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Remove cast and rescale and adjust test values to match

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This commit is contained in:
Tony S Yu
2014-07-16 23:24:03 -05:00
parent c24adec714
commit d9a39d44eb
2 changed files with 18 additions and 22 deletions
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skimage/color/adapt_rgb.py
+1 -4
View File
@@ -56,11 +56,8 @@ def hsv_value(image_filter, image, *args, **kwargs):
image : array
Input image. Note that RGBA images are treated as RGB.
"""
# XXX: Are these 2 lines really necessary?
image = img_as_float(image[:, :, :3])
image = rescale_intensity(image)
# Slice the first three channels so that we remove any alpha channels.
hsv = color.rgb2hsv(image)
hsv = color.rgb2hsv(image[:, :, :3])
value = hsv[:, :, 2].copy()
value = image_filter(value, *args, **kwargs)
hsv[:, :, 2] = convert(value, hsv.dtype)
skimage/exposure/tests/test_exposure.py
+17 -18
View File
@@ -145,8 +145,8 @@ def test_rescale_uint14_limits():
# ====================================
def test_adapthist_scalar():
'''Test a scalar uint8 image
'''
"""Test a scalar uint8 image
"""
img = skimage.img_as_ubyte(data.moon())
adapted = exposure.equalize_adapthist(img, clip_limit=0.02)
assert adapted.min() == 0.0
@@ -162,8 +162,8 @@ def test_adapthist_scalar():
def test_adapthist_grayscale():
'''Test a grayscale float image
'''
"""Test a grayscale float image
"""
img = skimage.img_as_float(data.lena())
img = rgb2gray(img)
img = np.dstack((img, img, img))
@@ -171,14 +171,14 @@ def test_adapthist_grayscale():
nbins=128)
assert_almost_equal = np.testing.assert_almost_equal
assert img.shape == adapted.shape
assert_almost_equal(peak_snr(img, adapted), 104.307, 3)
assert_almost_equal(peak_snr(img, adapted), 104.3277, 3)
assert_almost_equal(norm_brightness_err(img, adapted), 0.0265, 3)
return data, adapted
def test_adapthist_color():
'''Test an RGB color uint16 image
'''
"""Test an RGB color uint16 image
"""
img = skimage.img_as_uint(data.lena())
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
@@ -191,15 +191,14 @@ def test_adapthist_color():
assert adapted.max() == 1.0
assert img.shape == adapted.shape
full_scale = skimage.exposure.rescale_intensity(img)
assert_almost_equal(peak_snr(full_scale, adapted), 105.50517, 3)
assert_almost_equal(norm_brightness_err(full_scale, adapted),
0.0544, 3)
assert_almost_equal(peak_snr(full_scale, adapted), 106.9, 1)
assert_almost_equal(norm_brightness_err(full_scale, adapted), 0.05, 2)
return data, adapted
def test_adapthist_alpha():
'''Test an RGBA color image
'''
"""Test an RGBA color image
"""
img = skimage.img_as_float(data.lena())
alpha = np.ones((img.shape[0], img.shape[1]), dtype=float)
img = np.dstack((img, alpha))
@@ -209,12 +208,12 @@ def test_adapthist_alpha():
full_scale = skimage.exposure.rescale_intensity(img)
assert img.shape == adapted.shape
assert_almost_equal = np.testing.assert_almost_equal
assert_almost_equal(peak_snr(full_scale, adapted), 105.50198, 3)
assert_almost_equal(norm_brightness_err(full_scale, adapted), 0.0544, 3)
assert_almost_equal(peak_snr(full_scale, adapted), 106.86, 2)
assert_almost_equal(norm_brightness_err(full_scale, adapted), 0.0509, 3)
def peak_snr(img1, img2):
'''Peak signal to noise ratio of two images
"""Peak signal to noise ratio of two images
Parameters
----------
@@ -225,7 +224,7 @@ def peak_snr(img1, img2):
-------
peak_snr : float
Peak signal to noise ratio
'''
"""
if img1.ndim == 3:
img1, img2 = rgb2gray(img1.copy()), rgb2gray(img2.copy())
img1 = skimage.img_as_float(img1)
@@ -236,7 +235,7 @@ def peak_snr(img1, img2):
def norm_brightness_err(img1, img2):
'''Normalized Absolute Mean Brightness Error between two images
"""Normalized Absolute Mean Brightness Error between two images
Parameters
----------
@@ -247,7 +246,7 @@ def norm_brightness_err(img1, img2):
-------
norm_brightness_error : float
Normalized absolute mean brightness error
'''
"""
if img1.ndim == 3:
img1, img2 = rgb2gray(img1), rgb2gray(img2)
ambe = np.abs(img1.mean() - img2.mean())