50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
#!/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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