Viewing File: /home/ubuntu/combine_ai/combine/lib/python3.10/site-packages/skimage/io/tests/test_collection.py
import os
import itertools
import numpy as np
import imageio.v3 as iio3
from skimage import data_dir
from skimage.io.collection import ImageCollection, MultiImage, alphanumeric_key
from skimage.io import reset_plugins
from skimage._shared import testing
from skimage._shared.testing import assert_equal, assert_allclose, fetch
import pytest
try:
has_pooch = True
except ModuleNotFoundError:
has_pooch = False
def test_string_split():
test_string = 'z23a'
test_str_result = ['z', 23, 'a']
assert_equal(alphanumeric_key(test_string), test_str_result)
def test_string_sort():
filenames = ['f9.10.png', 'f9.9.png', 'f10.10.png', 'f10.9.png',
'e9.png', 'e10.png', 'em.png']
expected_filenames = ['e9.png', 'e10.png', 'em.png', 'f9.9.png',
'f9.10.png', 'f10.9.png', 'f10.10.png']
sorted_filenames = sorted(filenames, key=alphanumeric_key)
assert_equal(expected_filenames, sorted_filenames)
def test_imagecollection_input():
"""Test function for ImageCollection. The new behavior (implemented
in 0.16) allows the `pattern` argument to accept a list of strings
as the input.
Notes
-----
If correct, `images` will receive three images.
"""
# Ensure that these images are part of the legacy datasets
# this means they will always be available in the user's install
# regardless of the availability of pooch
pics = [
fetch('data/coffee.png'),
fetch('data/chessboard_GRAY.png'),
fetch('data/rocket.jpg')
]
pattern = [os.path.join(data_dir, pic) for pic in pics]
images = ImageCollection(pattern)
assert len(images) == 3
class TestImageCollection():
pics = [
fetch('data/brick.png'),
fetch('data/color.png'),
fetch('data/moon.png')
]
pattern = pics[:2]
pattern_same_shape = pics[::2]
def setup_method(self):
reset_plugins()
# Generic image collection with images of different shapes.
self.images = ImageCollection(self.pattern)
# Image collection with images having shapes that match.
self.images_matched = ImageCollection(self.pattern_same_shape)
# Same images as a collection of frames
self.frames_matched = MultiImage(self.pattern_same_shape)
def test_len(self):
assert len(self.images) == 2
def test_getitem(self):
num = len(self.images)
for i in range(-num, num):
assert isinstance(self.images[i], np.ndarray)
assert_allclose(self.images[0],
self.images[-num])
def return_img(n):
return self.images[n]
with testing.raises(IndexError):
return_img(num)
with testing.raises(IndexError):
return_img(-num - 1)
def test_slicing(self):
assert type(self.images[:]) is ImageCollection
assert len(self.images[:]) == 2
assert len(self.images[:1]) == 1
assert len(self.images[1:]) == 1
assert_allclose(self.images[0], self.images[:1][0])
assert_allclose(self.images[1], self.images[1:][0])
assert_allclose(self.images[1], self.images[::-1][0])
assert_allclose(self.images[0], self.images[::-1][1])
def test_files_property(self):
assert isinstance(self.images.files, list)
def set_files(f):
self.images.files = f
with testing.raises(AttributeError):
set_files('newfiles')
@pytest.mark.skipif(not has_pooch, reason="needs pooch to download data")
def test_custom_load_func_sequence(self):
filename = fetch('data/no_time_for_that_tiny.gif')
def reader(index):
return iio3.imread(filename, index=index)
ic = ImageCollection(range(24), load_func=reader)
# the length of ic should be that of the given load_pattern sequence
assert len(ic) == 24
# GIF file has frames of size 25x14 with 4 channels (RGBA)
assert ic[0].shape == (25, 14, 3)
@pytest.mark.skipif(not has_pooch, reason="needs pooch to download data")
def test_custom_load_func_w_kwarg(self):
load_pattern = fetch('data/no_time_for_that_tiny.gif')
def load_fn(f, step):
vid = iio3.imiter(f)
return list(itertools.islice(vid, None, None, step))
ic = ImageCollection(load_pattern, load_func=load_fn, step=3)
# Each file should map to one image (array).
assert len(ic) == 1
# GIF file has 24 frames, so 24 / 3 equals 8.
assert len(ic[0]) == 8
def test_custom_load_func(self):
def load_fn(x):
return x
ic = ImageCollection(os.pathsep.join(self.pattern), load_func=load_fn)
assert_equal(ic[0], self.pattern[0])
def test_concatenate(self):
array = self.images_matched.concatenate()
expected_shape = (len(self.images_matched),) + self.images[0].shape
assert_equal(array.shape, expected_shape)
def test_concatenate_mismatched_image_shapes(self):
with testing.raises(ValueError):
self.images.concatenate()
def test_multiimage_imagecollection(self):
assert_equal(self.images_matched[0], self.frames_matched[0])
assert_equal(self.images_matched[1], self.frames_matched[1])
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