old_contents: import torch
  import torchvision
  import torchvision.transforms as transforms
  import active_vision_dataset
  
  
  
  #from pytorch tutorial
  
  
  #create a transform to normalize the images
  transform=transforms.Compose([transforms.ToTensor(),
                                transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
                               ])
  
  #create the dataset instance
  #use the default training scenes
  trainset = active_vision_dataset.AVD(root='/playpen/ammirato/Data/RohitData', 
                                      train=True, transform=transform)
  
  #create a torch Data loader instance
  trainloader = torch.utils.data.DataLoader(trainset,batch_size=4,shuffle=True)
  
  #create a torch iterator over the data
  dataiter = iter(trainloader)
  
  #get one batch of images and labels
  images,labels = dataiter.next()
  
  
new_contents: import torch
  import torchvision
  import torchvision.transforms as transforms
  import active_vision_dataset
  
  
  #USE 1
  ##########from pytorch tutorial
  
  #create a transform to normalize the images
  transform=transforms.Compose([transforms.ToTensor(),
                                transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
                               ])
  
  #create the dataset instance
  #use the default training scenes
  trainset = active_vision_dataset.AVD(root='/playpen/ammirato/Data/RohitData', 
                                      train=True, transform=transform)
  
  #create a torch Data loader instance
  trainloader = torch.utils.data.DataLoader(trainset,batch_size=4,shuffle=True)
  
  #create a torch iterator over the data
  dataiter = iter(trainloader)
  
  #get one batch of images and labels
  images,labels = dataiter.next()
  
  
  
  
  
  
  #USE 2 
  ##########not using pytorch, using custom scene list
  
  #use images/labels from these scenes only
  scene_list = ['Home_01_1', 'Home_02_1', 'Home_03_1']
  
  trainset = active_vision_dataset.AVD(root='/playpen/ammirato/Data/RohitData', 
                                      scene_list=scene_list)
  
  #get an image and its label(s) 
  image,labels = trainset[0]
  #get the next image and its label(s)
  image2,labels2 = trainset[1]
  
  
subject: add use 2