diff --git a/samples/python2/dft.py b/samples/python2/dft.py
new file mode 100644
index 0000000000..32a91e3b58
--- /dev/null
+++ b/samples/python2/dft.py
@@ -0,0 +1,100 @@
+#/usr/bin/env python
+
+import cv2
+import numpy as np
+import sys
+
+
+def shift_dft(src, dst=None):
+    '''
+        Rearrange the quadrants of Fourier image so that the origin is at
+        the image center. Swaps quadrant 1 with 3, and 2 with 4. 
+       
+        src and dst arrays must be equal size & type
+    '''
+    
+    if dst is None:
+        dst = np.empty(src.shape, src.dtype)
+    elif src.shape != dst.shape:
+        raise ValueError("src and dst must have equal sizes")
+    elif src.dtype != dst.dtype:
+        raise TypeError("src and dst must have equal types")
+    
+    if src is dst:
+        ret = np.empty(src.shape, src.dtype)
+    else:
+        ret = dst
+    
+    h, w = src.shape[:2]
+    
+    cx1 = cx2 = w/2
+    cy1 = cy2 = h/2
+    
+    # if the size is odd, then adjust the bottom/right quadrants
+    if w % 2 != 0:
+        cx2 += 1
+    if h % 2 != 0:
+        cy2 += 1 
+        
+    # swap quadrants
+    
+    # swap q1 and q3
+    ret[h-cy1:, w-cx1:] = src[0:cy1 , 0:cx1 ]   # q1 -> q3
+    ret[0:cy2 , 0:cx2 ] = src[h-cy2:, w-cx2:]   # q3 -> q1
+    
+    # swap q2 and q4
+    ret[0:cy2 , w-cx2:] = src[h-cy2:, 0:cx2 ]   # q2 -> q4
+    ret[h-cy1:, 0:cx1 ] = src[0:cy1 , w-cx1:]   # q4 -> q2
+    
+    if src is dst:
+        dst[:,:] = ret
+    
+    return dst
+
+if __name__ == "__main__":
+        
+    if len(sys.argv)>1:
+        im = cv2.imread(sys.argv[1])
+    else :
+        im = cv2.imread('../c/baboon.jpg')
+        print "usage : python dft.py <image_file>"
+
+    # convert to grayscale
+    im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+    h, w = im.shape[:2]
+    
+    realInput = im.astype(np.float64)
+    
+    # perform an optimally sized dft
+    dft_M = cv2.getOptimalDFTSize(w)
+    dft_N = cv2.getOptimalDFTSize(h)
+
+    # copy A to dft_A and pad dft_A with zeros
+    dft_A = np.zeros((dft_N, dft_M, 2), dtype=np.float64)
+    dft_A[:h, :w, 0] = realInput
+    
+    # no need to pad bottom part of dft_A with zeros because of
+    # use of nonzeroRows parameter in cv2.dft()
+    cv2.dft(dft_A, dst=dft_A, nonzeroRows=h)
+    
+    cv2.imshow("win", im)
+    
+    # Split fourier into real and imaginary parts
+    image_Re, image_Im = cv2.split(dft_A)
+    
+    # Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
+    magnitude = cv2.sqrt(image_Re**2.0 + image_Im**2.0)
+    
+    # Compute log(1 + Mag)
+    log_spectrum = cv2.log(1.0 + magnitude)
+    
+    # Rearrange the quadrants of Fourier image so that the origin is at
+    # the image center
+    shift_dft(log_spectrum, log_spectrum)
+
+    # normalize and display the results as rgb
+    cv2.normalize(log_spectrum, log_spectrum, 0.0, 1.0, cv2.cv.CV_MINMAX)
+    cv2.imshow("magnitude", log_spectrum)
+
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()