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Open Source Computer Vision Library
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50 lines
1.4 KiB
50 lines
1.4 KiB
#!/usr/bin/env python |
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''' |
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Test for disctrete fourier transform (dft) |
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''' |
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# Python 2/3 compatibility |
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from __future__ import print_function |
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import cv2 as cv |
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import numpy as np |
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import sys |
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from tests_common import NewOpenCVTests |
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class dft_test(NewOpenCVTests): |
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def test_dft(self): |
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img = self.get_sample('samples/data/rubberwhale1.png', 0) |
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eps = 0.001 |
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#test direct transform |
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refDft = np.fft.fft2(img) |
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refDftShift = np.fft.fftshift(refDft) |
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refMagnitide = np.log(1.0 + np.abs(refDftShift)) |
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testDft = cv.dft(np.float32(img),flags = cv.DFT_COMPLEX_OUTPUT) |
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testDftShift = np.fft.fftshift(testDft) |
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testMagnitude = np.log(1.0 + cv.magnitude(testDftShift[:,:,0], testDftShift[:,:,1])) |
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refMagnitide = cv.normalize(refMagnitide, 0.0, 1.0, cv.NORM_MINMAX) |
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testMagnitude = cv.normalize(testMagnitude, 0.0, 1.0, cv.NORM_MINMAX) |
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self.assertLess(cv.norm(refMagnitide - testMagnitude), eps) |
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#test inverse transform |
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img_back = np.fft.ifft2(refDft) |
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img_back = np.abs(img_back) |
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img_backTest = cv.idft(testDft) |
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img_backTest = cv.magnitude(img_backTest[:,:,0], img_backTest[:,:,1]) |
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img_backTest = cv.normalize(img_backTest, 0.0, 1.0, cv.NORM_MINMAX) |
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img_back = cv.normalize(img_back, 0.0, 1.0, cv.NORM_MINMAX) |
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self.assertLess(cv.norm(img_back - img_backTest), eps) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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