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STY: Image comparison functions now share common prefix

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This commit is contained in:
Joshua Warner
2016-01-31 23:04:25 -07:00
parent a08d75a786
commit b218cfdd81
5 changed files with 61 additions and 32 deletions
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skimage/measure/__init__.py
+8 -5
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@@ -2,8 +2,8 @@ from ._find_contours import find_contours
from ._marching_cubes import (marching_cubes, mesh_surface_area,
correct_mesh_orientation)
from ._regionprops import regionprops, perimeter
from .simple_metrics import mean_squared_error, normalized_root_mse, psnr
from ._structural_similarity import structural_similarity
from .simple_metrics import compare_mse, compare_nrmse, compare_psnr
from ._structural_similarity import compare_ssim, structural_similarity
from ._polygon import approximate_polygon, subdivide_polygon
from ._pnpoly import points_in_poly, grid_points_in_poly
from ._moments import moments, moments_central, moments_normalized, moments_hu
@@ -36,6 +36,9 @@ __all__ = ['find_contours',
'label',
'points_in_poly',
'grid_points_in_poly',
'mean_squared_error',
'normalized_root_mse',
'psnr']
'structural_similarity',
'compare_ssim',
'compare_mse',
'compare_nrmse',
'compare_psnr',
]
skimage/measure/_structural_similarity.py
+16 -4
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@@ -1,17 +1,19 @@
from __future__ import division
__all__ = ['structural_similarity']
__all__ = ['compare_ssim',
'structural_similarity']
import numpy as np
from scipy.ndimage import uniform_filter, gaussian_filter
from ..util.dtype import dtype_range
from ..util.arraypad import crop
from .._shared.utils import deprecated
def structural_similarity(X, Y, win_size=None, gradient=False,
dynamic_range=None, multichannel=False,
gaussian_weights=False, full=False, **kwargs):
def compare_ssim(X, Y, win_size=None, gradient=False,
dynamic_range=None, multichannel=False,
gaussian_weights=False, full=False, **kwargs):
"""Compute the mean structural similarity index between two images.
Parameters
@@ -216,3 +218,13 @@ def structural_similarity(X, Y, win_size=None, gradient=False,
return mssim, S
else:
return mssim
@deprecated('compare_ssim')
def structural_similarity(X, Y, win_size=None, gradient=False,
dynamic_range=None, multichannel=False,
gaussian_weights=False, full=False, **kwargs):
"""""" + compare_ssim.__doc__
return compare_ssim(X, Y, win_size=None, gradient=False,
dynamic_range=None, multichannel=False,
gaussian_weights=False, full=False, **kwargs)
skimage/measure/simple_metrics.py
+9 -6
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@@ -3,7 +3,10 @@ from __future__ import division
import numpy as np
from ..util.dtype import dtype_range
__all__ = ['mean_squared_error', 'normalized_root_mse', 'psnr']
__all__ = ['compare_mse',
'compare_nrmse',
'compare_psnr',
]
def _assert_compatible(im1, im2):
@@ -25,7 +28,7 @@ def _as_floats(im1, im2):
return im1, im2
def mean_squared_error(im1, im2):
def compare_mse(im1, im2):
"""Compute the mean-squared error between two images.
Parameters
@@ -44,7 +47,7 @@ def mean_squared_error(im1, im2):
return np.mean(np.square(im1 - im2), dtype=np.float64)
def normalized_root_mse(im_true, im_test, norm_type='Euclidean'):
def compare_nrmse(im_true, im_test, norm_type='Euclidean'):
"""Compute the normalized root mean-squared error (NRMSE) between two
images.
@@ -85,10 +88,10 @@ def normalized_root_mse(im_true, im_test, norm_type='Euclidean'):
denom = im_true.mean()
else:
raise ValueError("Unsupported norm_type")
return np.sqrt(mean_squared_error(im_true, im_test)) / denom
return np.sqrt(compare_mse(im_true, im_test)) / denom
def psnr(im_true, im_test, dynamic_range=None):
def compare_psnr(im_true, im_test, dynamic_range=None):
""" Compute the peak signal to noise ratio (PSNR) for an image.
