title: Create a list where the even indexes have a path to a positive category and odd indexes have a path to the negative category
body: <p>I'm basically sorting my CNN images into a list with even and odd indexing. Even index will have positive images and odd index will have negative images. Here's  my code so far:</p>
  
  <pre><code>from PIL import Image
  import matplotlib.pyplot as plt
  import os
  import glob
  import torch
  from torch.utils.data import Dataset
  
  def show_data(data_sample, shape = (28, 28)):
      plt.imshow(data_sample[0].numpy().reshape(shape), cmap='gray')
      plt.title('y = ' + data_sample[1])
  
  directory="/resources/data"
  negative='Negative'
  negative_file_path=os.path.join(directory,negative)
  negative_files=[os.path.join(negative_file_path,file) for file in  os.listdir(negative_file_path) if file.endswith(".jpg")]
  negative_files.sort()
  negative_files[0:3]
  
  positive="Positive"
  positive_file_path=os.path.join(directory,positive)
  positive_files=[os.path.join(positive_file_path,file) for file in  os.listdir(positive_file_path) if file.endswith(".jpg")]
  positive_files.sort()
  positive_files[0:3]
  
  n = len(negative_files)
  p = len(positive_files)
  number_of_samples = n + p
  print(number_of_samples)
  
  Y=torch.zeros([number_of_samples])
  
  Y=Y.type(torch.LongTensor)
  Y.type()
  
  Y[::2]=1
  Y[1::2]=0
  </code></pre>