def test_threshold_minimum():
camera = util.img_as_ubyte(camerad)
threshold = threshold_minimum(camera)
assert_array_equal(threshold, 85)
astronaut = util.img_as_ubyte(astronautd)
threshold = threshold_minimum(astronaut)
assert_array_equal(threshold, 114)
def test_li_astro_image():
image = util.img_as_ubyte(astronautd)
threshold = threshold_li(image)
ce_actual = _cross_entropy(image, threshold)
assert 64 < threshold < 65
assert ce_actual < _cross_entropy(image, threshold + 1)
assert ce_actual < _cross_entropy(image, threshold - 1)
def test_li_camera_image():
image = util.img_as_ubyte(camerad)
threshold = threshold_li(image)
ce_actual = _cross_entropy(image, threshold)
assert 78 < threshold_li(image) < 79
assert ce_actual < _cross_entropy(image, threshold + 1)
assert ce_actual < _cross_entropy(image, threshold - 1)
def test_gray2rgba_dtype():
img_f64 = cp.random.random((5, 5))
img_f32 = img_f64.astype('float32')
img_u8 = img_as_ubyte(img_f64)
img_int = img_u8.astype(int)
for img in [img_f64, img_f32, img_u8, img_int]:
assert gray2rgba(img).dtype == img.dtype
def test_isodata_camera_image():
camera = util.img_as_ubyte(camerad)
threshold = threshold_isodata(camera)
assert np.floor((camera[camera <= threshold].mean() +
camera[camera > threshold].mean()) / 2.0) == threshold
assert threshold == 102
assert_array_equal(threshold_isodata(camera, return_all=True), [102, 103])
def test_isodata_coins_image():
coins = util.img_as_ubyte(coinsd)
threshold = threshold_isodata(coins)
assert np.floor((coins[coins <= threshold].mean() +
coins[coins > threshold].mean()) / 2.0) == threshold
assert threshold == 107
assert_array_equal(threshold_isodata(coins, return_all=True), [107])
def test_isodata_moon_image_negative_float():
moon = util.img_as_ubyte(moond).astype(cp.float64)
moon -= 100
assert -14 < threshold_isodata(moon) < -13
thresholds = threshold_isodata(moon, return_all=True)
# fmt: off
assert_array_almost_equal(thresholds,
[-13.83789062, -12.84179688, -11.84570312, 22.02148438, # noqa
23.01757812, 24.01367188, 38.95507812, 39.95117188]) # noqa
def test_li_coins_image():
image = util.img_as_ubyte(coinsd)
threshold = threshold_li(image)
ce_actual = _cross_entropy(image, threshold)
assert 94 < threshold_li(image) < 95
assert ce_actual < _cross_entropy(image, threshold + 1)
# in the case of the coins image, the minimum cross-entropy is achieved one
# threshold below that found by the iterative method. Not sure why that is
# but `threshold_li` does find the stationary point of the function (ie the
# tolerance can be reduced arbitrarily but the exact same threshold is
# found), so my guess is some kind of histogram binning effect.
assert ce_actual < _cross_entropy(image, threshold - 2)
def test_isodata_moon_image():
moon = util.img_as_ubyte(moond)
threshold = threshold_isodata(moon)
assert np.floor((moon[moon <= threshold].mean() +
moon[moon > threshold].mean()) / 2.0) == threshold
assert threshold == 86
thresholds = threshold_isodata(moon, return_all=True)
for threshold in thresholds:
assert np.floor((moon[moon <= threshold].mean() +
moon[moon > threshold].mean()) / 2.0) == threshold
assert_array_equal(thresholds, [86, 87, 88, 122, 123, 124, 139, 140])
def test_isodata_moon_image_negative_int():
moon = util.img_as_ubyte(moond).astype(cp.int32)
moon -= 100
threshold = threshold_isodata(moon)
assert np.floor((moon[moon <= threshold].mean() +
moon[moon > threshold].mean()) / 2.0) == threshold
assert threshold == -14
thresholds = threshold_isodata(moon, return_all=True)
for threshold in thresholds:
assert np.floor((moon[moon <= threshold].mean() +
moon[moon > threshold].mean()) / 2.0) == threshold
assert_array_equal(thresholds, [-14, -13, -12, 22, 23, 24, 39, 40])
def _build_expected_output(self):
funcs = (grey.erosion, grey.dilation, grey.opening, grey.closing,
grey.white_tophat, grey.black_tophat)
selems_2D = (selem.square, selem.diamond, selem.disk, selem.star)
image = img_as_ubyte(
transform.downscale_local_mean(
color.rgb2gray(cp.array(data.coffee())), (20, 20)))
output = {}
