diff --git a/test.py b/test.py
index c99cd7e..6bed1f5 100644
--- a/test.py
+++ b/test.py
@@ -5,9 +5,10 @@
 import numpy as np
 import torch
 import architecture as arch
+from pathlib import Path
 
 model_path = sys.argv[1]  # models/RRDB_ESRGAN_x4.pth OR models/RRDB_PSNR_x4.pth
-device = torch.device('cuda')  # if you want to run on CPU, change 'cuda' -> cpu
+device = torch.device('cpu')  # if you want to run on CPU, change 'cuda' -> cpu
 # device = torch.device('cpu')
 
 test_img_folder = 'LR/*'
@@ -19,9 +20,12 @@
 for k, v in model.named_parameters():
     v.requires_grad = False
 model = model.to(device)
+model_used = Path('{:s}'.format(model_path)).stem # get model name to simple string for filename use
 
 print('Model path {:s}. \nTesting...'.format(model_path))
 
+
+amend = 2 #File already exists, lets amend a 2 to the end of the file name
 idx = 0
 for path in glob.glob(test_img_folder):
     idx += 1
@@ -37,4 +41,13 @@
     output = model(img_LR).data.squeeze().float().cpu().clamp_(0, 1).numpy()
     output = np.transpose(output[[2, 1, 0], :, :], (1, 2, 0))
     output = (output * 255.0).round()
-    cv2.imwrite('results/{:s}_rlt.png'.format(base), output)
+
+    while os.path.exists('results/{:s}_%s_%s.png'.format(base) % (model_used, amend)):
+        amend += 1
+
+    if os.path.exists('results/{:s}_%s.png'.format(base) % model_used):
+        cv2.imwrite('results/{:s}_%s_%s.png'.format(base) % (model_used, amend), output)
+
+    else: 
+        cv2.imwrite('results/{:s}_%s.png'.format(base) % model_used, output)
+