text: path_to_single = r"E:\Datasets\BraTS challenge\BraTS2021_00621"
  
  path_to_BraTS2021 = "E:\Datasets\BraTS challenge\RSNA_ASNR_MICCAI_BraTS2021_TrainingData"
  
  ## What is flair 
  ## What is seg 
  ## What is t1 
  ## What is t1ce 
  ## What is t2?
  
  ## So we need to unzip the data points 
  from utils import unzip_all_files_folder_2, convert_nii_to_png
  ## function works for a single folder we can for loop all folders
  # unzip_all_files_folder_2(path_to_single)
  convert_nii_to_png(path_to_single)
  ## read in the nitfi files into numpy arrays 
  
  import numpy as np
  import nibabel as nib
  import itk
  # Packages 
  # itkwidgets
  # nibabel 
  # img = nib.load(example_filename)
  # a = np.array(img.dataobj)
  
  
  
  ## visualize the data somehow
  
  ## Training set and the test set
  
  
  
  ## Apply Agglomerative Hierarchical clustering
  ## Apply Divisive Hierarchical clustering technique 
  
  ## What I found interesting Calculate the similarity between two clusters?
  # MIN, MAX, Group Average, Distance between Centroids, Ward's Method's ## How can any of these be similar to 
  # Dice SImilarity Coefficient or Hausdorff distance 
  # https://towardsdatascience.com/understanding-the-concept-of-hierarchical-clustering-technique-c6e8243758ec