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