1e2ca2e0bf
And add teardown to the test-suite so we can spot refleaks more easily.
218 lines
8.3 KiB
Python
218 lines
8.3 KiB
Python
# vim: set fileencoding=utf-8 :
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import operator
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import pytest
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from functools import reduce
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import pyvips
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from helpers import noncomplex_formats, run_fn2, run_fn, \
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assert_almost_equal_objects, assert_less_threshold
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# point convolution
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def conv(image, mask, x_position, y_position):
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s = 0.0
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for x in range(0, mask.width):
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for y in range(0, mask.height):
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m = mask(x, y)
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i = image(x + x_position, y + y_position)
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p = run_fn2(operator.mul, m, i)
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s = run_fn2(operator.add, s, p)
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return run_fn2(operator.truediv, s, mask.scale)
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def compass(image, mask, x_position, y_position, n_rot, fn):
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acc = []
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for i in range(0, n_rot):
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result = conv(image, mask, x_position, y_position)
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result = run_fn(abs, result)
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acc.append(result)
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mask = mask.rot45()
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return reduce(lambda a, b: run_fn2(fn, a, b), acc)
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class TestConvolution:
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@classmethod
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def setup_class(cls):
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im = pyvips.Image.mask_ideal(100, 100, 0.5, reject=True, optical=True)
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cls.colour = im * [1, 2, 3] + [2, 3, 4]
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cls.colour = cls.colour.copy(interpretation=pyvips.Interpretation.SRGB)
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cls.mono = cls.colour.extract_band(1)
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cls.mono = cls.mono.copy(interpretation=pyvips.Interpretation.B_W)
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cls.all_images = [cls.mono, cls.colour]
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cls.sharp = pyvips.Image.new_from_array([[-1, -1, -1],
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[-1, 16, -1],
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[-1, -1, -1]], scale=8)
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cls.blur = pyvips.Image.new_from_array([[1, 1, 1],
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[1, 1, 1],
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[1, 1, 1]], scale=9)
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cls.line = pyvips.Image.new_from_array([[1, 1, 1],
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[-2, -2, -2],
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[1, 1, 1]])
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cls.sobel = pyvips.Image.new_from_array([[1, 2, 1],
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[0, 0, 0],
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[-1, -2, -1]])
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cls.all_masks = [cls.sharp, cls.blur, cls.line, cls.sobel]
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@classmethod
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def teardown_class(cls):
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cls.colour = None
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cls.mono = None
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cls.all_images = None
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cls.sharp = None
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cls.blur = None
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cls.line = None
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cls.sobel = None
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cls.all_masks = None
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def test_conv(self):
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for im in self.all_images:
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for msk in self.all_masks:
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for prec in [pyvips.Precision.INTEGER, pyvips.Precision.FLOAT]:
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convolved = im.conv(msk, precision=prec)
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result = convolved(25, 50)
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true = conv(im, msk, 24, 49)
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assert_almost_equal_objects(result, true)
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result = convolved(50, 50)
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true = conv(im, msk, 49, 49)
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assert_almost_equal_objects(result, true)
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# don't test conva, it's still not done
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def dont_est_conva(self):
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for im in self.all_images:
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for msk in self.all_masks:
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print("msk:")
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msk.matrixprint()
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print("im.bands = %s" % im.bands)
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convolved = im.conv(msk,
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precision=pyvips.Precision.APPROXIMATE)
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result = convolved(25, 50)
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true = conv(im, msk, 24, 49)
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print("result = %s, true = %s" % (result, true))
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assert_less_threshold(result, true, 5)
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result = convolved(50, 50)
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true = conv(im, msk, 49, 49)
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print("result = %s, true = %s" % (result, true))
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assert_less_threshold(result, true, 5)
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def test_compass(self):
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for im in self.all_images:
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for msk in self.all_masks:
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for prec in [pyvips.Precision.INTEGER, pyvips.Precision.FLOAT]:
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for times in range(1, 4):
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convolved = im.compass(msk,
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times=times,
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angle=pyvips.Angle45.D45,
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combine=pyvips.Combine.MAX,
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precision=prec)
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result = convolved(25, 50)
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true = compass(im, msk, 24, 49, times, max)
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assert_almost_equal_objects(result, true)
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for im in self.all_images:
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for msk in self.all_masks:
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for prec in [pyvips.Precision.INTEGER, pyvips.Precision.FLOAT]:
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for times in range(1, 4):
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convolved = im.compass(msk,
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times=times,
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angle=pyvips.Angle45.D45,
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combine=pyvips.Combine.SUM,
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precision=prec)
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result = convolved(25, 50)
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true = compass(im, msk, 24, 49, times, operator.add)
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assert_almost_equal_objects(result, true)
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def test_convsep(self):
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for im in self.all_images:
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for prec in [pyvips.Precision.INTEGER, pyvips.Precision.FLOAT]:
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gmask = pyvips.Image.gaussmat(2, 0.1,
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precision=prec)
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gmask_sep = pyvips.Image.gaussmat(2, 0.1,
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separable=True,
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precision=prec)
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assert gmask.width == gmask.height
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assert gmask_sep.width == gmask.width
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assert gmask_sep.height == 1
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a = im.conv(gmask, precision=prec)
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b = im.convsep(gmask_sep, precision=prec)
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a_point = a(25, 50)
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b_point = b(25, 50)
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assert_almost_equal_objects(a_point, b_point, threshold=0.1)
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def test_fastcor(self):
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for im in self.all_images:
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for fmt in noncomplex_formats:
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small = im.crop(20, 45, 10, 10).cast(fmt)
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cor = im.fastcor(small)
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v, x, y = cor.minpos()
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assert v == 0
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assert x == 25
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assert y == 50
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def test_spcor(self):
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for im in self.all_images:
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for fmt in noncomplex_formats:
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small = im.crop(20, 45, 10, 10).cast(fmt)
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cor = im.spcor(small)
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v, x, y = cor.maxpos()
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assert v == 1.0
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assert x == 25
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assert y == 50
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def test_gaussblur(self):
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for im in self.all_images:
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for prec in [pyvips.Precision.INTEGER, pyvips.Precision.FLOAT]:
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for i in range(5, 10):
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sigma = i / 5.0
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gmask = pyvips.Image.gaussmat(sigma, 0.2,
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precision=prec)
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a = im.conv(gmask, precision=prec)
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b = im.gaussblur(sigma, min_ampl=0.2, precision=prec)
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a_point = a(25, 50)
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b_point = b(25, 50)
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assert_almost_equal_objects(a_point, b_point,
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threshold=0.1)
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def test_sharpen(self):
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for im in self.all_images:
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for fmt in noncomplex_formats:
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# old vipses used "radius", check that that still works
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sharp = im.sharpen(radius=5)
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for sigma in [0.5, 1, 1.5, 2]:
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im = im.cast(fmt)
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sharp = im.sharpen(sigma=sigma)
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# hard to test much more than this
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assert im.width == sharp.width
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assert im.height == sharp.height
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# if m1 and m2 are zero, sharpen should do nothing
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sharp = im.sharpen(sigma=sigma, m1=0, m2=0)
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sharp = sharp.colourspace(im.interpretation)
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# print("testing sig = %g" % sigma)
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# print("testing fmt = %s" % fmt)
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# print("max diff = %g" % (im - sharp).abs().max())
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assert (im - sharp).abs().max() == 0
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if __name__ == '__main__':
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pytest.main()
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