diff --git a/u2net_test.py b/u2net_test.py
index 8b501c6..02f0300 100644
--- a/u2net_test.py
+++ b/u2net_test.py
@@ -37,7 +37,7 @@ def save_output(image_name,pred,d_dir):
     predict_np = predict.cpu().data.numpy()
 
     im = Image.fromarray(predict_np*255).convert('RGB')
-    img_name = image_name.split("/")[-1]
+    img_name = image_name.split(os.sep)[-1]
     image = io.imread(image_name)
     imo = im.resize((image.shape[1],image.shape[0]),resample=Image.BILINEAR)
 
@@ -57,11 +57,12 @@ def main():
     model_name='u2net'#u2netp
 
 
-    image_dir = './test_data/test_images/'
-    prediction_dir = './test_data/' + model_name + '_results/'
-    model_dir = './saved_models/'+ model_name + '/' + model_name + '.pth'
 
-    img_name_list = glob.glob(image_dir + '*')
+    image_dir = os.path.join(os.getcwd(), 'test_data', 'test_images')
+    prediction_dir = os.path.join(os.getcwd(), 'test_data', model_name + '_results' + os.sep)
+    model_dir = os.path.join(os.getcwd(), 'saved_models', model_name, model_name + '.pth')
+
+    img_name_list = glob.glob(image_dir + os.sep + '*')
     print(img_name_list)
 
     # --------- 2. dataloader ---------
@@ -91,7 +92,7 @@ def main():
     # --------- 4. inference for each image ---------
     for i_test, data_test in enumerate(test_salobj_dataloader):
 
-        print("inferencing:",img_name_list[i_test].split("/")[-1])
+        print("inferencing:",img_name_list[i_test].split(os.sep)[-1])
 
         inputs_test = data_test['image']
         inputs_test = inputs_test.type(torch.FloatTensor)
@@ -108,6 +109,8 @@ def main():
         pred = normPRED(pred)
 
         # save results to test_results folder
+        if not os.path.exists(prediction_dir):
+            os.makedirs(prediction_dir, exist_ok=True)
         save_output(img_name_list[i_test],pred,prediction_dir)
 
         del d1,d2,d3,d4,d5,d6,d7