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fix issue #117 #201

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Merged
alessiamarcolini merged 1 commit into from
Dec 30, 2020
Merged

fix issue #117 #201

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24 changes: 0 additions & 24 deletions src/histolab/filters/image_filters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -953,30 +953,6 @@ def __repr__(self) -> str:
return self.__class__.__name__ + "()"


class PenMarks:
"""Filter out pen marks from a diagnostic slide.

Pen marks are removed by applying Otsu threshold on the H channel of the image
converted to the HSV space.

Parameters
---------
img : PIL.Image.Image
Input RGB image

Returns
-------
np.ndarray
Boolean NumPy array representing the mask with the pen marks filtered out.
"""

def __call__(self, img: PIL.Image.Image) -> PIL.Image.Image:
return F.pen_marks(img)

def __repr__(self) -> str:
return self.__class__.__name__ + "()"


class YenThreshold:
"""Mask image based on pixel above Yen threshold.

Expand Down
25 changes: 0 additions & 25 deletions src/histolab/filters/image_filters_functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -836,31 +836,6 @@ def otsu_threshold(
return threshold_to_mask(image, otsu_thresh, relate)


def pen_marks(img: PIL.Image.Image) -> np.ndarray:
"""Filter out pen marks from a diagnostic slide.

Pen marks are removed by applying Otsu threshold on the H channel of the image
converted to the HSV space.

Parameters
---------
img : PIL.Image.Image
Input RGB image

Returns
-------
np.ndarray
Boolean NumPy array representing the mask with the pen marks filtered out.
"""
if img.mode == "RGBA":
raise ValueError("Image input must be RGB, got RGBA.")
np_img = np.array(img)
np_hsv = sk_color.convert_colorspace(np_img, "RGB", "HSV")
hue = np_hsv[:, :, 0]
threshold = sk_filters.threshold_otsu(hue)
return threshold_to_mask(hue, threshold, operator.gt)


def red_filter(
img: PIL.Image.Image, red_thresh: int, green_thresh: int, blue_thresh: int
) -> np.ndarray:
Expand Down
37 changes: 1 addition & 36 deletions tests/integration/test_image_filters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1282,40 +1282,6 @@ def test_green_channel_filter_with_wrong_threshold(green_threshold):
assert str(err.value) == "threshold must be in range [0, 255]"


@pytest.mark.parametrize(
"rgb_img, expectation",
(
(
RGB.DIAGNOSTIC_SLIDE_THUMB_RGB,
"mask-arrays/diagnostic-slide-thumb-rgb-pen-marks-mask",
),
(
RGB.DIAGNOSTIC_SLIDE_THUMB_HSV,
"mask-arrays/diagnostic-slide-thumb-hsv-pen-marks-mask",
),
(
RGB.DIAGNOSTIC_SLIDE_THUMB_YCBCR,
"mask-arrays/diagnostic-slide-thumb-ycbcr-pen-marks-mask",
),
(RGB.TCGA_LUNG_RGB, "mask-arrays/tcga-lung-rgb-pen-marks-mask"),
),
)
def test_pen_marks_filter_on_rgb_image(rgb_img, expectation):
pen_marks_filter = imf.pen_marks(rgb_img)

np.testing.assert_array_equal(
pen_marks_filter, load_expectation(expectation, type_="npy")
)


def test_pen_marks_filter_with_wrong_img_mode():
with pytest.raises(ValueError) as err:
imf.pen_marks(RGBA.DIAGNOSTIC_SLIDE_THUMB)

assert isinstance(err.value, ValueError)
assert str(err.value) == "Image input must be RGB, got RGBA."


@pytest.mark.parametrize(
"pil_img, red_thresh, green_thresh, blue_thresh, expected_value",
(
Expand Down Expand Up @@ -1704,8 +1670,7 @@ def test_rgb_to_lab_filter_with_rgb_image(pil_image, expected_image):


@pytest.mark.parametrize(
"pil_image",
(RGBA.DIAGNOSTIC_SLIDE_THUMB, GS.DIAGNOSTIC_SLIDE_THUMB_GS),
"pil_image", (RGBA.DIAGNOSTIC_SLIDE_THUMB, GS.DIAGNOSTIC_SLIDE_THUMB_GS),
)
def test_rgb_to_lab_raises_exception_on_gs_and_rgba_image(pil_image):
with pytest.raises(Exception) as err:
Expand Down
13 changes: 0 additions & 13 deletions tests/unit/filters/test_image_filters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -348,19 +348,6 @@ def it_calls_blue_pen_filter_functional(self, request):
F_blue_pen_filter.assert_called_once_with(image)
assert type(blue_pen_filter(image)) == np.ndarray

def it_calls_pen_marks_filter_functional(self, request):
image = PILIMG.RGBA_COLOR_500X500_155_249_240
F_pen_marks = function_mock(
request, "histolab.filters.image_filters_functional.pen_marks"
)
F_pen_marks.return_value = np.array(image)
pen_marks = imf.PenMarks()

pen_marks(image)

F_pen_marks.assert_called_once_with(image)
assert type(pen_marks(image)) == np.ndarray

def it_calls_np_to_pil(self, request):
array = NpArrayMock.ONES_30X30_UINT8
util_np_to_pil = function_mock(request, "histolab.util.np_to_pil")
Expand Down