--- a/python/cvutils.py	Fri Jul 12 02:29:49 2013 -0400
+++ b/python/cvutils.py	Fri Jul 12 11:28:47 2013 -0400
@@ -4,10 +4,17 @@
 import Image, ImageDraw # PIL
 try:
     import cv2
-    opencvExists = True
+    opencvAvailable = True
 except ImportError:
     print('OpenCV library could not be loaded')
-    opencvExists = False
+    opencvAvailable = False
+try:
+    import skimage
+    skimageAvailable = True
+except ImportError:
+    print('Scikit-image library could not be loaded')
+    skimageAvailable = False
+    
 from sys import stdout
 
 import utils
@@ -70,7 +77,7 @@
             a[i,j] = cvmat[i,j]
     return a
 
-if opencvExists:
+if opencvAvailable:
     def computeHomography(srcPoints, dstPoints, method=0, ransacReprojThreshold=0.0):
         '''Returns the homography matrix mapping from srcPoints to dstPoints (dimension Nx2)'''
         H, mask = cv2.findHomography(srcPoints, dstPoints, method, ransacReprojThreshold)
@@ -209,7 +216,7 @@
     invH /= invH[2,2]
     return invH
 
-if opencvExists:
+if opencvAvailable:
     def computeTranslation(img1, img2, img1Points, maxTranslation2, minNMatches, windowSize = (5,5), level = 5, criteria = (cv2.TERM_CRITERIA_EPS, 0, 0.01)):
         '''Computes the translation of img2 with respect to img1
         (loaded using OpenCV as numpy arrays)
@@ -235,3 +242,32 @@
         else:
             print(dp)
             return None
+
+if skimageAvailable:
+    def createHOGTrainingSet(imageDirectory, classLabel, rescaleSize = (64, 64), orientations=9, pixelsPerCell=(8, 8), cellsPerBlock=(3, 3), visualize=False, normalize=False):
+        from os import listdir
+        from matplotlib.pyplot import imread, imshow, figure, subplot
+        from skimage.feature import hog
+        from skimage import color, transform
+        from numpy import array, float32
+
+        inputData = []
+        for filename in listdir(imageDirectory):
+            img = imread(imageDirectory+filename)
+            bwImg = color.rgb2gray(img)
+            inputImg = transform.resize(bwImg, rescaleSize)
+            features = hog(inputImg, orientations, pixelsPerCell, cellsPerBlock, visualize, normalize)
+            if visualize:
+                hogViz = features[1]
+                features = features[0]
+                figure()
+                subplot(1,2,1)
+                imshow(img)
+                subplot(1,2,2)
+                imshow(hogViz)
+            inputData.append(features)
+
+        nImages = len(inputData)
+        return array(inputData, dtype = float32), array([classLabel]*nImages, dtype = float32)
+
+