diff --git a/README.md b/README.md
index 57760da..7b44f28 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,7 @@ Converted trained weights needed to run the network.
 
 
 Download converted weights here:
-[link:pspnet50_ade20k.npy](https://www.dropbox.com/s/2ksp9hvokzk6qc8/pspnet50_ade20k.npy?dl=0)
+[link:pspnet50_ade20k.npy](https://www.dropbox.com/s/ms8afun494dlh1t/pspnet50_ade20k.npy?dl=0)
 
 And place in directory with pspnet50_ade20k.npy
 
@@ -24,6 +24,8 @@ Was repaired some issues. But the result is not as well as expected compared to
 ![Original](test.jpg)
 ![Processed](test_seg.jpg)
 ![Alpha mixed](test_seg_blended.jpg)
+![New](out.jpg)
+![New](probs.jpg)
 
 ## Pycaffe result
 ![Pycaffe results](test_pycaffe.jpg)
diff --git a/out.jpg b/out.jpg
new file mode 100644
index 0000000..14c2689
Binary files /dev/null and b/out.jpg differ
diff --git a/probs.jpg b/probs.jpg
new file mode 100644
index 0000000..9bc9563
Binary files /dev/null and b/probs.jpg differ
diff --git a/pspnet.py b/pspnet.py
index ef000d7..fa42f64 100644
--- a/pspnet.py
+++ b/pspnet.py
@@ -1,7 +1,7 @@
 import os
 import argparse
 import numpy as np
-from scipy import misc
+from scipy import misc, ndimage
 
 from keras import backend as K
 import tensorflow as tf
@@ -26,7 +26,7 @@ class PSPNet:
         h_ori,w_ori = img.shape[:2]
 
         # Preprocess
-        img = img.resize((473,473))
+        img = misc.imresize(img, (473, 473))
         img = img - DATA_MEAN
         img = img[:,:,::-1] # RGB => BGR
         img = img.astype('float32')
@@ -43,7 +43,7 @@ class PSPNet:
         assert data.shape == (473,473,3)
         data = data[np.newaxis,:,:,:]
 
-        utils.debug(self.model, data)
+        # utils.debug(self.model, data)
         pred = self.model.predict(data)
         return pred[0]