diff --git a/mini_proj/test_nn.py b/mini_proj/test_nn.py
index 987b6b5..b0b6727 100644
--- a/mini_proj/test_nn.py
+++ b/mini_proj/test_nn.py
@@ -53,7 +53,7 @@ def is_Wally(trained_model_path, image, from_file=False):
 
 if __name__ == '__main__':
     # Read image
-    image = cv2.imread("10.jpg")
+    image = cv2.imread("7.jpg")
     # Split image
     cuts = image_cut(image, 64, 64)
     for i in range(len(cuts)):
@@ -63,11 +63,18 @@ if __name__ == '__main__':
         block = color.hsv2rgb(hsv)
         block = np.rollaxis(block, -1)
         if is_Wally("Waldo.h5", block):
-        # if True:
             # Border block
             GREEN = [0, 255, 0]
             cuts[i] = cv2.copyMakeBorder(cuts[i][1:61,1:61],2,2,2,2,cv2.BORDER_CONSTANT,value=GREEN)
 
-    # Stitch image TODO!
+    # Stitch image
+    width = int(image.shape[1]/64) # TODO: does not work if this is not actually an integer
+    i = 0
+    layers = []
+    while i < len(cuts):
+        filler = [ np.zeros((64,64,3)) for j in range(i+width - min(i+width, len(cuts))) ]
+        layers.append(np.concatenate(([cuts[j] for j in range(i, min(i+width, len(cuts)))] + filler),axis=1))
+        i = i + width
+    image = np.concatenate(layers, axis=0)
     # Show image
     cv2.imwrite('output.png',image)