def it_knows_its_biggest_regions(self):
regions = [
Region(index=0,
area=14,
bbox=(0, 0, 2, 2),
center=(0.5, 0.5),
coords=None),
Region(index=1,
area=2,
bbox=(0, 0, 2, 2),
center=(0.5, 0.5),
coords=None),
Region(index=2,
area=5,
bbox=(0, 0, 2, 2),
center=(0.5, 0.5),
coords=None),
Region(index=3,
area=10,
bbox=(0, 0, 2, 2),
center=(0.5, 0.5),
coords=None),
]
binary_mask = BiggestTissueBoxMask
biggest_regions = binary_mask._regions(regions, 2)
assert biggest_regions == [regions[0], regions[3]]
def test_regions_to_binary_mask():
regions = [
Region(
index=None,
area=None,
bbox=None,
center=None,
coords=np.array([[1, 3], [2, 3], [3, 2], [3, 3]]),
),
Region(
index=None,
area=None,
bbox=None,
center=None,
coords=np.array([[3, 7], [4, 7], [4, 8]]),
),
]
binary_mask_regions = regions_to_binary_mask(regions, dims=(10, 10))
assert type(binary_mask_regions) == np.ndarray
assert binary_mask_regions.dtype == bool
np.testing.assert_array_almost_equal(
binary_mask_regions,
load_expectation("mask-arrays/regions-to-binary-mask", type_="npy"),
)
def it_knows_its_biggest_regions(self):
regions = [
Region(index=0, area=14, bbox=(0, 0, 2, 2), center=(0.5, 0.5)),
Region(index=1, area=2, bbox=(0, 0, 2, 2), center=(0.5, 0.5)),
Region(index=2, area=5, bbox=(0, 0, 2, 2), center=(0.5, 0.5)),
Region(index=3, area=10, bbox=(0, 0, 2, 2), center=(0.5, 0.5)),
]
slide = Slide("a/b", "c/d")
biggest_regions = slide._biggest_regions(regions, 2)
assert biggest_regions == [regions[0], regions[3]]
def it_knows_regions_from_binary_mask(self, request):
binary_mask = np.array([[True, False], [True, True]])
label = function_mock(request, "histolab.util.label")
regionprops = function_mock(request, "histolab.util.regionprops")
RegionProps = namedtuple("RegionProps", ("area", "bbox", "centroid"))
regions_props = [
RegionProps(3, (0, 0, 2, 2),
(0.6666666666666666, 0.3333333333333333))
]
regionprops.return_value = regions_props
label(binary_mask).return_value = [[0, 1], [1, 1]]
regions_from_binary_mask_ = regions_from_binary_mask(binary_mask)
regionprops.assert_called_once_with(label(binary_mask))
assert type(regions_from_binary_mask_) == list
assert len(regions_from_binary_mask_) == 1
assert type(regions_from_binary_mask_[0]) == Region
assert regions_from_binary_mask_ == [
Region(
index=0,
area=regions_props[0].area,
bbox=regions_props[0].bbox,
center=regions_props[0].centroid,
)
]
def it_knows_its_region_coordinates(self):
region = Region(index=0, area=14, bbox=(0, 1, 1, 2), center=(0.5, 0.5))
slide = Slide("a/b", "c/d")
region_coords_ = slide._region_coordinates(region)
assert region_coords_ == CoordinatePair(x_ul=1, y_ul=0, x_br=2, y_br=1)
def test_region_coordinates():
region = Region(index=0,
area=14,
bbox=(0, 1, 1, 2),
center=(0.5, 0.5),
coords=None)
region_coords_ = region_coordinates(region)
assert region_coords_ == CP(x_ul=1, y_ul=0, x_br=2, y_br=1)
def it_knows_its_mask(
self,
request,
tmpdir,
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
RemoveSmallHoles_,
RemoveSmallObjects_,
):
slide, _ = base_test_slide(tmpdir,
PILIMG.RGBA_COLOR_500X500_155_249_240)
regions = [
Region(index=0,
area=33,
bbox=(0, 0, 2, 2),
center=(0.5, 0.5),
coords=None)
]
