--- a/python/cvutils.py	Tue May 26 11:40:32 2015 +0200
+++ b/python/cvutils.py	Tue May 26 13:53:40 2015 +0200
@@ -17,6 +17,7 @@
     skimageAvailable = False
     
 from sys import stdout
+from numpy import dot, array, append
 
 #import aggdraw # agg on top of PIL (antialiased drawing)
 
@@ -67,15 +68,14 @@
 
 def loadPointCorrespondences(filename):
     '''Loads and returns the corresponding points in world (first 2 lines) and image spaces (last 2 lines)'''
-    from numpy.lib.npyio import loadtxt
-    from numpy import float32
+    from numpy import loadtxt, float32
     points = loadtxt(filename, dtype=float32)
     return  (points[:2,:].T, points[2:,:].T) # (world points, image points)
 
 def cvMatToArray(cvmat):
     '''Converts an OpenCV CvMat to numpy array.'''
     print('Deprecated, use new interface')
-    from numpy.core.multiarray import zeros
+    from numpy import zeros
     a = zeros((cvmat.rows, cvmat.cols))#array([[0.0]*cvmat.width]*cvmat.height)
     for i in xrange(cvmat.rows):
         for j in xrange(cvmat.cols):
@@ -116,7 +116,7 @@
 
     def computeUndistortMaps(width, height, undistortedImageMultiplication, intrinsicCameraMatrix, distortionCoefficients):
         from copy import deepcopy
-        from numpy import identity, array
+        from numpy import identity
         newImgSize = (int(round(width*undistortedImageMultiplication)), int(round(height*undistortedImageMultiplication)))
         newCameraMatrix = deepcopy(intrinsicCameraMatrix)
         newCameraMatrix[0,2] = newImgSize[0]/2.
@@ -325,7 +325,6 @@
     def computeHomographyFromPDTV(camera):
         '''Returns the homography matrix at ground level from PDTV camera
         https://bitbucket.org/hakanardo/pdtv'''
-        from numpy import array
         # camera = pdtv.load(cameraFilename)
         srcPoints = [[x,y] for x, y in zip([1.,2.,2.,1.],[1.,1.,2.,2.])] # need floats!!
         dstPoints = []
@@ -340,7 +339,7 @@
         map1 and map2 are the mapping functions from undistorted image
         to distorted (original image)
         map1(x,y) = originalx, originaly'''
-        from numpy import abs, logical_and, unravel_index, dot, sum
+        from numpy import abs, logical_and, unravel_index, sum
         from matplotlib.mlab import find
         distx = abs(map1-x)
         disty = abs(map2-y)
@@ -459,10 +458,6 @@
 def projectArray(homography, points):
     '''Returns the coordinates of the projected points through homography
     (format: array 2xN points)'''
-    from numpy.core import dot
-    from numpy.core.multiarray import array
-    from numpy.lib.function_base import append
-
     if points.shape[0] != 2:
         raise Exception('points of dimension {0} {1}'.format(points.shape[0], points.shape[1]))
 
@@ -477,20 +472,18 @@
 def project(homography, p):
     '''Returns the coordinates of the projection of the point p with coordinates p[0], p[1]
     through homography'''
-    from numpy import array
     return projectArray(homography, array([[p[0]],[p[1]]]))
 
 def projectTrajectory(homography, trajectory):
     '''Projects a series of points in the format
     [[x1, x2, ...],
     [y1, y2, ...]]'''
-    from numpy.core.multiarray import array
     return projectArray(homography, array(trajectory))
 
 def invertHomography(homography):
     '''Returns an inverted homography
     Unnecessary for reprojection over camera image'''
-    from numpy.linalg.linalg import inv
+    from numpy import inv
     invH = inv(homography)
     invH /= invH[2,2]
     return invH
@@ -517,7 +510,6 @@
     return undistortedTrajectory
 
 def projectGInputPoints(homography, points):
-    from numpy import array
     return projectTrajectory(homography, array(points+[points[0]]).T)
 
 if opencvAvailable:
@@ -527,9 +519,7 @@
         img1Points are used to compute the translation
 
         TODO add diagnostic if data is all over the place, and it most likely is not a translation (eg zoom, other non linear distortion)'''
-        from numpy.core.multiarray import array
-        from numpy.lib.function_base import median
-        from numpy.core.fromnumeric import sum
+        from numpy import median, sum
 
         nextPoints = array([])
         (img2Points, status, track_error) = cv2.calcOpticalFlowPyrLK(img1, img2, img1Points, nextPoints, winSize=windowSize, maxLevel=level, criteria=criteria)
@@ -568,7 +558,7 @@
 
     def createHOGTrainingSet(imageDirectory, classLabel, rescaleSize = (64, 64), orientations=9, pixelsPerCell=(8, 8), cellsPerBlock=(2, 2), visualize=False, normalize=False):
         from os import listdir
-        from numpy import array, float32
+        from numpy import float32
         from matplotlib.pyplot import imread
 
         inputData = []