pygorpho.gen

Mathematical morphology with general (grayscale) structuring elements.

pygorpho.gen.morph(vol, strel, op, block_size=[256, 256, 256])[source]

Morphological operation with general structuring element.

Parameters:
  • vol – Volume to apply operation to. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • op – Operation to perform. Must be either DILATE or ERODE from constants.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of the operation.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple dilation with an 11 x 11 x 11 box structuring element
vol = np.zeros((100, 100, 100))
vol[50, 50, 50] = 1
strel = np.ones((11, 11, 11))
res = pg.gen.morph(vol, strel, pg.DILATE)
pygorpho.gen.dilate(vol, strel, block_size=[256, 256, 256])[source]

Dilation with general structuring element.

Parameters:
  • vol – Volume to dilate/erode. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of dilation/erosion.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple dilation with an 11 x 11 x 11 box structuring element
vol = np.zeros((100, 100, 100))
vol[50, 50, 50] = 1
strel = np.ones((11, 11, 11))
res = pg.gen.dilate(vol, strel)
pygorpho.gen.erode(vol, strel, block_size=[256, 256, 256])[source]

Erosion with general structuring element.

Parameters:
  • vol – Volume to dilate/erode. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of dilation/erosion.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple erosion with an 11 x 11 x 11 box structuring element
vol = np.ones((100, 100, 100))
vol[50, 50, 50] = 0
strel = np.ones((11, 11, 11))
res = pg.gen.erode(vol, strel)
pygorpho.gen.open(vol, strel, block_size=[256, 256, 256])[source]

Opening with general structuring element.

Parameters:
  • vol – Volume to open. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of opening.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple opening with an 11 x 11 x 11 box structuring element
vol = np.zeros((100, 100, 100))
vol[10:15,10:15,48:53] = 1  # Small box
vol[60:80,60:80,40:60] = 1  # Big box
strel = np.ones((11, 11, 11))
res = pg.gen.open(vol, strel)
pygorpho.gen.close(vol, strel, block_size=[256, 256, 256])[source]

Closing with general structuring element.

Parameters:
  • vol – Volume to close. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of closing.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple closing with an 11 x 11 x 11 box structuring element
vol = np.ones((100, 100, 100))
vol[10:15,10:15,48:53] = 0  # Small box
vol[60:80,60:80,40:60] = 0  # Big box
strel = np.ones((11, 11, 11))
res = pg.gen.close(vol, strel)
pygorpho.gen.tophat(vol, strel, block_size=[256, 256, 256])[source]

Top-hat transform with general structuring element.

Also known as a white top-hat transform. It is given by tophat(x) = x - open(x).

Parameters:
  • vol – Volume to top-hat transform. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of the top-hat transform.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple top-hat with an 11 x 11 x 11 box structuring element
vol = np.zeros((100, 100, 100))
vol[10:15,10:15,48:53] = 1  # Small box
vol[60:80,60:80,40:60] = 1  # Big box
strel = np.ones((11, 11, 11))
res = pg.gen.tophat(vol, strel)
pygorpho.gen.bothat(vol, strel, block_size=[256, 256, 256])[source]

Bot-hat transform with general structuring element.

Also known as a black top-hat transform. It is given by bothat(x) = close(x) - x.

Parameters:
  • vol – Volume to bot-hat transform. Must be convertible to numpy array of at most 3 dimensions.
  • strel – Structuring element. Must be convertible to numpy array of at most 3 dimensions.
  • block_size – Block size for GPU processing. Volume is sent to the GPU in blocks of this size.
Returns:

Volume of same size as vol with the result of the bot-hat transform.
Return type:

numpy.array

Example

import numpy as np
import pygorpho as pg
# Simple bot-hat with an 11 x 11 x 11 box structuring element
vol = np.ones((100, 100, 100))
vol[10:15,10:15,48:53] = 0  # Small box
vol[60:80,60:80,40:60] = 0  # Big box
strel = np.ones((11, 11, 11))
res = pg.gen.bothat(vol, strel)