seaborn_image.fftplot(data, *, window_type=None, shift=True, log=True, ax=None, cmap='viridis', showticks=False, despine=None, **kwargs)#

Perform and visualize fast fourier transform of input image.

  • data (array-like) – Image data. Supported array shapes are all matplotlib.pyplot.imshow array shapes

  • window_type (string, float or tuple, optional) – The type of window to be created. Any window type supported by scipy.signal.get_window is allowed here. See the scikit-image documentation or the SciPy documentation for the supported window types, by default None

  • shift (bool, optional) – If True, this will shift the DC component to the center, by default True

  • log (bool, optional) – If true, takes the magnitude spectrum of the frequency transform, by default True

  • ax (matplotlib.axes.Axes, optional) – Matplotlib axes to plot image on. If None, figure and axes are auto-generated, by default None

  • cmap (str or matplotlib.colors.Colormap, optional) – Colormap for image, by default “viridis”

  • showticks (bool, optional) – Show image x-y axis ticks, by default False

  • despine (bool, optional) – Remove axes spines from image axes, by default None

  • **kwargs (optional) – Any additional parameters to be passed to skimage.filters.window. For more information see


Matplotlib axes where the image is drawn

Return type:



ValueError – If input image is RGB image


Perform fast-fourier transform and visualize it

>>> import seaborn_image as isns
>>> img = isns.load_image("polymer")
>>> isns.fftplot(img)

Specify a window type

>>> isns.fftplot(img, window_type="hann")
>>> isns.fftplot(img, window_type=('tukey', 0.8))

Don’t shift the DC comppnent to the center

>>> isns.fftplot(img, shift=False)