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Deep learning toolkit EEG classification using Keras
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3catz/keras_eeg_deeplearning
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----------------------------------------- ---- PRELIMINARIES ---- ----------------------------------------- *** must make sure that cuda libraries are on the PATH *** *** make sure that requirements.txt has tensorflow-gpu==1.4.0 *** FOR PYTHON 3.6.0: virtualenv -p python3 venv module load python/3.6.0 module load cuda/8.0 module load cudnn/7 source venv/bin/activate (venv) pip install -r requirements.txt (venv) STEP3_TrainNeuralNetwork.py LD_LIBRARY_PATH=/usr/local/cuda-6.5/lib64: PATH=/home/mohammad/anaconda2/bin:/usr/local/cuda-6.5/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin: deactivate ----------------------------------------- ---- STEP1_ImportMatCovariates.py ---- ----------------------------------------- Imports the various covariates (age, cause, rosc, cpc, etc.), and saves them as .npy files in the 'python_covariates' directory ----------------------------------------- ---- STEP2_PrepImages.py ---- ----------------------------------------- Converts spatio-temporal topoplots in '/images' from matlab format to .npy files. Also reshapes the data so that it can be used by the Keras DNN framework and samples each subject multiple times. ----------------------------------------- ---- STEP3_Train3DCNN.py ---- ----------------------------------------- Train a 3D CNN ----------------------------------------- ---- generate_hyperparameters.py ---- ----------------------------------------- Generates a large set of hyperparamters for training ----------------------------------------- ---- runNN.py ---- ----------------------------------------- Trains many models for the given hyperparameters and neatly stores the results.
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