def test_selem_overflow():
    strel = np.ones((17, 17), dtype=np.uint8)
    img = np.zeros((20, 20), dtype=bool)
    img[2:19, 2:19] = True
    binary_res = binary.binary_erosion(img, strel)
    gray_res = img_as_bool(gray.erosion(img, strel))
    testing.assert_array_equal(binary_res, gray_res)
def test_selem_overflow():
    strel = np.ones((17, 17), dtype=np.uint8)
    img = np.zeros((20, 20), dtype=bool)
    img[2:19, 2:19] = True
    binary_res = binary.binary_erosion(img, strel)
    grey_res = img_as_bool(grey.erosion(img, strel))
    testing.assert_array_equal(binary_res, grey_res)
def test_footprint_overflow():
    footprint = np.ones((17, 17), dtype=np.uint8)
    img = np.zeros((20, 20), dtype=bool)
    img[2:19, 2:19] = True
    binary_res = binary.binary_erosion(img, footprint)
    gray_res = img_as_bool(gray.erosion(img, footprint))
    assert_array_equal(binary_res, gray_res)
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def test_selem_overflow():
    strel = np.ones((17, 17), dtype=np.uint8)
    img = np.zeros((20, 20))
    img[2:19, 2:19] = 1
    binary_res = binary.binary_erosion(img, strel)
    with expected_warnings(['precision loss']):
        grey_res = img_as_bool(grey.erosion(img, strel))
    testing.assert_array_equal(binary_res, grey_res)
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    def mark_areas(image: np.ndarray) -> Tuple[np.ndarray, int]:
        """
        Method to segment clustered areas

        :param image: The image to segment
        :return: The segmented area
        """
        # Define mask
        mask = create_circular_mask(40, 40)
        # Fill image
        fill = binary_fill_holes(image)
        # Perform binary erosion on image
        er = binary_erosion(fill, selem=mask)
        # Label eroded map
        lab, nums = label(er)
        # Dilate eroded map
        lab = dilation(lab, selem=mask)
        return lab, nums
def test_binary_erosion():
    strel = selem.square(3)
    binary_res = binary.binary_erosion(bw_img, strel)
    grey_res = img_as_bool(grey.erosion(bw_img, strel))
    testing.assert_array_equal(binary_res, grey_res)
def test_non_square_image():
    strel = selem.square(3)
    binary_res = binary.binary_erosion(bw_img[:100, :200], strel)
    grey_res = img_as_bool(grey.erosion(bw_img[:100, :200], strel))
    testing.assert_array_equal(binary_res, grey_res)
def test_binary_erosion():
    strel = selem.square(3)
    binary_res = binary.binary_erosion(bw_img, strel)
    gray_res = img_as_bool(gray.erosion(bw_img, strel))
    testing.assert_array_equal(binary_res, gray_res)
def test_non_square_image():
    strel = selem.square(3)
    binary_res = binary.binary_erosion(bw_img[:100, :200], strel)
    gray_res = img_as_bool(gray.erosion(bw_img[:100, :200], strel))
    testing.assert_array_equal(binary_res, gray_res)
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def test_binary_erosion():
    footprint = morphology.square(3)
    binary_res = binary.binary_erosion(bw_img, footprint)
    gray_res = img_as_bool(gray.erosion(bw_img, footprint))
    assert_array_equal(binary_res, gray_res)
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def test_non_square_image():
    footprint = morphology.square(3)
    binary_res = binary.binary_erosion(bw_img[:100, :200], footprint)
    gray_res = img_as_bool(gray.erosion(bw_img[:100, :200], footprint))
    assert_array_equal(binary_res, gray_res)
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def test_binary_erosion():
    strel = selem.square(3)
    binary_res = binary.binary_erosion(bw_img, strel)
    with expected_warnings(['precision loss']):
        grey_res = img_as_bool(grey.erosion(bw_img, strel))
    testing.assert_array_equal(binary_res, grey_res)
def test_binary_erosion():
    strel = selem.square(3)
    binary_res = binary.binary_erosion(bw_lena, strel)
    grey_res = grey.erosion(bw_lena, strel)
    testing.assert_array_equal(binary_res, grey_res)