main_tissue_areas_mask_filters_ = property_mock(
request, _SlideFiltersComposition, "tissue_mask_filters")
main_tissue_areas_mask_filters_.return_value = Compose([
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
RemoveSmallHoles_,
RemoveSmallObjects_,
])
regions_from_binary_mask = function_mock(
request, "histolab.masks.regions_from_binary_mask")
regions_from_binary_mask.return_value = regions
biggest_regions_ = method_mock(request,
BiggestTissueBoxMask,
"_regions",
autospec=False)
biggest_regions_.return_value = regions
region_coordinates_ = function_mock(
request, "histolab.masks.region_coordinates")
region_coordinates_.return_values = CP(0, 0, 2, 2)
rectangle_to_mask_ = function_mock(request,
"histolab.util.rectangle_to_mask")
rectangle_to_mask_((1000, 1000), CP(0, 0, 2, 2)).return_value = [
[True, True],
[False, True],
]
biggest_mask_tissue_box = BiggestTissueBoxMask()
binary_mask = biggest_mask_tissue_box(slide)
np.testing.assert_almost_equal(binary_mask, np.zeros((500, 500)))
region_coordinates_.assert_called_once_with(regions[0])
biggest_regions_.assert_called_once_with(regions, n=1)
rectangle_to_mask_.assert_called_once_with((1000, 1000),
CP(x_ul=0,
y_ul=0,
x_br=2,
y_br=2))
def it_knows_its_biggest_tissue_box_mask(
self,
request,
tmpdir,
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
RemoveSmallHoles_,
RemoveSmallObjects_,
):
tmp_path_ = tmpdir.mkdir("myslide")
image = PILIMG.RGBA_COLOR_500X500_155_249_240
image.save(os.path.join(tmp_path_, "mywsi.png"), "PNG")
slide_path = os.path.join(tmp_path_, "mywsi.png")
slide = Slide(slide_path, "processed")
regions = [
Region(index=0, area=33, bbox=(0, 0, 2, 2), center=(0.5, 0.5))
]
main_tissue_areas_mask_filters_ = property_mock(
request, _SlideFiltersComposition, "tissue_mask_filters")
main_tissue_areas_mask_filters_.return_value = Compose([
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
RemoveSmallHoles_,
RemoveSmallObjects_,
])
regions_from_binary_mask = function_mock(
request, "histolab.slide.regions_from_binary_mask")
regions_from_binary_mask.return_value = regions
biggest_regions_ = method_mock(request,
Slide,
"_biggest_regions",
autospec=False)
biggest_regions_.return_value = regions
region_coordinates_ = function_mock(
request, "histolab.slide.region_coordinates")
region_coordinates_.return_values = CP(0, 0, 2, 2)
polygon_to_mask_array_ = function_mock(
request, "histolab.util.polygon_to_mask_array")
polygon_to_mask_array_((1000, 1000), CP(0, 0, 2, 2)).return_value = [
[True, True],
[False, True],
]
biggest_mask_tissue_box = slide.biggest_tissue_box_mask
region_coordinates_.assert_called_once_with(regions[0])
biggest_regions_.assert_called_once_with(regions, n=1)
polygon_to_mask_array_.assert_called_once_with((1000, 1000),
CP(x_ul=0,
y_ul=0,
x_br=2,
y_br=2))
np.testing.assert_almost_equal(biggest_mask_tissue_box,
np.zeros((500, 500)))
def but_it_raises_an_error_when_n_is_not_between_1_and_number_of_regions(
self, n):
regions = [
Region(i, i + 1, (0, 0, 2, 2), (0.5, 0.5)) for i in range(4)
]
slide = Slide("a/b", "c/d")
with pytest.raises(ValueError) as err:
slide._biggest_regions(regions, n)
assert str(
err.value) == f"n should be between 1 and {len(regions)}, got {n}"
