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from __future__ import division, print_function, absolute_import
import os.path
import tempfile
import shutil
import numpy as np
import warnings
import glob
from numpy.testing import (assert_equal, dec, decorate_methods,
TestCase, run_module_suite, assert_allclose,
assert_array_equal)
from scipy import misc
try:
import PIL.Image
except ImportError:
_have_PIL = False
else:
_have_PIL = True
# Function / method decorator for skipping PIL tests on import failure
_pilskip = dec.skipif(not _have_PIL, 'Need to import PIL for this test')
datapath = os.path.dirname(__file__)
class TestPILUtil(TestCase):
def test_imresize(self):
im = np.random.random((10, 20))
for T in np.sctypes['float'] + [float]:
# 1.1 rounds to below 1.1 for float16, 1.101 works
im1 = misc.imresize(im, T(1.101))
assert_equal(im1.shape, (11, 22))
def test_imresize2(self):
im = np.random.random((20, 30))
im2 = misc.imresize(im, (30, 40), interp='bicubic')
assert_equal(im2.shape, (30, 40))
def test_imresize3(self):
im = np.random.random((15, 30))
im2 = misc.imresize(im, (30, 60), interp='nearest')
assert_equal(im2.shape, (30, 60))
def test_imresize4(self):
im = np.array([[1, 2],
[3, 4]])
# Check that resizing by target size, float and int are the same
im2 = misc.imresize(im, (4, 4), mode='F') # output size
im3 = misc.imresize(im, 2., mode='F') # fraction
im4 = misc.imresize(im, 200, mode='F') # percentage
assert_equal(im2, im3)
assert_equal(im2, im4)
def test_imresize5(self):
im = np.random.random((25, 15))
im2 = misc.imresize(im, (30, 60), interp='lanczos')
assert_equal(im2.shape, (30, 60))
def test_bytescale(self):
x = np.array([0, 1, 2], np.uint8)
y = np.array([0, 1, 2])
assert_equal(misc.bytescale(x), x)
assert_equal(misc.bytescale(y), [0, 127, 255])
def test_bytescale_keywords(self):
x = np.array([40, 60, 120, 200, 300, 500])
res_lowhigh = misc.bytescale(x, low=10, high=143)
assert_equal(res_lowhigh, [10, 16, 33, 56, 85, 143])
res_cmincmax = misc.bytescale(x, cmin=60, cmax=300)
assert_equal(res_cmincmax, [0, 0, 64, 149, 255, 255])
assert_equal(misc.bytescale(np.array([3, 3, 3]), low=4), [4, 4, 4])
def test_imsave(self):
picdir = os.path.join(datapath, "data")
for png in glob.iglob(picdir + "/*.png"):
with warnings.catch_warnings(record=True): # PIL ResourceWarning
img = misc.imread(png)
tmpdir = tempfile.mkdtemp()
try:
fn1 = os.path.join(tmpdir, 'test.png')
fn2 = os.path.join(tmpdir, 'testimg')
# PIL ResourceWarning
with warnings.catch_warnings(record=True):
misc.imsave(fn1, img)
misc.imsave(fn2, img, 'PNG')
# PIL ResourceWarning
with warnings.catch_warnings(record=True):
data1 = misc.imread(fn1)
data2 = misc.imread(fn2)
assert_allclose(data1, img)
assert_allclose(data2, img)
assert_equal(data1.shape, img.shape)
assert_equal(data2.shape, img.shape)
finally:
shutil.rmtree(tmpdir)
decorate_methods(TestPILUtil, _pilskip)
def tst_fromimage(filename, irange, shape):
fp = open(filename, "rb")
img = misc.fromimage(PIL.Image.open(fp))
fp.close()
imin, imax = irange
assert_equal(img.min(), imin)
assert_equal(img.max(), imax)
assert_equal(img.shape, shape)
@_pilskip
def test_fromimage():
# Test generator for parametric tests
# Tuples in the list are (filename, (datamin, datamax), shape).
files = [('icon.png', (0, 255), (48, 48, 4)),
('icon_mono.png', (0, 255), (48, 48, 4)),
('icon_mono_flat.png', (0, 255), (48, 48, 3))]
for fn, irange, shape in files:
yield tst_fromimage, os.path.join(datapath, 'data', fn), irange, shape
@_pilskip
def test_imread_indexed_png():
# The file `foo3x5x4indexed.png` was created with this array
# (3x5 is (height)x(width)):
data = np.array([[[127, 0, 255, 255],
[127, 0, 255, 255],
[127, 0, 255, 255],
[127, 0, 255, 255],
[127, 0, 255, 255]],
[[192, 192, 255, 0],
[192, 192, 255, 0],
[0, 0, 255, 0],
[0, 0, 255, 0],
[0, 0, 255, 0]],
[[0, 31, 255, 255],
[0, 31, 255, 255],
[0, 31, 255, 255],
[0, 31, 255, 255],
[0, 31, 255, 255]]], dtype=np.uint8)
filename = os.path.join(datapath, 'data', 'foo3x5x4indexed.png')
im = misc.imread(filename)
assert_array_equal(im, data)
@_pilskip
def test_imread_1bit():
# box1.png is a 48x48 grayscale image with bit depth 1.
# The border pixels are 1 and the rest are 0.
filename = os.path.join(datapath, 'data', 'box1.png')
with open(filename, 'rb') as f:
im = misc.imread(f)
assert_equal(im.dtype, np.uint8)
expected = np.zeros((48, 48), dtype=np.uint8)
# When scaled up from 1 bit to 8 bits, 1 becomes 255.
expected[:, 0] = 255
expected[:, -1] = 255
expected[0, :] = 255
expected[-1, :] = 255
assert_equal(im, expected)
@_pilskip
def test_imread_2bit():
# blocks2bit.png is a 12x12 grayscale image with bit depth 2.
# The pattern is 4 square subblocks of size 6x6. Upper left
# is all 0, upper right is all 1, lower left is all 2, lower
# right is all 3.
# When scaled up to 8 bits, the values become [0, 85, 170, 255].
filename = os.path.join(datapath, 'data', 'blocks2bit.png')
with open(filename, 'rb') as f:
im = misc.imread(f)
assert_equal(im.dtype, np.uint8)
expected = np.zeros((12, 12), dtype=np.uint8)
expected[:6, 6:] = 85
expected[6:, :6] = 170
expected[6:, 6:] = 255
assert_equal(im, expected)
@_pilskip
def test_imread_4bit():
# pattern4bit.png is a 12(h) x 31(w) grayscale image with bit depth 4.
# The value in row j and column i is maximum(j, i) % 16.
# When scaled up to 8 bits, the values become [0, 17, 34, ..., 255].
filename = os.path.join(datapath, 'data', 'pattern4bit.png')
with open(filename, 'rb') as f:
im = misc.imread(f)
assert_equal(im.dtype, np.uint8)
# When the oldest supported version of numpy is 1.7, the following
# line can be change to
# j, i = np.meshgrid(np.arange(12), np.arange(31), indexing='ij')
j, i = [k.T for k in np.meshgrid(np.arange(12), np.arange(31))]
expected = 17*(np.maximum(j, i) % 16).astype(np.uint8)
assert_equal(im, expected)
if __name__ == "__main__":
run_module_suite()
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