wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-02 19:39:55 +08:00
Code Issues Packages Projects Releases Wiki Activity

cut long lines

Browse Source
This commit is contained in:
Olivier Debeir
2012-10-18 10:12:19 +02:00
parent e618c1d454
commit 53deddf5e0
3 changed files with 40 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/filter/rank/bilateral_rank.py
+6 -3
View File
@@ -45,7 +45,8 @@ def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y, s0, s1):
bitdepth = find_bitdepth(image)
if bitdepth > 11:
raise ValueError("only uint16 <4096 image (12bit) supported!")
return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out, s0=s0, s1=s1)
return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out,
s0=s0, s1=s1)
def bilateral_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10, s1=10):
@@ -109,7 +110,8 @@ def bilateral_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=Fal
"""
return _apply(None, _crank16_bilateral.mean, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, s0=s0, s1=s1)
return _apply(None, _crank16_bilateral.mean, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y,
s0=s0, s1=s1)
def bilateral_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10, s1=10):
@@ -173,7 +175,8 @@ def bilateral_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=Fals
"""
return _apply(None, _crank16_bilateral.pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, s0=s0, s1=s1)
return _apply(None, _crank16_bilateral.pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y,
s0=s0, s1=s1)
if __name__ == "__main__":
import sys
skimage/filter/rank/percentile_rank.py
+18 -9
View File
@@ -35,7 +35,8 @@ def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y, p0, p1):
bitdepth = find_bitdepth(image)
if bitdepth > 11:
raise ValueError("only uint16 <4096 image (12bit) supported!")
return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out, p0=p0, p1=p1)
return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out,
p0=p0, p1=p1)
else:
raise TypeError("only uint8 and uint16 image supported!")
@@ -101,7 +102,8 @@ def percentile_autolevel(image, selem, out=None, mask=None, shift_x=False, shift
"""
return _apply(_crank8_percentiles.autolevel, _crank16_percentiles.autolevel, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.autolevel, _crank16_percentiles.autolevel, image, selem, out=out, mask=mask,
shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
def percentile_gradient(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -165,7 +167,8 @@ def percentile_gradient(image, selem, out=None, mask=None, shift_x=False, shift_
"""
return _apply(_crank8_percentiles.gradient, _crank16_percentiles.gradient, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.gradient, _crank16_percentiles.gradient, image, selem, out=out, mask=mask,
shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
def percentile_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -229,7 +232,8 @@ def percentile_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=Fa
"""
return _apply(_crank8_percentiles.mean, _crank16_percentiles.mean, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.mean, _crank16_percentiles.mean, image, selem, out=out, mask=mask,
shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
def percentile_mean_substraction(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -293,7 +297,8 @@ def percentile_mean_substraction(image, selem, out=None, mask=None, shift_x=Fals
"""
return _apply(_crank8_percentiles.mean_substraction, _crank16_percentiles.mean_substraction, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.mean_substraction, _crank16_percentiles.mean_substraction, image, selem, out=out,
mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
def percentile_morph_contr_enh(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -357,7 +362,8 @@ def percentile_morph_contr_enh(image, selem, out=None, mask=None, shift_x=False,
"""
return _apply(_crank8_percentiles.morph_contr_enh, _crank16_percentiles.morph_contr_enh, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.morph_contr_enh, _crank16_percentiles.morph_contr_enh, image, selem, out=out,
mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -422,7 +428,8 @@ def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False,
"""
return _apply(_crank8_percentiles.percentile, _crank16_percentiles.percentile, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.percentile, _crank16_percentiles.percentile, image, selem, out=out, mask=mask,
shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
def percentile_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -486,7 +493,8 @@ def percentile_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=Fal
"""
return _apply(_crank8_percentiles.pop, _crank16_percentiles.pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.pop, _crank16_percentiles.pop, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y, p0=p0, p1=p1)
def percentile_threshold(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.):
@@ -551,7 +559,8 @@ def percentile_threshold(image, selem, out=None, mask=None, shift_x=False, shift
"""
return _apply(_crank8_percentiles.threshold, _crank16_percentiles.threshold, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
return _apply(_crank8_percentiles.threshold, _crank16_percentiles.threshold, image, selem, out=out, mask=mask,
shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1)
if __name__ == "__main__":
skimage/filter/rank/rank.py
+16 -8
View File
@@ -18,7 +18,8 @@ from skimage.filter.rank import _crank8, _crank16
from skimage.filter.rank.generic import find_bitdepth
__all__ = ['autolevel', 'bottomhat', 'equalize', 'gradient', 'maximum', 'mean', 'meansubstraction', 'median', 'minimum', 'modal', 'morph_contr_enh', 'pop', 'threshold', 'tophat']
__all__ = ['autolevel', 'bottomhat', 'equalize', 'gradient', 'maximum', 'mean', 'meansubstraction', 'median', 'minimum',
'modal', 'morph_contr_enh', 'pop', 'threshold', 'tophat']
def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y):
@@ -95,7 +96,8 @@ def autolevel(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
"""
return _apply(_crank8.autolevel, _crank16.autolevel, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.autolevel, _crank16.autolevel, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y)
def bottomhat(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
@@ -156,7 +158,8 @@ def bottomhat(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
[ 0, 0, 0, 0, 0]], dtype=uint16)
"""
return _apply(_crank8.bottomhat, _crank16.bottomhat, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.bottomhat, _crank16.bottomhat, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y)
def equalize(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
@@ -217,7 +220,8 @@ def equalize(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
[3071, 2730, 2047, 2730, 3071]], dtype=uint16)
"""
return _apply(_crank8.equalize, _crank16.equalize, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.equalize, _crank16.equalize, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y)
def gradient(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
@@ -279,7 +283,8 @@ def gradient(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
"""
return _apply(_crank8.gradient, _crank16.gradient, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.gradient, _crank16.gradient, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y)
def maximum(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
@@ -465,7 +470,8 @@ def meansubstraction(image, selem, out=None, mask=None, shift_x=False, shift_y=F
"""
return _apply(_crank8.meansubstraction, _crank16.meansubstraction, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.meansubstraction, _crank16.meansubstraction, image, selem, out=out, mask=mask,
shift_x=shift_x, shift_y=shift_y)
def median(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
@@ -715,7 +721,8 @@ def morph_contr_enh(image, selem, out=None, mask=None, shift_x=False, shift_y=Fa
"""
return _apply(_crank8.morph_contr_enh, _crank16.morph_contr_enh, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.morph_contr_enh, _crank16.morph_contr_enh, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y)
def pop(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
@@ -840,7 +847,8 @@ def threshold(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
"""
return _apply(_crank8.threshold, _crank16.threshold, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)
return _apply(_crank8.threshold, _crank16.threshold, image, selem, out=out, mask=mask, shift_x=shift_x,
shift_y=shift_y)
def tophat(image, selem, out=None, mask=None, shift_x=False, shift_y=False):