updated versions

Author: baumgach

README.md

@@ -50,15 +50,10 @@ Author of this code:
 
 ## How to get the code to run:
 
- * Step 1: Set up a virtual environment (e.g. conda or virtualenv) with Python 3 (I used 3.4.3), and tensorflow 
- (I used version 1.2). There is a requirements.txt file so `pip install -r requirements.txt`
-  should work.
-
-Potential caveat: We had to use the dev version of skimage to allow for 3D image 
-resampling of the ADNI data. Previously, we had problems to compile it with anything 
-else but Python 3.4.3. However, if you don't need this function 
-(which you don't on 2D data) you can simply use the normal `pip install scikit-image`.
-
+ * Step 1: Set up a virtual environment (e.g. conda or virtualenv) with Python 3 (I use Python 3.5), and tensorflow 
+ (I used version 1.12). There is a requirements.txt file so `pip install -r requirements.txt`
+  should work. Tensorflow is not included in the requirements file so you can decide whether you want
+  to install the GPU or CPU version. 
 
  * Step 2: Open `config/system.py` and change the settings to match your system.
 

SGE_scripts/run_on_host.sh

@@ -9,7 +9,7 @@
 # Author: Christian F. Baumgartner (c.f.baumgartner@gmail.com)
 
 ## SET THE FOLLOWING VARIABLES ACCORDING TO YOUR SYSTEM ##
-CUDA_HOME=/scratch_net/bmicdl03/libs/cuda-8.0-bmic
+CUDA_HOME=/scratch_net/bmicdl03/libs/cuda-9.0
 PROJECT_HOME=/scratch_net/bmicdl03/code/python/vagan-code/
 VIRTUAL_ENV_PATH=/scratch_net/bmicdl03/code/python/environments/tensorflow1.2-gpu/
 

SGE_scripts/run_on_host_short.sh

@@ -9,7 +9,7 @@
 # Author: Christian F. Baumgartner (c.f.baumgartner@gmail.com)
 
 ## SET THE FOLLOWING VARIABLES ACCORDING TO YOUR SYSTEM ##
-CUDA_HOME=/scratch_net/bmicdl03/libs/cuda-8.0-bmic
+CUDA_HOME=/scratch_net/bmicdl03/libs/cuda-9.0
 PROJECT_HOME=/scratch_net/bmicdl03/code/python/vagan-code/
 VIRTUAL_ENV_PATH=/scratch_net/bmicdl03/code/python/environments/tensorflow1.2-gpu/
 
@@ -26,7 +26,7 @@ VIRTUAL_ENV_PATH=/scratch_net/bmicdl03/code/python/environments/tensorflow1.2-gp
 
 # Host and gpu settings
 #$ -l gpu
-##$ -l hostname=bmicgpu01   ## <-------------- Comment in or out to force a specific machine
+#$ -l hostname=bmicgpu01   ## <-------------- Comment in or out to force a specific machine
 
 ## stderr and stdout are merged together to stdout
 #$ -j y

config/system.py

@@ -11,7 +11,7 @@
 # Full paths are required because otherwise the code will not know where to look
 # when it is executed on one of the clusters.
 
-at_biwi = True  # Are you running this code from the ETH Computer Vision Lab (Biwi)?
+at_biwi = False  # Are you running this code from the ETH Computer Vision Lab (Biwi)?
 
 project_root = '/scratch_net/bmicdl03/code/python/vagan-code'
 test_data_root = None

requirements.txt

@@ -1,12 +1,29 @@
-
-cython>=0.23
-setuptools>=35.0
-numpy==1.13.0
-nibabel==2.1.0
-h5py==2.7.0
-matplotlib==2.0.1
-pandas==0.20.1
-scipy==0.19.1
-
--e git+https://github.com/scikit-image/scikit-image/#egg=scikit-image
-
+absl-py==0.7.1
+astor==0.8.0
+cycler==0.10.0
+decorator==4.4.0
+gast==0.2.2
+grpcio==1.22.0
+h5py==2.9.0
+imageio==2.5.0
+joblib==0.13.2
+Keras-Applications==1.0.8
+Keras-Preprocessing==1.1.0
+kiwisolver==1.1.0
+Markdown==3.1.1
+matplotlib==3.0.3
+networkx==2.3
+nibabel==2.4.1
+numpy==1.16.4
+Pillow==6.1.0
+pkg-resources==0.0.0
+protobuf==3.9.0
+pyparsing==2.4.0
+python-dateutil==2.8.0
+PyWavelets==1.0.3
+scikit-image==0.15.0
+scikit-learn==0.21.2
+scipy==1.3.0
+six==1.12.0
+termcolor==1.1.0
+Werkzeug==0.15.5

vagan/experiments/adni_experiment.py

@@ -20,7 +20,7 @@
 label_name = 'diagnosis'
 nlabels = len(label_list)
 data_root = '/usr/bmicnas01/data-biwi-01/bmicdatasets/Processed/ADNI_Christian/ADNI_allfixed_allPP_robex'
-preproc_folder = os.path.join(sys_config.project_root,'data/preproc_data/allfixed_noskull')
+preproc_folder = '/srv/beegfs02/scratch/baumgach_data/data/preproc_data/vagan_adni/'
 rescale_to_one = True
 image_z_slice = 56  # for displaying images during training
 

vagan/experiments/synthetic_experiment.py

@@ -5,7 +5,7 @@
 from vagan.network_zoo.nets2D import critics, mask_generators
 
 # Experiment name
-experiment_name = 'synth_vagan'
+experiment_name = 'synth_vagan_rerun'
 
 # Model settings
 critic_net = critics.C3D_fcn_16_2D