for n in range(1, 4):
for strel in selems_2D:
for func in funcs:
key = '{0}_{1}_{2}'.format(strel.__name__, n,
func.__name__)
output[key] = func(image, strel(n))
return output
def test_gray2rgba_alpha():
img = cp.random.random((5, 5))
img_u8 = img_as_ubyte(img)
# Default
alpha = None
rgba = gray2rgba(img, alpha)
assert_array_equal(rgba[..., :3], gray2rgb(img))
assert_array_equal(rgba[..., 3], 1.0)
# Scalar
alpha = 0.5
rgba = gray2rgba(img, alpha)
assert_array_equal(rgba[..., :3], gray2rgb(img))
assert_array_equal(rgba[..., 3], alpha)
# Array
alpha = cp.random.random((5, 5))
rgba = gray2rgba(img, alpha)
assert_array_equal(rgba[..., :3], gray2rgb(img))
assert_array_equal(rgba[..., 3], alpha)
# Warning about alpha cast
alpha = 0.5
with expected_warnings(["alpha can't be safely cast to image dtype"]):
rgba = gray2rgba(img_u8, alpha)
assert_array_equal(rgba[..., :3], gray2rgb(img_u8))
# Invalid shape
alpha = cp.random.random((5, 5, 1))
# expected_err_msg = ("could not broadcast input array from shape (5,5,1) "
# "into shape (5,5)")
with pytest.raises(ValueError): # as err:
rgba = gray2rgba(img, alpha)
def test_threshold_minimum_histogram():
camera = util.img_as_ubyte(camerad)
hist = histogram(camera.ravel(), 256, source_range='image')
threshold = threshold_minimum(hist=hist)
assert_array_equal(threshold, 85)
def test_otsu_camera_image():
camera = util.img_as_ubyte(camerad)
assert 101 < threshold_otsu(camera) < 103
def test_isodata_camera_image_histogram():
camera = util.img_as_ubyte(camerad)
hist = histogram(camera.ravel(), 256, source_range='image')
threshold = threshold_isodata(hist=hist)
assert threshold == 102
def test_isodata_camera_image_counts():
camera = util.img_as_ubyte(camerad)
counts, bin_centers = histogram(camera.ravel(), 256, source_range='image')
threshold = threshold_isodata(hist=counts)
assert threshold == 102
def test_yen_coins_image():
coins = util.img_as_ubyte(coinsd)
assert 109 < threshold_yen(coins) < 111
def test_otsu_camera_image_histogram():
camera = util.img_as_ubyte(camerad)
hist = histogram(camera.ravel(), 256, source_range="image")
assert 101 < threshold_otsu(hist=hist) < 103
def test_yen_camera_image_counts():
camera = util.img_as_ubyte(camerad)
counts, bin_centers = histogram(camera.ravel(), 256, source_range='image')
assert 145 < threshold_yen(hist=counts) < 147
def test_hed_rgb_roundtrip(self):
img_rgb = img_as_ubyte(self.img_rgb)
new = img_as_ubyte(hed2rgb(rgb2hed(img_rgb)))
assert_array_equal(new, img_rgb)
def test_otsu_camera_image_counts():
camera = util.img_as_ubyte(camerad)
counts, bin_centers = histogram(camera.ravel(), 256, source_range="image")
assert 101 < threshold_otsu(hist=counts) < 103
def test_otsu_coins_image():
coins = util.img_as_ubyte(coinsd)
assert 106 < threshold_otsu(coins) < 108
def test_otsu_astro_image():
img = util.img_as_ubyte(astronautd)
with expected_warnings(['grayscale']):
assert 109 < threshold_otsu(img) < 111
def test_multiotsu_astro_image():
img = util.img_as_ubyte(astronautd)
with expected_warnings(['grayscale']):
assert_array_almost_equal(threshold_multiotsu(img), [58, 149])
def test_hdx_rgb_roundtrip(self):
from cucim.skimage.color.colorconv import hdx_from_rgb, rgb_from_hdx
img_rgb = self.img_rgb
conv = combine_stains(separate_stains(img_rgb, hdx_from_rgb),
rgb_from_hdx)
assert_array_equal(img_as_ubyte(conv), img_rgb)
def test_threshold_minimum_counts():
camera = util.img_as_ubyte(camerad)
counts, bin_centers = histogram(camera.ravel(), 256, source_range='image')
threshold = threshold_minimum(hist=counts)
assert_array_equal(threshold, 85)
def test_yen_camera_image():
camera = util.img_as_ubyte(camerad)
assert 145 < threshold_yen(camera) < 147
def test_yen_camera_image_histogram():
camera = util.img_as_ubyte(camerad)
hist = histogram(camera.ravel(), 256, source_range="image")
assert 145 < threshold_yen(hist=hist) < 147
def test_equalize_ubyte():
img = util.img_as_ubyte(test_img)
img_eq = exposure.equalize_hist(img)
cdf, bin_edges = exposure.cumulative_distribution(img_eq)
check_cdf_slope(cdf)
