def it_knows_its_tissue_ratio(
self,
request,
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
BinaryFillHoles_,
):
_tile_tissue_mask_filters = property_mock(request,
_TileFiltersComposition,
"tissue_mask_filters")
filters = Compose([
RgbToGrayscale_, OtsuThreshold_, BinaryDilation_, BinaryFillHoles_
])
_tile_tissue_mask_filters.return_value = filters
_call = method_mock(request, Compose, "__call__")
_call.return_value = COMPLEX_MASK
image = PILIMG.RGB_RANDOM_COLOR_10X10
tile = Tile(image, None, 0)
tissue_ratio = tile.tissue_ratio
_tile_tissue_mask_filters.assert_called_once()
_call.assert_called_once_with(filters, image)
assert type(tissue_ratio) == float
assert tissue_ratio == 0.61
def it_knows_its_mask(
self,
request,
tmpdir,
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
RemoveSmallHoles_,
):
slide, _ = base_test_slide(tmpdir,
PILIMG.RGBA_COLOR_500X500_155_249_240)
main_tissue_areas_mask_filters_ = property_mock(
request, _SlideFiltersComposition, "tissue_mask_filters")
expected_mask = [
[True, True],
[False, True],
]
remove_small_objects = method_mock(request, RemoveSmallObjects,
"__call__")
remove_small_objects.return_value = expected_mask
main_tissue_areas_mask_filters_.return_value = Compose([
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
RemoveSmallHoles_,
RemoveSmallObjects(),
])
tissue_mask = TissueMask()
binary_mask = tissue_mask(slide)
assert binary_mask == expected_mask
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 it_knows_its_tissue_mask(
self,
request,
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
BinaryFillHoles_,
):
BinaryFillHoles_.return_value = np.zeros((50, 50))
filters = Compose([
RgbToGrayscale_, OtsuThreshold_, BinaryDilation_, BinaryFillHoles_
])
image = PILIMG.RGBA_COLOR_50X50_155_0_0
tile = Tile(image, None, 0)
tissue_mask = tile._tissue_mask(filters)
assert tissue_mask.shape == (50, 50)
def it_calls_tile_tissue_mask_filters(
self,
request,
RgbToGrayscale_,
OtsuThreshold_,
BinaryDilation_,
BinaryFillHoles_,
):
_tissue_mask_filters = property_mock(request, _TileFiltersComposition,
"tissue_mask_filters")
BinaryFillHoles_.return_value = np.zeros((50, 50))
_tissue_mask_filters.return_value = Compose([
RgbToGrayscale_, OtsuThreshold_, BinaryDilation_, BinaryFillHoles_
])
image = PILIMG.RGBA_COLOR_50X50_155_0_0
tile = Tile(image, None, 0)
tile._has_only_some_tissue()
_tissue_mask_filters.assert_called_once()
assert type(tile._has_only_some_tissue()) == np.bool_