Update README.md

README.md

@@ -51,6 +51,7 @@ After training is conducted, a .h5 model will result from training runs. This mo
 Users may want to run the training provided on an HPC system. In this case, what is required is running train_set.py in the training folder. The training_data folder contains the training_data.csv file, which can be edited to run the required data. The input in the .csv file includes the path location of the training data, the weight file location (that is the initial .h5 file), the batch number used in the run, the network model (e.g., resnet101), and number of epochs for runs. See PixelLib for further details on these parameters.
 
 <B>Subfolders</B>
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 For more details on how different packages, or subfolders, are used then please see those packages and code inside, which have comments on individual methods.
 
 The first subfolder is the gui folder, which contains the GUI components. The train_gui.py module applies the main training GUI, while segment_gui.py applies the segmentation.