--- a
+++ b/mains/main_ceVAE_Zimmerer.py
@@ -0,0 +1,23 @@
+#!/usr/bin/env python
+import tensorflow as tf
+
+from models import context_encoder_variational_autoencoder_Zimmerer
+from trainers.ceVAE import ceVAE
+from utils import Evaluation
+from utils.default_config_setup import get_config, get_options, get_datasets, Dataset
+
+tf.reset_default_graph()
+dataset = Dataset.BRAINWEB
+options = get_options(batchsize=8, learningrate=0.0001, numEpochs=1, zDim=128, outputWidth=128, outputHeight=128)
+options['data']['dir'] = options["globals"][dataset.value]
+datasetHC, datasetPC = get_datasets(options, dataset=dataset)
+config = get_config(trainer=ceVAE, options=options, optimizer='ADAM', intermediateResolutions=[8, 8], dropout_rate=0.1, dataset=datasetHC)
+
+# Create an instance of the model and train it
+model = ceVAE(tf.Session(), config, network=context_encoder_variational_autoencoder_Zimmerer.context_encoder_variational_autoencoder_Zimmerer)
+
+# Train it
+model.train(datasetHC)
+
+# Evaluate
+Evaluation.evaluate(datasetPC, model, options, description=f"{type(datasetHC).__name__}-{options['threshold']}", epoch=str(options['train']['numEpochs']))