clean code

ppgan/datasets/aligned_dataset.py

@@ -61,7 +61,6 @@ class AlignedDataset(BaseDataset):
         B = B_transform(B)
 
         return {'A': A, 'B': B, 'A_paths': AB_path, 'B_paths': AB_path}
-        # return A, B, index #{'A': A, 'B': B, 'A_paths': AB_path, 'B_paths': AB_path}
 
     def __len__(self):
         """Return the total number of images in the dataset."""

ppgan/datasets/base_dataset.py

@@ -65,27 +65,24 @@ def get_transform(cfg, params=None, grayscale=False, method=cv2.INTER_CUBIC, con
     transform_list = []
     if grayscale:
         print('grayscale not support for now!!!')
-        # transform_list.append(transforms.Grayscale(1))
+        pass
     if 'resize' in cfg.preprocess:
         osize = (cfg.load_size, cfg.load_size)
-        # print('os size:', osize)
         transform_list.append(transforms.Resize(osize, method))
     elif 'scale_width' in cfg.preprocess:
         print('scale_width not support for now!!!')
-        # transform_list.append(transforms.Lambda(lambda img: __scale_width(img, cfg.load_size, cfg.crop_size, method)))
+        pass
 
     if 'crop' in cfg.preprocess:
-        # print('crop not support for now!!!', cfg.crop_size)
-        # transform_list.append(T.RandomCrop(cfg.crop_size))
+
         if params is None:
             transform_list.append(T.RandomCrop(cfg.crop_size))
         else:
-            # print('crop not support for now!!!')
             transform_list.append(T.Crop(params['crop_pos'], cfg.crop_size))
 
     if cfg.preprocess == 'none':
         print('preprocess not support for now!!!')
-        # transform_list.append(transforms.Lambda(lambda img: __make_power_2(img, base=4, method=method)))
+        pass
 
     if not cfg.no_flip:
         if params is None:
@@ -97,48 +94,3 @@ def get_transform(cfg, params=None, grayscale=False, method=cv2.INTER_CUBIC, con
         transform_list += [transforms.Permute(to_rgb=True)]
         transform_list += [transforms.Normalize((127.5, 127.5, 127.5), (127.5, 127.5, 127.5))]
     return transforms.Compose(transform_list)
-
-
-def __make_power_2(img, base, method=Image.BICUBIC):
-    ow, oh = img.size
-    h = int(round(oh / base) * base)
-    w = int(round(ow / base) * base)
-    if h == oh and w == ow:
-        return img
-
-    __print_size_warning(ow, oh, w, h)
-    return img.resize((w, h), method)
-
-
-def __scale_width(img, target_size, crop_size, method=Image.BICUBIC):
-    ow, oh = img.size
-    if ow == target_size and oh >= crop_size:
-        return img
-    w = target_size
-    h = int(max(target_size * oh / ow, crop_size))
-    return img.resize((w, h), method)
-
-
-def __crop(img, pos, size):
-    ow, oh = img.size
-    x1, y1 = pos
-    tw = th = size
-    if (ow > tw or oh > th):
-        return img.crop((x1, y1, x1 + tw, y1 + th))
-    return img
-
-
-def __flip(img, flip):
-    if flip:
-        return img.transpose(Image.FLIP_LEFT_RIGHT)
-    return img
-
-
-def __print_size_warning(ow, oh, w, h):
-    """Print warning information about image size(only print once)"""
-    if not hasattr(__print_size_warning, 'has_printed'):
-        print("The image size needs to be a multiple of 4. "
-              "The loaded image size was (%d, %d), so it was adjusted to "
-              "(%d, %d). This adjustment will be done to all images "
-              "whose sizes are not multiples of 4" % (ow, oh, w, h))
-        __print_size_warning.has_printed = True

ppgan/datasets/single_dataset.py

@@ -33,15 +33,9 @@ class SingleDataset(BaseDataset):
             A_paths(str) - - the path of the image
         """
         A_path = self.A_paths[index]
-        # A_img = Image.open(A_path).convert('RGB')
         A_img = cv2.imread(A_path)
         A = self.transform(A_img)
-        # items = {}
-        # if self.cfg.direction == 'AtoB':
-        #     items = {'A': A, 'A_paths': A_path}
-        # else:
-        #     items = {'B': A, 'B_paths': A_path}
-        # return items
+
         return {'A': A, 'A_paths': A_path}
 
     def __len__(self):