mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-28 11:25:42 +08:00
Fixed PEP8 and added numpy documentation.
This commit is contained in:
Pieter Holtzhausen
+111
-45
@@ -1,4 +1,4 @@
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'''edges.py - Sobel edge filter
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"""edges.py - Sobel edge filter
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Originally part of CellProfiler, code licensed under both GPL and BSD licenses.
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Website: http://www.cellprofiler.org
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@@ -7,124 +7,190 @@ Copyright (c) 2009-2011 Broad Institute
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All rights reserved.
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Original author: Lee Kamentsky
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'''
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"""
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import numpy as np
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from scipy.ndimage import convolve, binary_erosion, generate_binary_structure
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def sobel(image, mask=None):
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'''Calculate the absolute magnitude Sobel to find the edges
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image - image to process
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mask - mask of relevant points
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"""Calculate the absolute magnitude Sobel to find the edges.
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Parameters
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----------
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image : array_like, dtype=float
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Image to process
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mask : array_like, dtype=bool, optional
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An optional mask to limit the application to a certain area
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Returns
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-------
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output : ndarray
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The Sobel edge map.
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Notes
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-----
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Take the square root of the sum of the squares of the horizontal and
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vertical Sobels to get a magnitude that's somewhat insensitive to
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direction.
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Note that scipy's Sobel returns a directional Sobel which isn't
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useful for edge detection in its raw form.
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'''
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"""
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return np.sqrt(hsobel(image,mask)**2 + vsobel(image,mask)**2)
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def hsobel(image, mask=None):
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'''Find the horizontal edges of an image using the Sobel transform
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"""Find the horizontal edges of an image using the Sobel transform
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image - image to process
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mask - mask of relevant points
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Parameters
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----------
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image : array_like, dtype=float
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Image to process
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mask : array_like, dtype=bool, optional
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An optional mask to limit the application to a certain area.
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Returns
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-------
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output : ndarray
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The Sobel edge map.
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Notes
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-----
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We use the following kernel and return the absolute value of the
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result at each point:
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1 2 1
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0 0 0
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-1 -2 -1
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'''
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if mask == None:
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"""
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if mask is None:
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mask = np.ones(image.shape, bool)
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big_mask = binary_erosion(mask,
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generate_binary_structure(2,2),
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generate_binary_structure(2, 2),
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border_value = 0)
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result = np.abs(convolve(image, np.array([[ 1, 2, 1],
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[ 0, 0, 0],
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[-1,-2,-1]]).astype(float)/4.0))
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result[big_mask==False] = 0
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[-1,-2,-1]]).astype(float) / 4.0))
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result[big_mask == False] = 0
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return result
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def vsobel(image, mask=None):
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'''Find the vertical edges of an image using the Sobel transform
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"""Find the vertical edges of an image using the Sobel transform.
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image - image to process
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mask - mask of relevant points
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Parameters
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----------
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image : array_like, dtype=float
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Image to process
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mask : array_like, dtype=bool, optional
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An optional mask to limit the application to a certain area
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Returns
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-------
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output : ndarray
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The Sobel edge map.
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Notes
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-----
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We use the following kernel and return the absolute value of the
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result at each point:
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1 0 -1
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2 0 -2
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1 0 -1
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'''
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if mask == None:
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"""
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if mask is None:
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mask = np.ones(image.shape, bool)
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big_mask = binary_erosion(mask,
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generate_binary_structure(2,2),
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generate_binary_structure(2, 2),
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border_value = 0)
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result = np.abs(convolve(image, np.array([[ 1, 0,-1],
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[ 2, 0,-2],
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[ 1, 0,-1]]).astype(float)/4.0))
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result[big_mask==False] = 0
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[ 1, 0,-1]]).astype(float) / 4.0))
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result[big_mask == False] = 0
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return result
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def prewitt(image, mask=None):
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'''Find the edge magnitude using the Prewitt transform
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"""Find the edge magnitude using the Prewitt transform.
