from imfeatbox import ImFEATbox

## Example script to carry out the feature extraction
#
# This script calls all feature extraction allgorithms provided by
# ImFEATbox.
#
# Output:   feat_vec: an [NxM] array of M features extracted from N 2D images.
#
# The basic steps to successfully carry out the feature extraction:
# 1.)   Import the images of which you want to extract the features.
#       Note: this script expects images to be cell arrays
# 2.)   Set typeflag to define which features you wish to extract.
#       For more information about typeflag: see README.txt
# 3.)   Set parameters needed for some feature extraction algorithms.
#       Note: default values are tuned for use with automated MR image
#       quality assessment, you might need to change them according to your
#       application
# 4.)   Choose wheather or not you wish to use additional tools
#       (preprocessing, visualization).
#
# ************************************************************************
# Implemented for MRI feature extraction by the Department of Diagnostic
# and Interventional Radiology, University Hospital of Tuebingen, Germany
# and the Institute of Signal Processing and System Theory University of
# Stuttgart, Germany. Last modified: February 2017
#
# This implementation is part of ImFEATbox, a toolbox for image feature
# extraction and analysis. Available online at:
# https://github.com/annikaliebgott/ImFEATbox
#
# Contact: annika.liebgott@iss.uni-stuttgart.de
#          thomas.kuestner@iss.uni-stuttgart.de
# ************************************************************************

## add necessary paths
addpath(genpath([pwd,filesep,'features_matlab']))

## import images to extract the features from
# Note: this script expects images to be saved as cell arrays
data = load(['dataset',filesep,'images.mat'])
images = data.images


## get available/implemented features
#cFeatures = fExtractFeatures([],[], '-getFeatures')
cFeatures = ImFEATbox.getFeatures()

## extract all features
feat_vector = []
for iI=1:length(images)
    feat_vector = cat(1,fExtractFeatures(images{iI},[],'all'))
end


## extract transformation features with feature parameters (specified in file)
sFeatureParameter = [pwd, filesep, 'parameters_ImFEATBox_def.m']
feat_vector = []
for iI=1:length(images)
    feat_vector = cat(1,fExtractFeatures(images{iI},[],'transform', sFeatureParameter))
end


## extract specific features with feature parameters (specified in file)
sFeatureParameter = [pwd, filesep, 'parameters_ImFEATBox_def.m']
feat_vector = []
for iI=1:length(images)
    feat_vector = cat(1,fExtractFeatures(images{iI},[],{'intensity', 'mser'}, sFeatureParameter))
end