Parameters
@@ -128,5 +131,5 @@ def psnr(im_true, im_test, dynamic_range=None):
im_true, im_test = _as_floats(im_true, im_test)
err = mean_squared_error(im_true, im_test)
err = compare_mse(im_true, im_test)
return 10 * np.log10((dynamic_range ** 2) / err)
skimage/measure/tests/test_simple_metrics.py
+16 -16
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@@ -2,7 +2,7 @@ import numpy as np
from numpy.testing import (run_module_suite, assert_equal, assert_raises,
assert_almost_equal)
from skimage.measure import psnr, normalized_root_mse, mean_squared_error
from skimage.measure import compare_psnr, compare_nrmse, compare_mse
import skimage.data
np.random.seed(5)
@@ -16,45 +16,45 @@ def test_PSNR_vs_IPOL():
# Tests vs. imdiff result from the following IPOL article and code:
# http://www.ipol.im/pub/art/2011/g_lmii/
p_IPOL = 22.4497
p = psnr(cam, cam_noisy)
p = compare_psnr(cam, cam_noisy)
assert_almost_equal(p, p_IPOL, decimal=4)
def test_PSNR_float():
p_uint8 = psnr(cam, cam_noisy)
p_float64 = psnr(cam/255., cam_noisy/255., dynamic_range=1)
p_uint8 = compare_psnr(cam, cam_noisy)
p_float64 = compare_psnr(cam/255., cam_noisy/255., dynamic_range=1)
assert_almost_equal(p_uint8, p_float64, decimal=5)
def test_PSNR_errors():
assert_raises(ValueError, psnr, cam, cam.astype(np.float32))
assert_raises(ValueError, psnr, cam, cam[:-1, :])
assert_raises(ValueError, compare_psnr, cam, cam.astype(np.float32))
assert_raises(ValueError, compare_psnr, cam, cam[:-1, :])
def test_NRMSE():
x = np.ones(4)
y = np.asarray([0., 2., 2., 2.])
assert_equal(normalized_root_mse(y, x, 'mean'), 1/np.mean(y))
assert_equal(normalized_root_mse(y, x, 'Euclidean'), 1/np.sqrt(3))
assert_equal(normalized_root_mse(y, x, 'min-max'), 1/(y.max()-y.min()))
assert_equal(compare_nrmse(y, x, 'mean'), 1/np.mean(y))
assert_equal(compare_nrmse(y, x, 'Euclidean'), 1/np.sqrt(3))
assert_equal(compare_nrmse(y, x, 'min-max'), 1/(y.max()-y.min()))
def test_NRMSE_no_int_overflow():
camf = cam.astype(np.float32)
cam_noisyf = cam_noisy.astype(np.float32)
assert_almost_equal(mean_squared_error(cam, cam_noisy),
mean_squared_error(camf, cam_noisyf))
assert_almost_equal(normalized_root_mse(cam, cam_noisy),
normalized_root_mse(camf, cam_noisyf))
assert_almost_equal(compare_mse(cam, cam_noisy),
compare_mse(camf, cam_noisyf))
assert_almost_equal(compare_nrmse(cam, cam_noisy),
compare_nrmse(camf, cam_noisyf))
def test_NRMSE_errors():
x = np.ones(4)
assert_raises(ValueError, normalized_root_mse,
assert_raises(ValueError, compare_nrmse,
x.astype(np.uint8), x.astype(np.float32))
assert_raises(ValueError, normalized_root_mse, x[:-1], x)
assert_raises(ValueError, compare_nrmse, x[:-1], x)
# invalid normalization name
assert_raises(ValueError, normalized_root_mse, x, x, 'foo')
assert_raises(ValueError, compare_nrmse, x, x, 'foo')
if __name__ == "__main__":
skimage/measure/tests/test_structural_similarity.py
+12 -1
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@@ -4,10 +4,11 @@ import scipy.io
from numpy.testing import (assert_equal, assert_raises, assert_almost_equal,
assert_array_almost_equal)
from skimage.measure import structural_similarity as ssim
from skimage.measure import compare_ssim as ssim
import skimage.data
from skimage.io import imread
from skimage import data_dir
from skimage._shared._warnings import expected_warnings
np.random.seed(5)
cam = skimage.data.camera()
@@ -18,6 +19,16 @@ cam_noisy = cam_noisy.astype(cam.dtype)
np.random.seed(1234)
# This test to be removed in 0.14, along with the structural_similarity alias
# for compare_ssim
def test_old_name_deprecated():
from skimage.measure import structural_similarity
with expected_warnings('Call to deprecated function '
'``structural_similarity``. Use '
'``compare_ssim`` instead.'):
ssim_result = structural_similarity(cam, cam_noisy, win_size=32)
def test_ssim_patch_range():
N = 51
X = (np.random.rand(N, N) * 255).astype(np.uint8)