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image - image to process
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mask - mask of relevant points
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Parameters
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----------
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image : array_like, dtype=float
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Image to process
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mask : array_like, dtype=bool, optional
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An optional mask to limit the application to a certain area
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Returns
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-------
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output : ndarray
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The Prewitt edge map.
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Notes
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-----
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Return the square root of the sum of squares of the horizontal
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and vertical Prewitt transforms.
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'''
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return np.sqrt(hprewitt(image,mask)**2 + vprewitt(image,mask)**2)
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"""
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return np.sqrt(hprewitt(image, mask) ** 2 + vprewitt(image, mask) ** 2)
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def hprewitt(image, mask=None):
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'''Find the horizontal edges of an image using the Prewitt transform
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"""Find the horizontal edges of an image using the Prewitt transform.
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image - image to process
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mask - mask of relevant points
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Parameters
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----------
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image : array_like, dtype=float
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Image to process
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mask : array_like, dtype=bool, optional
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An optional mask to limit the application to a certain area
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Returns
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-------
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output : ndarray
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The Prewitt edge map.
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Notes
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-----
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We use the following kernel and return the absolute value of the
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result at each point:
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1 1 1
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0 0 0
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-1 -1 -1
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'''
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if mask == None:
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"""
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if mask is None:
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mask = np.ones(image.shape, bool)
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big_mask = binary_erosion(mask,
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generate_binary_structure(2,2),
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generate_binary_structure(2, 2),
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border_value = 0)
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result = np.abs(convolve(image, np.array([[ 1, 1, 1],
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[ 0, 0, 0],
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[-1,-1,-1]]).astype(float)/3.0))
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result[big_mask==False] = 0
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[-1,-1,-1]]).astype(float) / 3.0))
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result[big_mask == False] = 0
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return result
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def vprewitt(image, mask=None):
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'''Find the vertical edges of an image using the Prewitt transform
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"""Find the vertical edges of an image using the Prewitt transform.
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image - image to process
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mask - mask of relevant points
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Parameters
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----------
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image : array_like, dtype=float
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Image to process
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mask : array_like, dtype=bool, optional
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An optional mask to limit the application to a certain area
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Returns
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-------
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output : ndarray
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The Prewitt edge map.
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Notes
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-----
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We use the following kernel and return the absolute value of the
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result at each point:
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1 0 -1
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1 0 -1
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1 0 -1
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'''
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if mask == None:
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"""
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if mask is None:
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mask = np.ones(image.shape, bool)
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big_mask = binary_erosion(mask,
