Update data/single_dataset.py

data/single_dataset.py

@@ -16,19 +16,25 @@ class SingleDataset(BaseDataset):
             opt (Option class) -- stores all the experiment flags; needs to be a subclass of BaseOptions
         """
         BaseDataset.__init__(self, opt)
-
-        self.A_path = opt.image_path  # Assume 'image_path' is a new option for single image input
-
+        self.A_paths = sorted(make_dataset(opt.dataroot, opt.max_dataset_size))
         input_nc = self.opt.output_nc if self.opt.direction == 'BtoA' else self.opt.input_nc
         self.transform = get_transform(opt, grayscale=(input_nc == 1))
 
     def __getitem__(self, index):
-        """Return a data point and its metadata information."""
-        A_img = Image.open(self.A_path).convert('RGB')
+        """Return a data point and its metadata information.
+
+        Parameters:
+            index - - a random integer for data indexing
+
+        Returns a dictionary that contains A and A_paths
+            A(tensor) - - an image in one domain
+            A_paths(str) - - the path of the image
+        """
+        A_path = self.A_paths[index]
+        A_img = Image.open(A_path).convert('RGB')
         A = self.transform(A_img)
-        return {'A': A, 'A_paths': self.A_path}
+        return {'A': A, 'A_paths': A_path}
 
     def __len__(self):
         """Return the total number of images in the dataset."""
-        return 1  # Always 1 for single image input
-
+        return len(self.A_paths)