Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/skimage/morphology/binary.py

@@ -0,0 +1,146 @@
+"""
+Binary morphological operations
+"""
+import numpy as np
+from scipy import ndimage as ndi
+from .misc import default_selem
+
+
+# The default_selem decorator provides a diamond structuring element as default
+# with the same dimension as the input image and size 3 along each axis.
+@default_selem
+def binary_erosion(image, selem=None, out=None):
+    """Return fast binary morphological erosion of an image.
+
+    This function returns the same result as greyscale erosion but performs
+    faster for binary images.
+
+    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.
+
+    Parameters
+    ----------
+    image : ndarray
+        Binary input image.
+    selem : ndarray, optional
+        The neighborhood expressed as a 2-D array of 1's and 0's.
+        If None, use a cross-shaped structuring element (connectivity=1).
+    out : ndarray of bool, optional
+        The array to store the result of the morphology. If None is
+        passed, a new array will be allocated.
+
+    Returns
+    -------
+    eroded : ndarray of bool or uint
+        The result of the morphological erosion taking values in
+        ``[False, True]``.
+
+    """
+    if out is None:
+        out = np.empty(image.shape, dtype=np.bool)
+    ndi.binary_erosion(image, structure=selem, output=out, border_value=True)
+    return out
+
+
+@default_selem
+def binary_dilation(image, selem=None, out=None):
+    """Return fast binary morphological dilation of an image.
+
+    This function returns the same result as greyscale dilation but performs
+    faster for binary images.
+
+    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.
+
+    Parameters
+    ----------
+
+    image : ndarray
+        Binary input image.
+    selem : ndarray, optional
+        The neighborhood expressed as a 2-D array of 1's and 0's.
+        If None, use a cross-shaped structuring element (connectivity=1).
+    out : ndarray of bool, optional
+        The array to store the result of the morphology. If None is
+        passed, a new array will be allocated.
+
+    Returns
+    -------
+    dilated : ndarray of bool or uint
+        The result of the morphological dilation with values in
+        ``[False, True]``.
+    """
+    if out is None:
+        out = np.empty(image.shape, dtype=np.bool)
+    ndi.binary_dilation(image, structure=selem, output=out)
+    return out
+
+
+@default_selem
+def binary_opening(image, selem=None, out=None):
+    """Return fast binary morphological opening of an image.
+
+    This function returns the same result as greyscale opening but performs
+    faster for binary images.
+
+    The morphological opening on an image is defined as an erosion followed by
+    a dilation. Opening can remove small bright spots (i.e. "salt") and connect
+    small dark cracks. This tends to "open" up (dark) gaps between (bright)
+    features.
+
+    Parameters
+    ----------
+    image : ndarray
+        Binary input image.
+    selem : ndarray, optional
+        The neighborhood expressed as a 2-D array of 1's and 0's.
+        If None, use a cross-shaped structuring element (connectivity=1).
+    out : ndarray of bool, optional
+        The array to store the result of the morphology. If None
+        is passed, a new array will be allocated.
+
+    Returns
+    -------
+    opening : ndarray of bool
+        The result of the morphological opening.
+
+    """
+    eroded = binary_erosion(image, selem)
+    out = binary_dilation(eroded, selem, out=out)
+    return out
+
+
+@default_selem
+def binary_closing(image, selem=None, out=None):
+    """Return fast binary morphological closing of an image.
+
+    This function returns the same result as greyscale closing but performs
+    faster for binary images.
+
+    The morphological closing on an image is defined as a dilation followed by
+    an erosion. Closing can remove small dark spots (i.e. "pepper") and connect
+    small bright cracks. This tends to "close" up (dark) gaps between (bright)
+    features.
+
+    Parameters
+    ----------
+    image : ndarray
+        Binary input image.
+    selem : ndarray, optional
+        The neighborhood expressed as a 2-D array of 1's and 0's.
+        If None, use a cross-shaped structuring element (connectivity=1).
+    out : ndarray of bool, optional
+        The array to store the result of the morphology. If None,
+        is passed, a new array will be allocated.
+
+    Returns
+    -------
+    closing : ndarray of bool
+        The result of the morphological closing.
+
+    """
+    dilated = binary_dilation(image, selem)
+    out = binary_erosion(dilated, selem, out=out)
+    return out