# Examples from pyvista.ImageDataFilters.dilate
# =============================================

# Create a toy example with two non-zero grayscale foreground values
# `padded` with a background of zeros.
import pyvista as pv
im = pv.ImageData(dimensions=(2, 1, 1))
im['data'] = [128, 255]
im = im.pad_image(pad_value=0, pad_size=2, dimensionality=2)

# Define a custom plotter to plot pixels as cells.
def image_plotter(image):
    pl = pv.Plotter()
    pl.add_mesh(
        image.points_to_cells(),
        cmap='grey',
        clim=[0, 255],
        show_scalar_bar=False,
        show_edges=True,
        lighting=False,
        line_width=3,
    )
    pl.camera_position = 'xy'
    pl.camera.tight()
    pl.enable_anti_aliasing()
    return pl

# Show the image.
image_plotter(im).show()

# Dilate it with default settings. Observe that both foreground values are dilated.
dilated = im.dilate()
image_plotter(dilated).show()

# Use a larger kernel size.
dilated = im.dilate(kernel_size=5)
image_plotter(dilated).show()

# Use an asymmetric kernel.
dilated = im.dilate(kernel_size=(2, 4, 1))
image_plotter(dilated).show()

# Use binary dilation. By default, the max value (`255` in this example) is dilated
# with the min value (`0` in this example). All other values are unaffected.
dilated = im.dilate(binary=True)
image_plotter(dilated).show()

# Equivalently, set the binary values for the dilation explicitly.
dilated = im.dilate(binary=[0, 255])
image_plotter(dilated).show()

# Use binary dilation with the other foreground value instead.
dilated = im.dilate(binary=[0, 128])
image_plotter(dilated).show()

# ----------------------------------------------------------------------
# Generated by sphinx-examples-as-code https://github.com/pyvista/sphinx-examples-as-code