diff --git a/README.md b/README.md
index 1e6c5d31a8d925fd8475e29a6aabf333af48dd1e..72f97ca27ce3c6def57937ed7002a260d2de00cd 100755
--- a/README.md
+++ b/README.md
@@ -33,6 +33,7 @@ We provide scripts for reproducing all the results from our paper. You can train
 * **imageio**
 * matplotlib
 * tqdm
+* cv2 >= 3.xx (Only if you use video input/output)
 
 **Recent updates**
 
diff --git a/src/data/srdata.py b/src/data/srdata.py
index a7c9a947fdf492f640fc329980ff43c4efcdb8c0..5dcf99d2932d2d987e54663bba9479645ee2f924 100644
--- a/src/data/srdata.py
+++ b/src/data/srdata.py
@@ -77,7 +77,10 @@ class SRData(data.Dataset):
         if train:
             n_patches = args.batch_size * args.test_every
             n_images = len(args.data_train) * len(self.images_hr)
-            self.repeat = max(n_patches // n_images, 1)
+            if n_images == 0:
+                self.repeat = 0
+            else:
+                self.repeat = max(n_patches // n_images, 1)
 
     # Below functions as used to prepare images
     def _scan(self):
diff --git a/src/main.py b/src/main.py
index 5ff359de1111c25021df1acf2205add56eac56b4..a6093f70bfb25d348e3c0b1b820b92a2ef060071 100644
--- a/src/main.py
+++ b/src/main.py
@@ -6,12 +6,12 @@ import model
 import loss
 from option import args
 from trainer import Trainer
-from videotester import VideoTester
 
 torch.manual_seed(args.seed)
 checkpoint = utility.checkpoint(args)
 
 if args.data_test == 'video':
+    from videotester import VideoTester
     model = model.Model(args, checkpoint)
     t = VideoTester(args, model, checkpoint)
     t.test()