Reading our data into a numpy array

reading_landcovernet_data

inputs_dir = '/content/landcovernet/inputs'  # The directory where our input resides
targets_dir = '/content/landcovernet/targets' # The directory where our target resides
# First stack all the bands togather

def process_tiffs(inputs_dir, target_dir):
  data = []
  sub_dir_list = []
  images_target = {}
  stacked_imgs = []
  list_bands = []
  for sub_dir in os.listdir(inputs_dir):
    # Store the images dir and their target
    sub_dir_list.append(os.path.join(inputs_dir, sub_dir))
  print(sub_dir_list)

  for image_dir in sub_dir_list:
    # Get the rgb version
    rgb = get_rgb(image_dir)
    custom_img = get_cust_img(image_dir)
    mask = get_img_mask(targets_dir, image_dir)
    mask = process_masks(mask) # get the six classes
    # Dictionary of image and its target in numpy format
    images_target = {}
    images_target = {
        'input' : custom_img,
        'input_rgb' : rgb,
        'mask' : mask,
    }
 
    stacked_imgs.append(images_target) # list of dict
 
  return stacked_imgs
  #return images
images_target = process_tiffs(inputs_dir, targets_dir)