:py:mod:`kwimage.im_filter`
===========================

.. py:module:: kwimage.im_filter


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   kwimage.im_filter.radial_fourier_mask
   kwimage.im_filter.fourier_mask



.. py:function:: radial_fourier_mask(img_hwc, radius=11, axis=None, clip=None)

   In [1] they use a radius of 11.0 on CIFAR-10.

   :Parameters: **img_hwc** (*ndarray*) -- assumed to be float 01

   .. rubric:: References

   [1] Jo and Bengio "Measuring the tendency of CNNs to Learn Surface Statistical Regularities" 2017.
   https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_imgproc/py_transforms/py_fourier_transform/py_fourier_transform.html

   .. rubric:: Example

   >>> from kwimage.im_filter import *  # NOQA
   >>> import kwimage
   >>> img_hwc = kwimage.grab_test_image()
   >>> img_hwc = kwimage.ensure_float01(img_hwc)
   >>> out_hwc = radial_fourier_mask(img_hwc, radius=11)
   >>> # xdoc: REQUIRES(--show)
   >>> import kwplot
   >>> plt = kwplot.autoplt()
   >>> def keepdim(func):
   >>>     def _wrap(im):
   >>>         needs_transpose = (im.shape[0] == 3)
   >>>         if needs_transpose:
   >>>             im = im.transpose(1, 2, 0)
   >>>         out = func(im)
   >>>         if needs_transpose:
   >>>             out = out.transpose(2, 0, 1)
   >>>         return out
   >>>     return _wrap
   >>> @keepdim
   >>> def rgb_to_lab(im):
   >>>     return kwimage.convert_colorspace(im, src_space='rgb', dst_space='lab')
   >>> @keepdim
   >>> def lab_to_rgb(im):
   >>>     return kwimage.convert_colorspace(im, src_space='lab', dst_space='rgb')
   >>> @keepdim
   >>> def rgb_to_yuv(im):
   >>>     return kwimage.convert_colorspace(im, src_space='rgb', dst_space='yuv')
   >>> @keepdim
   >>> def yuv_to_rgb(im):
   >>>     return kwimage.convert_colorspace(im, src_space='yuv', dst_space='rgb')
   >>> def show_data(img_hwc):
   >>>     # dpath = ub.ensuredir('./fouriertest')
   >>>     kwplot.imshow(img_hwc, fnum=1)
   >>>     pnum_ = kwplot.PlotNums(nRows=4, nCols=5)
   >>>     for r in range(0, 17):
   >>>         imgt = radial_fourier_mask(img_hwc, r, clip=(0, 1))
   >>>         kwplot.imshow(imgt, pnum=pnum_(), fnum=2)
   >>>         plt.gca().set_title('r = {}'.format(r))
   >>>     kwplot.set_figtitle('RGB')
   >>>     # plt.gcf().savefig(join(dpath, '{}_{:08d}.png'.format('rgb', x)))
   >>>     pnum_ = kwplot.PlotNums(nRows=4, nCols=5)
   >>>     for r in range(0, 17):
   >>>         imgt = lab_to_rgb(radial_fourier_mask(rgb_to_lab(img_hwc), r))
   >>>         kwplot.imshow(imgt, pnum=pnum_(), fnum=3)
   >>>         plt.gca().set_title('r = {}'.format(r))
   >>>     kwplot.set_figtitle('LAB')
   >>>     # plt.gcf().savefig(join(dpath, '{}_{:08d}.png'.format('lab', x)))
   >>>     pnum_ = kwplot.PlotNums(nRows=4, nCols=5)
   >>>     for r in range(0, 17):
   >>>         imgt = yuv_to_rgb(radial_fourier_mask(rgb_to_yuv(img_hwc), r))
   >>>         kwplot.imshow(imgt, pnum=pnum_(), fnum=4)
   >>>         plt.gca().set_title('r = {}'.format(r))
   >>>     kwplot.set_figtitle('YUV')
   >>>     # plt.gcf().savefig(join(dpath, '{}_{:08d}.png'.format('yuv', x)))
   >>> show_data(img_hwc)
   >>> kwplot.show_if_requested()


.. py:function:: fourier_mask(img_hwc, mask, axis=None, clip=None)

   Applies a mask to the fourier spectrum of an image

   :Parameters: * **img_hwc** (*ndarray*) -- assumed to be float 01
                * **mask** (*ndarray*) -- mask used to modulate the image in the fourier domain.
                  Usually these are boolean values (hence the name mask), but any
                  numerical value is technically allowed.

   CommandLine:
       xdoctest -m kwimage.im_filter fourier_mask --show

   .. rubric:: Example

   >>> from kwimage.im_filter import *  # NOQA
   >>> import kwimage
   >>> img_hwc = kwimage.grab_test_image(space='gray')
   >>> mask = np.random.rand(*img_hwc.shape[0:2])
   >>> out_hwc = fourier_mask(img_hwc, mask)
   >>> # xdoc: REQUIRES(--show)
   >>> import kwplot
   >>> kwplot.autompl()
   >>> kwplot.imshow(img_hwc, pnum=(1, 2, 1), fnum=1)
   >>> kwplot.imshow(out_hwc, pnum=(1, 2, 2), fnum=1)
   >>> kwplot.show_if_requested()