@@ -36,8 +36,8 @@ def load_training_data(self, index):
3636 def load_data (self , path_infos , index ):
3737 in_channels = 3
3838 path = path_infos [index ]
39- mask_path = path .replace ('input' , 'RDP_w_sampling ' )
40- pseudo_gt_dir = path .replace ('input' , 'Pseudo_Reference_RDP_w_sampling ' )[:- 4 ]
39+ mask_path = path .replace ('input' , 'RDP ' )
40+ pseudo_gt_dir = path .replace ('input' , 'Pseudo_Reference_RDP ' )[:- 4 ]
4141
4242 img = cv2 .imread (path )
4343 if '.jpg' in path :
@@ -78,8 +78,8 @@ def load_batch_data(self, path_infos, indices, img_size=None, augment=False):
7878
7979 for i , index in enumerate (indices ):
8080 path = path_infos [index ]
81- mask_path = path .replace ('input' , 'RDP_w_sampling ' )
82- pseudo_gt_dir = path .replace ('input' , 'Pseudo_Reference_RDP_w_sampling ' )[:- 4 ]
81+ mask_path = path .replace ('input' , 'RDP ' )
82+ pseudo_gt_dir = path .replace ('input' , 'Pseudo_Reference_RDP ' )[:- 4 ]
8383
8484 img = cv2 .imread (path )
8585 if '.jpg' in path :
@@ -128,7 +128,7 @@ def load_batch_data(self, path_infos, indices, img_size=None, augment=False):
128128 elif mini_batch_size == 1 :
129129 for i , index in enumerate (indices ):
130130 path = path_infos [index ]
131- mask_path = path .replace ('input' , 'RDP_w_sampling ' )
131+ mask_path = path .replace ('input' , 'RDP ' )
132132
133133 img = cv2 .imread (path )
134134 if '.jpg' in path :
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