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generate_binary_structure(2,2),
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border_value = 0)
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generate_binary_structure(2, 2),
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border_value=0)
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result = np.abs(convolve(image, np.array([[ 1, 0,-1],
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[ 1, 0,-1],
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[ 1, 0,-1]]).astype(float)/3.0))
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result[big_mask==False] = 0
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[ 1, 0,-1]]).astype(float) / 3.0))
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result[big_mask == False] = 0
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return result
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@@ -5,193 +5,193 @@ import scikits.image.filter as F
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class TestSobel():
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def test_00_00_zeros(self):
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'''Sobel on an array of all zeros'''
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result = F.sobel(np.zeros((10,10)), np.ones((10,10),bool))
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assert (np.all(result==0))
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"""Sobel on an array of all zeros"""
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result = F.sobel(np.zeros((10, 10)), np.ones((10, 10), bool))
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assert (np.all(result == 0))
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def test_00_01_mask(self):
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'''Sobel on a masked array should be zero'''
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"""Sobel on a masked array should be zero"""
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np.random.seed(0)
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result = F.sobel(np.random.uniform(size=(10,10)),
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np.zeros((10,10),bool))
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result = F.sobel(np.random.uniform(size=(10, 10)),
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np.zeros((10, 10), bool))
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assert (np.all(result == 0))
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def test_01_01_horizontal(self):
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'''Sobel on an edge should be a horizontal line'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (i>=0).astype(float)
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"""Sobel on an edge should be a horizontal line"""
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i, j = np.mgrid[-5:6, -5:6]
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image = (i >= 0).astype(float)
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result = F.sobel(image)
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# Fudge the eroded points
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i[np.abs(j)==5] = 10000
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assert (np.all(result[i==0] == 1))
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i[np.abs(j) == 5] = 10000
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assert (np.all(result[i == 0] == 1))
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assert (np.all(result[np.abs(i) > 1] == 0))
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def test_01_02_vertical(self):
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'''Sobel on a vertical edge should be a vertical line'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (j>=0).astype(float)
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"""Sobel on a vertical edge should be a vertical line"""
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i,j = np.mgrid[-5:6, -5:6]
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image = (j >= 0).astype(float)
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result = F.sobel(image)
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j[np.abs(i)==5] = 10000
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assert (np.all(result[j==0] == 1))
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j[np.abs(i) == 5] = 10000
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assert (np.all(result[j == 0] == 1))
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assert (np.all(result[np.abs(j) > 1] == 0))
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class TestHSobel():
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def test_00_00_zeros(self):
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'''Horizontal sobel on an array of all zeros'''
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result = F.hsobel(np.zeros((10,10)), np.ones((10,10),bool))
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assert (np.all(result==0))
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"""Horizontal sobel on an array of all zeros"""
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result = F.hsobel(np.zeros((10, 10)), np.ones((10, 10), bool))
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assert (np.all(result == 0))
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def test_00_01_mask(self):
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'''Horizontal Sobel on a masked array should be zero'''
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"""Horizontal Sobel on a masked array should be zero"""
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np.random.seed(0)
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result = F.hsobel(np.random.uniform(size=(10,10)),
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np.zeros((10,10),bool))
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result = F.hsobel(np.random.uniform(size=(10, 10)),
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np.zeros((10, 10), bool))
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assert (np.all(result == 0))
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def test_01_01_horizontal(self):
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'''Horizontal Sobel on an edge should be a horizontal line'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (i>=0).astype(float)
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"""Horizontal Sobel on an edge should be a horizontal line"""
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i,j = np.mgrid[-5:6, -5:6]
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image = (i >= 0).astype(float)
