Update README.md

README.md

@@ -26,17 +26,33 @@ Conference
 We would like to build a data-driven model to reconstruct CT images. The model should be evaluated on the LoDoPaB challenge. (https://lodopab.grand-challenge.org/) 
 
 ## How to run
+We will be using the jupyter notebook from the server mathgpu1, provided by Uni-Hamburg.   
 
 # clone project   
 git clone https://gitlab.rrz.uni-hamburg.de/BAT9096/deepinverse.git
 
 # install project
+Not yet ready.    
 
 # run module (example: mnist as your main contribution)
+We will using the data provided by zonodo.org.  LoDoPaB-CT Dataset.
+There will be two data sets, 1. with more than 50GB as zip and the other 3GB as Zip. We will focus more on training the 3GB data first.
 
 
 ## Imports
-Not yet completed
+So far, we are using the following:
+pytorch-lightning
+torch 
+torchvision 
+numpy
+scipy
+matplotlib
+scikit-learn
+scikit-image
+jupyter
+imageio
+
+
 
 ### Citation   
 ```