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Clinical Face Phenotype Space pipeline. v1.2 Copyright (c) 06/5/2014 Christoffer Nellaker Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. Please cite the original publication: http://dx.doi.org/10.7554/eLife.02020 ############################################# # How to use code v1.2 # ------------ Installation of source code. ------------ Download the code from https://github.com/ChristofferNellaker/Clinical_Face_Phenotype_Space_Pipeline Place in desired folder. Install dependencies (list below) Configure pipeline.ini with relative paths to models and dependencies. Configure image_folders.ini to point to folders with images to be analysed. Configure path_to_meta_data_parser.py Alternatively, there is an Ubuntu Virtual Box VM with a functioning compiled pipeline available throught the vagrand cloud chrisn/CFPS_VM ------------ Dependencies ------------ . Designed to run on Linux based operating systems. . Python 2.7x https://www.python.org/ . Python modules . Ruffus http://www.ruffus.org.uk/ . optparse https://docs.python.org/2/library/optparse.html . Automatic Naming of Characters in TV Video code set http://www.robots.ox.ac.uk/~vgg/research/nface/index.html . OpenCV http://opencv.org/ Developed on v2.4 . Sqlite3 https://sqlite.org/ . Sqlite3 driver for MATLAB http://www.cs.sunysb.edu/~kyamagu/software/matlab-sqlite3-driver/ . Serialize for MATLAB http://www.mathworks.com/matlabcentral/fileexchange/29457-serialize-deserialize/content/serialize.m . MATLAB 2011b or later with a license and access to the Matlab compiler . LIBSVM for MATLAB http://www.csie.ntu.edu.tw/~cjlin/libsvm/ -------------------------------------------------- Running the Clinical Face Phenotype Space pipeline. -------------------------------------------------- Check the pipeline printout cmd> python ./Clinical_Face_Phenotype_Space.py -vvvvn Run the pipeline cmd> python ./Clinical_Face_Phenotype_Space.py -vvvv Results will be output into: ./output_Diag_P0P1_acc.tab ./output_CIF_acc.tab -------------------------------------------------- Some notes on design principles applied -------------------------------------------------- . The MATLAB scripts are compiled as the first step of the pipeline which allows them to be run in parallel. . The variables for each script are passed in simple text files managed by the python ruffus pipeline. . Matlab output is stored in the sqlite3 database. The functions serialize and deserialise are used to encode these.
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