--- a/python/moving.py	Thu Jun 22 17:02:03 2017 -0400
+++ b/python/moving.py	Thu Jun 22 18:08:46 2017 -0400
@@ -1583,7 +1583,7 @@
         with an added px or py for width and height (around the box))
         computes HOG on this cropped image (with parameters rescaleSize, orientations, pixelsPerCell, cellsPerBlock)
         and applies the SVM model on it'''
-        croppedImg, yCropMin, yCropMax, xCropMin, xCropMax = cvutils.imageBox(img, self, instant, homography, width, height, px, py, minNPixels)
+        croppedImg = cvutils.imageBox(img, self, instant, homography, 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)
             self.userTypes[instant] = int(self.appearanceClassifier.predict(hog))