diff --git a/codes/data/LQGT_dataset.py b/codes/data/LQGT_dataset.py
index 587456a6..d1fa1f50 100644
--- a/codes/data/LQGT_dataset.py
+++ b/codes/data/LQGT_dataset.py
@@ -90,7 +90,7 @@ class LQGTDataset(data.Dataset):
 
         # get the pix image
         if self.paths_PIX is not None:
-            PIX_path = self.paths_PIX[index]
+            PIX_path = self.paths_PIX[index % len(self.paths_PIX)]
             img_PIX = util.read_img(self.PIX_env, PIX_path, resolution)
             if self.opt['color']:  # change color space if necessary
                 img_PIX = util.channel_convert(img_PIX.shape[2], self.opt['color'], [img_PIX])[0]
@@ -123,7 +123,10 @@ class LQGTDataset(data.Dataset):
             H, W, _ = img_GT.shape
 
             # using matlab imresize
-            img_LQ = util.imresize_np(img_GT, 1 / scale, True)
+            if scale == 1:
+                img_LQ = img_GT
+            else:
+                img_LQ = util.imresize_np(img_GT, 1 / scale, True)
             if img_LQ.ndim == 2:
                 img_LQ = np.expand_dims(img_LQ, axis=2)
 
@@ -160,11 +163,14 @@ class LQGTDataset(data.Dataset):
                 img_GT = img_GT[rnd_h_GT:rnd_h_GT + GT_size, rnd_w_GT:rnd_w_GT + GT_size, :]
                 img_PIX = img_PIX[rnd_h_GT:rnd_h_GT + GT_size, rnd_w_GT:rnd_w_GT + GT_size, :]
             else:
-                img_LQ = cv2.resize(img_LQ, (LQ_size, LQ_size), interpolation=cv2.INTER_LINEAR)
+                if img_LQ.shape[0] != LQ_size:
+                    img_LQ = cv2.resize(img_LQ, (LQ_size, LQ_size), interpolation=cv2.INTER_LINEAR)
                 if img_GAN is not None:
                     img_GAN = cv2.resize(img_GAN, (LQ_size, LQ_size), interpolation=cv2.INTER_LINEAR)
-                img_GT = cv2.resize(img_GT, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
-                img_PIX = cv2.resize(img_PIX, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
+                if img_GT.shape[0] != GT_size:
+                    img_GT = cv2.resize(img_GT, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
+                if img_PIX.shape[0] != GT_size:
+                    img_PIX = cv2.resize(img_PIX, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
 
                 if 'doResizeLoss' in self.opt.keys() and self.opt['doResizeLoss']:
                     r = random.randrange(0, 10)
@@ -224,7 +230,7 @@ class LQGTDataset(data.Dataset):
 
         if LQ_path is None:
             LQ_path = GT_path
-        d = {'LQ': img_LQ, 'GT': img_GT, 'PIX': img_PIX, 'LQ_path': LQ_path, 'GT_path': GT_path}
+        d = {'LQ': img_LQ, 'GT': img_GT, 'ref': img_PIX, 'LQ_path': LQ_path, 'GT_path': GT_path}
         if img_GAN is not None:
             d['GAN'] = img_GAN
         return d