diff --git a/facelib/LandmarksExtractor.py b/facelib/LandmarksExtractor.py
index 8a8a38c..9f5d6bd 100644
--- a/facelib/LandmarksExtractor.py
+++ b/facelib/LandmarksExtractor.py
@@ -28,20 +28,22 @@ class LandmarksExtractor(object):
         
         landmarks = []
         for (left, top, right, bottom) in rects:
+            try:
+                center = np.array( [ (left + right) / 2.0, (top + bottom) / 2.0] )
+                center[1] -= (bottom - top) * 0.12
+                scale = (right - left + bottom - top) / 195.0
             
-            center = np.array( [ (left + right) / 2.0, (top + bottom) / 2.0] )
-            center[1] -= (bottom - top) * 0.12
-            scale = (right - left + bottom - top) / 195.0
-        
-            image = self.crop(input_image, center, scale).astype(np.float32)
-            image = np.expand_dims(image, 0)
-            
-            predicted = self.keras_model.predict (image).transpose (0,3,1,2)
-            
-            pts_img = self.get_pts_from_predict ( predicted[-1], center, scale)
-            pts_img = [ ( int(pt[0]), int(pt[1]) ) for pt in pts_img ]             
-            landmarks.append ( ( (left, top, right, bottom),pts_img ) )
-   
+                image = self.crop(input_image, center, scale).astype(np.float32)
+                image = np.expand_dims(image, 0)
+                
+                predicted = self.keras_model.predict (image).transpose (0,3,1,2)
+                
+                pts_img = self.get_pts_from_predict ( predicted[-1], center, scale)
+                pts_img = [ ( int(pt[0]), int(pt[1]) ) for pt in pts_img ]             
+                landmarks.append ( ( (left, top, right, bottom),pts_img ) )
+            except:
+                landmarks.append ( ( (left, top, right, bottom), [ (0,0) for _ in range(68) ] ) )
+                
         return landmarks
         
     def transform(self, point, center, scale, resolution):
@@ -58,6 +60,7 @@ class LandmarksExtractor(object):
     def crop(self, image, center, scale, resolution=256.0):
         ul = self.transform([1, 1], center, scale, resolution).astype( np.int )
         br = self.transform([resolution, resolution], center, scale, resolution).astype( np.int )
+        
         if image.ndim > 2:
             newDim = np.array([br[1] - ul[1], br[0] - ul[0], image.shape[2]], dtype=np.int32)
             newImg = np.zeros(newDim, dtype=np.uint8)
@@ -71,6 +74,7 @@ class LandmarksExtractor(object):
         oldX = np.array([max(1, ul[0] + 1), min(br[0], wd)], dtype=np.int32)
         oldY = np.array([max(1, ul[1] + 1), min(br[1], ht)], dtype=np.int32)
         newImg[newY[0] - 1:newY[1], newX[0] - 1:newX[1] ] = image[oldY[0] - 1:oldY[1], oldX[0] - 1:oldX[1], :]
+        
         newImg = cv2.resize(newImg, dsize=(int(resolution), int(resolution)), interpolation=cv2.INTER_LINEAR)
         return newImg