colour.plotting.image_plot

colour.plotting.image_plot(image, label=None, label_size=15, label_colour=None, label_alpha=0.85, interpolation='nearest', colour_map=<matplotlib.colors.LinearSegmentedColormap object>, **kwargs)[source]

Plots given image.

Parameters:
  • image (array_like) – Image to plot.
  • label (unicode, optional) – Image label.
  • label_size (int, optional) – Image label font size.
  • label_colour (array_like or unicode, optional) – Image label colour.
  • label_alpha (numeric, optional) – Image label alpha.
  • interpolation (unicode, optional) – {‘nearest’, None, ‘none’, ‘bilinear’, ‘bicubic’, ‘spline16’, ‘spline36’, ‘hanning’, ‘hamming’, ‘hermite’, ‘kaiser’, ‘quadric’, ‘catrom’, ‘gaussian’, ‘bessel’, ‘mitchell’, ‘sinc’, ‘lanczos’} Image display interpolation.
  • colour_map (unicode, optional) – Colour map used to display single channel images.
Other Parameters:
 

**kwargs (dict, optional) – {colour.plotting.render()}, Please refer to the documentation of the previously listed definition.
Returns:

Current figure or None.
Return type:

Figure

Examples

>>> import os
>>> from colour import read_image
>>> path = os.path.join('resources',
...                     ('CIE_1931_Chromaticity_Diagram'
...                      '_CIE_1931_2_Degree_Standard_Observer.png'))
>>> image = read_image(path)  
>>> image_plot(image)