#!/usr/bin/python import cv2.cv as cv import sys import urllib2 # Rearrange the quadrants of Fourier image so that the origin is at # the image center # src & dst arrays of equal size & type def cvShiftDFT(src_arr, dst_arr ): size = cv.GetSize(src_arr) dst_size = cv.GetSize(dst_arr) if dst_size != size: cv.Error( cv.CV_StsUnmatchedSizes, "cv.ShiftDFT", "Source and Destination arrays must have equal sizes", __FILE__, __LINE__ ) if(src_arr is dst_arr): tmp = cv.CreateMat(size[1]/2, size[0]/2, cv.GetElemType(src_arr)) cx = size[0] / 2 cy = size[1] / 2 # image center q1 = cv.GetSubRect( src_arr, (0,0,cx, cy) ) q2 = cv.GetSubRect( src_arr, (cx,0,cx,cy) ) q3 = cv.GetSubRect( src_arr, (cx,cy,cx,cy) ) q4 = cv.GetSubRect( src_arr, (0,cy,cx,cy) ) d1 = cv.GetSubRect( src_arr, (0,0,cx,cy) ) d2 = cv.GetSubRect( src_arr, (cx,0,cx,cy) ) d3 = cv.GetSubRect( src_arr, (cx,cy,cx,cy) ) d4 = cv.GetSubRect( src_arr, (0,cy,cx,cy) ) if(src_arr is not dst_arr): if( not cv.CV_ARE_TYPES_EQ( q1, d1 )): cv.Error( cv.CV_StsUnmatchedFormats, "cv.ShiftDFT", "Source and Destination arrays must have the same format", __FILE__, __LINE__ ) cv.Copy(q3, d1) cv.Copy(q4, d2) cv.Copy(q1, d3) cv.Copy(q2, d4) else: cv.Copy(q3, tmp) cv.Copy(q1, q3) cv.Copy(tmp, q1) cv.Copy(q4, tmp) cv.Copy(q2, q4) cv.Copy(tmp, q2) if __name__ == "__main__": if len(sys.argv) > 1: im = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_GRAYSCALE) else: url = 'https://code.ros.org/svn/opencv/trunk/opencv/samples/c/baboon.jpg' filedata = urllib2.urlopen(url).read() imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1) cv.SetData(imagefiledata, filedata, len(filedata)) im = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE) realInput = cv.CreateImage( cv.GetSize(im), cv.IPL_DEPTH_64F, 1) imaginaryInput = cv.CreateImage( cv.GetSize(im), cv.IPL_DEPTH_64F, 1) complexInput = cv.CreateImage( cv.GetSize(im), cv.IPL_DEPTH_64F, 2) cv.Scale(im, realInput, 1.0, 0.0) cv.Zero(imaginaryInput) cv.Merge(realInput, imaginaryInput, None, None, complexInput) dft_M = cv.GetOptimalDFTSize( im.height - 1 ) dft_N = cv.GetOptimalDFTSize( im.width - 1 ) dft_A = cv.CreateMat( dft_M, dft_N, cv.CV_64FC2 ) image_Re = cv.CreateImage( (dft_N, dft_M), cv.IPL_DEPTH_64F, 1) image_Im = cv.CreateImage( (dft_N, dft_M), cv.IPL_DEPTH_64F, 1) # copy A to dft_A and pad dft_A with zeros tmp = cv.GetSubRect( dft_A, (0,0, im.width, im.height)) cv.Copy( complexInput, tmp, None ) if(dft_A.width > im.width): tmp = cv.GetSubRect( dft_A, (im.width,0, dft_N - im.width, im.height)) cv.Zero( tmp ) # no need to pad bottom part of dft_A with zeros because of # use nonzero_rows parameter in cv.FT() call below cv.DFT( dft_A, dft_A, cv.CV_DXT_FORWARD, complexInput.height ) cv.NamedWindow("win", 0) cv.NamedWindow("magnitude", 0) cv.ShowImage("win", im) # Split Fourier in real and imaginary parts cv.Split( dft_A, image_Re, image_Im, None, None ) # Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2) cv.Pow( image_Re, image_Re, 2.0) cv.Pow( image_Im, image_Im, 2.0) cv.Add( image_Re, image_Im, image_Re, None) cv.Pow( image_Re, image_Re, 0.5 ) # Compute log(1 + Mag) cv.AddS( image_Re, cv.ScalarAll(1.0), image_Re, None ) # 1 + Mag cv.Log( image_Re, image_Re ) # log(1 + Mag) # Rearrange the quadrants of Fourier image so that the origin is at # the image center cvShiftDFT( image_Re, image_Re ) min, max, pt1, pt2 = cv.MinMaxLoc(image_Re) cv.Scale(image_Re, image_Re, 1.0/(max-min), 1.0*(-min)/(max-min)) cv.ShowImage("magnitude", image_Re) cv.WaitKey(0)