Copyright (c) 2006 - 2015 Gerlich Lab, IMBA Vienna, Austria
CellCognition is distributed under the terms of LGPL.
www.cellcognition.org
doc.cellcognition.org
To compile the ccore extension you need to adopt the library/include paths in the setup.cfg accordingly.
Dependcies are:
- libvigraimpex
- libtiff
Remove the build- and dist directories and also the file cecog/ccore/_cecog.so(pyd)
python setup.py build_ext --inplace
python setup.py install --prefix=<path-to-prefix>
Run the make file.
Run build_win64_bin.bat
The demo data contains:
- A small set of raw images (10 timepoints of H2b-aTubulin).
- The two classifiers for H2b and aTubulin to test classification.
- A pre-configured settings file which is loaded on start-up.
Using the demo data it is possible to:
- Run segmentation on H2b (primary) and aTubulin (secondary) channels.
- Test the classifier for H2b and aTubulin channels.
#####Files:
- Settings
- demo_settings.conf, the settings file which is loaded on startup
- graph_primary.xml, an example for a graph definition file (H2b)
- graph_secondary.xml, an example for a graph definition file (Tubulin)
- Classifiers
- H2B
- aTubulin
- Images
- first 10 timeframes from the H2B-Tubulin image set.
The demo data included in the installer contains only a hand full of images i.e. 10 time frames. Please download the bigger H2B-Tubulin image set to perform:
- Classifier training and cross validation
- Event selection
- Error correction
It contains 206 frames with ~3.6 min. timelapse. Use the same settings except for the parameter Duration [post]. It is recommended to increase it to 35 frames.