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result = F.hsobel(image)
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# Fudge the eroded points
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i[np.abs(j)==5] = 10000
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assert (np.all(result[i==0] == 1))
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i[np.abs(j) == 5] = 10000
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assert (np.all(result[i == 0] == 1))
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assert (np.all(result[np.abs(i) > 1] == 0))
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def test_01_02_vertical(self):
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'''Horizontal Sobel on a vertical edge should be zero'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (j>=0).astype(float)
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"""Horizontal Sobel on a vertical edge should be zero"""
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i,j = np.mgrid[-5:6, -5:6]
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image = (j >= 0).astype(float)
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result = F.hsobel(image)
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assert (np.all(result == 0))
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class TestVSobel():
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def test_00_00_zeros(self):
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'''Vertical sobel on an array of all zeros'''
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result = F.vsobel(np.zeros((10,10)), np.ones((10,10),bool))
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assert (np.all(result==0))
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"""Vertical sobel on an array of all zeros"""
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result = F.vsobel(np.zeros((10, 10)), np.ones((10, 10), bool))
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assert (np.all(result == 0))
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def test_00_01_mask(self):
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'''Vertical Sobel on a masked array should be zero'''
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"""Vertical Sobel on a masked array should be zero"""
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np.random.seed(0)
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result = F.vsobel(np.random.uniform(size=(10,10)),
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np.zeros((10,10),bool))
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result = F.vsobel(np.random.uniform(size=(10, 10)),
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np.zeros((10, 10), bool))
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assert (np.all(result == 0))
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def test_01_01_vertical(self):
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'''Vertical Sobel on an edge should be a vertical line'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (j>=0).astype(float)
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"""Vertical Sobel on an edge should be a vertical line"""
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i,j = np.mgrid[-5:6, -5:6]
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image = (j >= 0).astype(float)
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result = F.vsobel(image)
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# Fudge the eroded points
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j[np.abs(i)==5] = 10000
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assert (np.all(result[j==0] == 1))
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j[np.abs(i) == 5] = 10000
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assert (np.all(result[j == 0] == 1))
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assert (np.all(result[np.abs(j) > 1] == 0))
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def test_01_02_horizontal(self):
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'''vertical Sobel on a horizontal edge should be zero'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (i>=0).astype(float)
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"""vertical Sobel on a horizontal edge should be zero"""
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i,j = np.mgrid[-5:6, -5:6]
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image = (i >= 0).astype(float)
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result = F.vsobel(image)
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eps = .000001
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assert (np.all(np.abs(result) < eps))
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class TestPrewitt():
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def test_00_00_zeros(self):
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'''Prewitt on an array of all zeros'''
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result = F.prewitt(np.zeros((10,10)), np.ones((10,10),bool))
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assert (np.all(result==0))
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"""Prewitt on an array of all zeros"""
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result = F.prewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
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assert (np.all(result == 0))
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def test_00_01_mask(self):
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'''Prewitt on a masked array should be zero'''
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"""Prewitt on a masked array should be zero"""
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np.random.seed(0)
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result = F.prewitt(np.random.uniform(size=(10,10)),
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np.zeros((10,10),bool))
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result = F.prewitt(np.random.uniform(size=(10, 10)),
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np.zeros((10, 10), bool))
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eps = .000001
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assert (np.all(np.abs(result) < eps))
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def test_01_01_horizontal(self):
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'''Prewitt on an edge should be a horizontal line'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (i>=0).astype(float)
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"""Prewitt on an edge should be a horizontal line"""
