless you know what you're doing:
Extract all files into your preferred location. You should now have created a folder named
gepard-master. Rename the folder to
Build the tsp module
The following step requires a C compiler. On Windows you will need to install Build Tools for Visual Studio. Most Linux distributions include GCC.
In the Anaconda prompt (Windows) or the terminal (Linux, MacOS), navigate to the gepard-subfolder named
external. Then type:
If a compiler is not available in your system, the command will produce an error. The exact wording depends on your operating system.
In the Anaconda prompt (Windows) or terminal (Linux, MacOS) navigate to the location containing the folder
gepard. You can now start using Gepard in Simulated Raman Mode by typing:
python -m gepard
Connect to a Raman microscope
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.
You will need to create a Gepard configuration file. In a text editor write the following (edit the magnification to match your used objective):
[Interface] raman_interface = WITEC_CONTROL [General Microscope Setup] magnification = 20
Save it as
gepard.cfg in the Gepard folder.
To return to Simulated Raman Mode, set:
raman_interface = SIMULATED_RAMAN_CONTROL
Errors and solutions
Errors related to the compiling process
Import error: cannot import name 'tsp' from 'gepard.external': The tsp module has not been compiled (properly). Try compiling again or use a pre-compiled module.
error: command 'gcc' failed with exit status 1 (Linux): Your system's C-compiler,
gcc, is not installed or not up to date. Install the corresponding packages or update your system and try again.
If that doesn't work, the issue might be Anaconda not linking to the external gcc compiler. Try again after installing the Anaconda compiler with:
conda install gcc_linux-64
ModuleNotFoundError: No module named 'Cython' (Windows): Install or update Visual Studio Build Tools and try compiling again.
Errors related to Gepard operation
no module named gepard: Please make sure that you are attempting to start Gepard from its parent folder, i.e. the location containing the folder "gepard".
ImportError: cannot import name 'tsp': If your setup includes multiple Anaconda environments, tsp build and gepard operation must be done in the same environment.