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# -*- coding: utf-8 -*-
#cython: embedsignature=True, language_level=3
#cython: boundscheck=False, wraparound=False, cdivision=True, initializedcheck=False,
## This is for developping:
##cython: profile=True, warn.undeclared=True, warn.unused=True, warn.unused_result=False, warn.unused_arg=True
#
# Project: Fast Azimuthal integration
# https://github.com/silx-kit/pyFAI
#
# Copyright (C) 2014-2020 European Synchrotron Radiation Facility, Grenoble, France
#
# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# .
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
# .
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
"""
This module provides a couple of binary morphology operations on images.
They are also implemented in ``scipy.ndimage`` in the general case, but not as
fast.
"""
__author__ = "Jerome Kieffer"
__contact__ = "Jerome.kieffer@esrf.fr"
__date__ = "30/04/2020"
__status__ = "stable"
__license__ = "MIT"
import cython
import numpy
cimport numpy
def binary_dilation(numpy.int8_t[:, ::1] image,
float radius=1.0):
"""
Return fast binary morphological dilation of an image.
Morphological dilation sets a pixel at (i,j) to the maximum over all pixels in the neighborhood centered at (i,j).
Dilation enlarges bright regions and shrinks dark regions.
:param image : ndarray
:param radius: float
:return: ndiamge
"""
cdef:
int x, y, i, j, size_x, size_y, px, py,
int r_int = int(radius), r2_int = int(radius * radius)
size_y = image.shape[0]
size_x = image.shape[1]
cdef:
numpy.int8_t val, curr
numpy.int8_t[:, ::1] result = numpy.empty(dtype=numpy.int8, shape=(size_y, size_x))
for y in range(size_y):
for x in range(size_x):
val = image[y, x]
for j in range(-r_int, r_int + 1):
py = y + j
if py < 0 or py >= size_y:
continue
for i in range(-r_int, r_int + 1):
px = x + i
if (px < 0) or (px >= size_x):
continue
if i * i + j * j <= r2_int:
curr = image[py, px]
val = max(val, curr)
result[y, x] = val
return numpy.asarray(result)
def binary_erosion(numpy.int8_t[:, ::1] image,
float radius=1.0):
"""Return fast binary morphological erosion of an image.
Morphological erosion sets a pixel at (i,j) to the minimum over all pixels
in the neighborhood centered at (i,j).
Erosion shrinks bright regions and enlarges dark regions.
:param image : ndarray
:param radius: float
:return: ndiamge
"""
cdef:
int x, y, i, j, size_x, size_y, px, py,
int r_int = int(radius), r2_int = int(radius * radius)
size_y = image.shape[0]
size_x = image.shape[1]
cdef:
numpy.int8_t val, curr
numpy.int8_t[:, ::1] result = numpy.empty(dtype=numpy.int8, shape=(size_y, size_x))
for y in range(size_y):
for x in range(size_x):
val = image[y, x]
for j in range(-r_int, r_int + 1):
py = y + j
if (py < 0) or (py >= size_y):
continue
for i in range(-r_int, r_int + 1):
px = x + i
if (px < 0) or (px >= size_x):
continue
if i * i + j * j <= r2_int:
curr = image[py, px]
val = min(val, curr)
result[y, x] = val
return numpy.asarray(result)
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