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i,j = np.mgrid[-5:6, -5:6]
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image = (i >= 0).astype(float)
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result = F.prewitt(image)
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# Fudge the eroded points
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i[np.abs(j)==5] = 10000
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i[np.abs(j) == 5] = 10000
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eps = .000001
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assert (np.all(result[i==0] == 1))
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assert (np.all(result[i == 0] == 1))
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assert (np.all(np.abs(result[np.abs(i) > 1]) < eps))
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def test_01_02_vertical(self):
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'''Prewitt on a vertical edge should be a vertical line'''
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i,j = np.mgrid[-5:6,-5:6]
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image = (j>=0).astype(float)
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"""Prewitt on a vertical edge should be a vertical line"""
|
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i,j = np.mgrid[-5:6, -5:6]
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image = (j >= 0).astype(float)
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result = F.prewitt(image)
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eps = .000001
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j[np.abs(i)==5] = 10000
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assert (np.all(result[j==0] == 1))
|
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assert (np.all(result[j == 0] == 1))
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assert (np.all(np.abs(result[np.abs(j) > 1]) < eps))
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|
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class TestHPrewitt():
|
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def test_00_00_zeros(self):
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'''Horizontal sobel on an array of all zeros'''
|
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result = F.hprewitt(np.zeros((10,10)), np.ones((10,10),bool))
|
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assert (np.all(result==0))
|
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"""Horizontal sobel on an array of all zeros"""
|
||||
result = F.hprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
|
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assert (np.all(result == 0))
|
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|
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def test_00_01_mask(self):
|
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'''Horizontal prewitt on a masked array should be zero'''
|
||||
"""Horizontal prewitt on a masked array should be zero"""
|
||||
np.random.seed(0)
|
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result = F.hprewitt(np.random.uniform(size=(10,10)),
|
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np.zeros((10,10),bool))
|
||||
result = F.hprewitt(np.random.uniform(size=(10, 10)),
|
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np.zeros((10, 10), bool))
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eps = .000001
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assert (np.all(np.abs(result) < eps))
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|
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def test_01_01_horizontal(self):
|
||||
'''Horizontal prewitt on an edge should be a horizontal line'''
|
||||
i,j = np.mgrid[-5:6,-5:6]
|
||||
image = (i>=0).astype(float)
|
||||
"""Horizontal prewitt on an edge should be a horizontal line"""
|
||||
i,j = np.mgrid[-5:6, -5:6]
|
||||
image = (i >= 0).astype(float)
|
||||
result = F.hprewitt(image)
|
||||
# Fudge the eroded points
|
||||
i[np.abs(j)==5] = 10000
|
||||
i[np.abs(j) == 5] = 10000
|
||||
eps = .000001
|
||||
assert (np.all(result[i==0] == 1))
|
||||
assert (np.all(result[i == 0] == 1))
|
||||
assert (np.all(np.abs(result[np.abs(i) > 1]) < eps))
|
||||
|
||||
def test_01_02_vertical(self):
|
||||
'''Horizontal prewitt on a vertical edge should be zero'''
|
||||
i,j = np.mgrid[-5:6,-5:6]
|
||||
image = (j>=0).astype(float)
|
||||
"""Horizontal prewitt on a vertical edge should be zero"""
|
||||
i,j = np.mgrid[-5:6, -5:6]
|
||||
image = (j >= 0).astype(float)
|
||||
result = F.hprewitt(image)
|
||||
eps = .000001
|
||||
assert (np.all(np.abs(result) < eps))
|
||||
|
||||
class TestVPrewitt():
|
||||
def test_00_00_zeros(self):
|
||||
'''Vertical prewitt on an array of all zeros'''
|
||||
result = F.vprewitt(np.zeros((10,10)), np.ones((10,10),bool))
|
||||
assert (np.all(result==0))
|
||||
"""Vertical prewitt on an array of all zeros"""
|
||||
result = F.vprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
|
||||
assert (np.all(result == 0))
|
||||
|
||||
def test_00_01_mask(self):
|
||||
'''Vertical prewitt on a masked array should be zero'''
|
||||
"""Vertical prewitt on a masked array should be zero"""
|
||||
np.random.seed(0)
|
||||
result = F.vprewitt(np.random.uniform(size=(10,10)),
|
||||
np.zeros((10,10),bool))
|
||||
result = F.vprewitt(np.random.uniform(size=(10, 10)),
|
||||
np.zeros((10, 10), bool))
|
||||
assert (np.all(result == 0))
|
||||
|
||||
def test_01_01_vertical(self):
|
||||
'''Vertical prewitt on an edge should be a vertical line'''
|
||||
i,j = np.mgrid[-5:6,-5:6]
|
||||
image = (j>=0).astype(float)
|
||||
"""Vertical prewitt on an edge should be a vertical line"""
|
||||
i,j = np.mgrid[-5:6, -5:6]
|
||||
image = (j >= 0).astype(float)
|
||||
result = F.vprewitt(image)
|
||||
# Fudge the eroded points
|
||||
j[np.abs(i)==5] = 10000
|
||||
assert (np.all(result[j==0] == 1))
|
||||
j[np.abs(i) == 5] = 10000
|
||||
assert (np.all(result[j == 0] == 1))
|
||||
eps = .000001
|
||||
assert (np.all(np.abs(result[np.abs(j) > 1]) < eps))
|
||||
|
||||
def test_01_02_horizontal(self):
|
||||
'''vertical prewitt on a horizontal edge should be zero'''
|
||||
i,j = np.mgrid[-5:6,-5:6]
|
||||
image = (i>=0).astype(float)
|
||||
"""Vertical prewitt on a horizontal edge should be zero"""
|
||||
i,j = np.mgrid[-5:6, -5:6]
|
||||
image = (i >= 0).astype(float)
|
||||
result = F.vprewitt(image)
|
||||
eps = .000001
|
||||
assert (np.all(np.abs(result) < eps))
|
||||
|
||||
@@ -1,2 +1 @@
|
||||
# THIS FILE IS GENERATED FROM THE SCIKITS.IMAGE SETUP.PY
|
||||
version='0.3dev'
|
||||
version='unbuilt-dev'
|
||||
|
||||
Reference in New Issue
Block a user