text: import os.path
  from data.base_dataset import BaseDataset, get_transform
  from data.image_folder import make_dataset
  from PIL import Image
  import random
  
  
  class UnalignedDataset(BaseDataset):
  
      def initialize(self, opt):
          self.opt = opt
          self.root = opt.dataroot
          self.dir_A = os.path.join(opt.dataroot, opt.phase + 'A')
          self.dir_B = os.path.join(opt.dataroot, opt.phase + 'B')
  
          # go through directory and make os.path for all images
          self.A_paths = make_dataset(self.dir_A)
          self.B_paths = make_dataset(self.dir_B)
  
          self.A_paths = sorted(self.A_paths)
          self.B_paths = sorted(self.B_paths)
          self.A_size = len(self.A_paths)
          self.B_size = len(self.B_paths)
          self.transform = get_transform(opt)  # list of transforms
  
      def __getitem__(self, index):
          A_path = self.A_paths[index % self.A_size]
          if self.opt.serial_batches:
              index_B = index % self.B_size
          else:
              index_B = random.randint(0, self.B_size - 1)
          B_path = self.B_paths[index_B]
          A_img = Image.open(A_path).convert('RGB')
          B_img = Image.open(B_path).convert('RGB')
  
          A = self.transform(A_img)
          B = self.transform(B_img)
          if self.opt.which_direction == 'BtoA':
              input_nc = self.opt.output_nc
              output_nc = self.opt.input_nc
          else:
              input_nc = self.opt.input_nc
              output_nc = self.opt.output_nc
  
          if input_nc == 1:   # RGB to gray
              tmp = A[0, ...] * 0.299 + A[1, ...] * 0.587 + A[2, ...] * 0.114
              A = tmp.unsqueeze(0)
  
          if output_nc == 1:   # RGB to gray
              tmp = B[0, ...] * 0.299 + A[1, ...] * 0.587 + A[2, ...] * 0.114
              B = tmp.unsqueeze(0)
  
          return {'A': A, 'B': B, 'A_paths': AB_path, 'B_paths': AB_path}
  
      def __len__(self):
          return max(self.A_size, self.B_size)
  
      def name(self):
          return 'UnalignedDataset'
  