--- a/python/moving.py	Fri Aug 18 18:00:11 2017 -0400
+++ b/python/moving.py	Thu Aug 24 17:22:24 2017 -0400
@@ -1108,6 +1108,11 @@
 
 userType2Num = utils.inverseEnumeration(userTypeNames)
 
+class CarClassifier:
+    def predict(self, hog):
+        return userType2Num['car']
+carClassifier = CarClassifier()
+    
 class MovingObject(STObject, VideoFilenameAddable):
     '''Class for moving objects: a spatio-temporal object 
     with a trajectory and a geometry (constant volume over time) 
@@ -1615,10 +1620,7 @@
         elif self.aggregatedSpeed < bikeCarSpeedThreshold:
             self.appearanceClassifier = bikeCarSVM
         else:
-            class CarClassifier:
-                def predict(self, hog):
-                    return userType2Num['car']
-            self.appearanceClassifier = CarClassifier()
+            self.appearanceClassifier = carClassifier
         # project feature positions
         if self.hasFeatures():
             for f in self.getFeatures():
@@ -1634,7 +1636,7 @@
         and applies the SVM model on it'''
         croppedImg = cvutils.imageBox(img, self, instant, width, height, px, py, minNPixels)
         if croppedImg is not None and len(croppedImg) > 0:
-            hog = cvutils.HOG(croppedImg, rescaleSize, orientations, pixelsPerCell, cellsPerBlock, blockNorm, visualize=False, normalize=False)
+            hog = cvutils.HOG(croppedImg, rescaleSize, orientations, pixelsPerCell, cellsPerBlock, blockNorm)
             self.userTypes[instant] = int(self.appearanceClassifier.predict(hog))
         else:
             self.userTypes[instant] = userType2Num['unknown']