libvips/test/test_resample.py

149 lines
5.0 KiB
Python
Executable File

#!/usr/bin/python
import unittest
import math
#import logging
#logging.basicConfig(level = logging.DEBUG)
from gi.repository import Vips
Vips.leak_set(True)
# Run a function expecting a complex image on a two-band image
def run_cmplx(fn, image):
if image.format == Vips.BandFormat.FLOAT:
new_format = Vips.BandFormat.COMPLEX
elif image.format == Vips.BandFormat.DOUBLE:
new_format = Vips.BandFormat.DPCOMPLEX
else:
raise "run_cmplx: not float or double"
# tag as complex, run, revert tagging
cmplx = image.copy(bands = 1, format = new_format)
cmplx_result = fn(cmplx)
return cmplx_result.copy(bands = 2, format = image.format)
def to_polar(image):
"""Transform image coordinates to polar.
The image is transformed so that it is wrapped around a point in the
centre. Vertical straight lines become circles or segments of circles,
horizontal straight lines become radial spokes.
"""
# xy image, zero in the centre, scaled to fit image to a circle
xy = Vips.Image.xyz(image.width, image.height)
xy -= [image.width / 2.0, image.height / 2.0]
scale = min(image.width, image.height) / float(image.width)
xy *= 2.0 / scale
# to polar, scale vertical axis to 360 degrees
index = run_cmplx(lambda x: x.polar(), xy)
index *= [1, image.height / 360.0]
return image.mapim(index)
def to_rectangular(image):
"""Transform image coordinates to rectangular.
The image is transformed so that it is unwrapped from a point in the
centre. Circles or segments of circles become vertical straight lines,
radial lines become horizontal lines.
"""
# xy image, vertical scaled to 360 degrees
xy = Vips.Image.xyz(image.width, image.height)
xy *= [1, 360.0 / image.height]
# to rect, scale to image rect
index = run_cmplx(lambda x: x.rect(), xy)
scale = min(image.width, image.height) / float(image.width)
index *= scale / 2.0
index += [image.width / 2.0, image.height / 2.0]
return image.mapim(index)
# an expanding zip ... if either of the args is a scalar or a one-element list,
# duplicate it down the other side
def zip_expand(x, y):
# handle singleton list case
if isinstance(x, list) and len(x) == 1:
x = x[0]
if isinstance(y, list) and len(y) == 1:
y = y[0]
if isinstance(x, list) and isinstance(y, list):
return list(zip(x, y))
elif isinstance(x, list):
return [[i, y] for i in x]
elif isinstance(y, list):
return [[x, j] for j in y]
else:
return [[x, y]]
class TestResample(unittest.TestCase):
# test a pair of things which can be lists for approx. equality
def assertAlmostEqualObjects(self, a, b, places = 4, msg = ''):
# print 'assertAlmostEqualObjects %s = %s' % (a, b)
for x, y in zip_expand(a, b):
self.assertAlmostEqual(x, y, places = places, msg = msg)
def test_affine(self):
im = Vips.Image.new_from_file("images/IMG_4618.jpg")
# vsqbs is non-interpolatory, don't test this way
for name in ["nearest", "bicubic", "bilinear", "nohalo", "lbb"]:
x = im
interpolate = Vips.Interpolate.new(name)
for i in range(4):
x = x.affine([0, 1, 1, 0], interpolate = interpolate)
self.assertEqual((x - im).abs().max(), 0)
def test_resize(self):
im = Vips.Image.new_from_file("images/IMG_4618.jpg")
im2 = im.resize(0.25)
self.assertEqual(im2.width, im.width // 4)
self.assertEqual(im2.height, im.height // 4)
def test_shrink(self):
im = Vips.Image.new_from_file("images/IMG_4618.jpg")
im2 = im.shrink(4, 4)
self.assertEqual(im2.width, im.width // 4)
self.assertEqual(im2.height, im.height // 4)
self.assertTrue(abs(im.avg() - im2.avg()) < 1)
im2 = im.shrink(2.5, 2.5)
self.assertEqual(im2.width, im.width // 2.5)
self.assertEqual(im2.height, im.height // 2.5)
self.assertLess(abs(im.avg() - im2.avg()), 1)
def test_similarity(self):
im = Vips.Image.new_from_file("images/IMG_4618.jpg")
im2 = im.similarity(angle = 90)
im3 = im.affine([0, -1, 1, 0])
# rounding in calculating the affine transform from the angle stops this
# being exactly true
self.assertLess((im2 - im3).abs().max(), 50)
def test_similarity_scale(self):
im = Vips.Image.new_from_file("images/IMG_4618.jpg")
im2 = im.similarity(scale = 2)
im3 = im.affine([2, 0, 0, 2])
self.assertEqual((im2 - im3).abs().max(), 0)
def test_mapim(self):
im = Vips.Image.new_from_file("images/IMG_4618.jpg")
p = to_polar(im)
r = to_rectangular(p)
# the left edge (which is squashed to the origin) will be badly
# distorted, but the rest should not be too bad
a = r.crop(50, 0, im.width - 50, im.height).gaussblur(2)
b = im.crop(50, 0, im.width - 50, im.height).gaussblur(2)
self.assertLess((a - b).abs().max(), 20)
if __name__ == '__main__':
unittest.main()