fastplotlib · kushalkolar · Jun 18, 2024 · Jun 18, 2024 · Jun 18, 2024 · Jun 18, 2024
@@ -0,0 +1,90 @@
+"""
+Explore fourier transform of images
+===================================
+Example showing how to use a `RectangleSelector` to interactively reconstruct
+an image using portions of it fourier transform
+"""
+
+# test_example = false
+# sphinx_gallery_pygfx_docs = 'screenshot'
+
+import numpy as np
+import fastplotlib as fpl
+import scipy
+import imageio.v3 as iio
+
+image = iio.imread("imageio:camera.png")
+
+# compute discrete fourier transform of image
+dft = scipy.fftpack.fft2(image)
+
+# image to just visualize absolute magnitudes
+log_abs_dft = np.log(np.abs(dft))
+
+# placeholders for displaying fft and inverse fft of selections
+zeros = np.zeros(image.shape)
+
+# create an ImageWidget to display all the images
+iw = fpl.ImageWidget(
+    data=[image, log_abs_dft, zeros, zeros, zeros, zeros],
+    names=["image", "DFT", "selected", "IDFT of selected", "not-selected", "IDFT of not-selected"],
+    figure_shape=(3, 2),  # so we can see image and fft side by side
+    figure_kwargs={"size": (700, 400)},
+    histogram_widget=False,
+)
+
+# set contrast limits based on the full DFT for the DFT-selection images
+iw.figure["selected"].graphics[0].vmin, iw.figure["selected"].graphics[0].vmax = log_abs_dft.min(), log_abs_dft.max()
+iw.figure["not-selected"].graphics[0].vmin, iw.figure["not-selected"].graphics[0].vmax = log_abs_dft.min(), log_abs_dft.max()
+
+iw.show()
+
+# create a rectangle selector
+rs = iw.managed_graphics[1].add_rectangle_selector()
+
+
+@rs.add_event_handler("selection")
+def update_images(ev):
+    """
+    Updates the images when the selection changes
+    """
+
+    # get the bbox of the selection
+    row_ixs, col_ixs = ev.get_selected_indices()
+    row_slice = slice(row_ixs[0], row_ixs[-1] + 1)
+    col_slice = slice(col_ixs[0], col_ixs[-1] + 1)
+
+    # fft of the selection
+    selected_fft = np.zeros(image.shape, dtype=np.complex64)
+    selected_fft[row_slice, col_slice] = dft[row_slice, col_slice]
+
+    # update image graphic with the current fft selection
+    iw.managed_graphics[2].data = np.log(np.abs(selected_fft))
+
+    # inverse fft to reconstruct image using only the selection
+    iw.managed_graphics[3].data = scipy.fftpack.ifft2(selected_fft)
+    iw.managed_graphics[3].reset_vmin_vmax()
+
+    # fft of the region outside the selection
+    unselected_fft = dft.copy()
+    unselected_fft[row_slice, col_slice] = 0
+
+    # update image graphic with unselected fft area
+    iw.managed_graphics[4].data = np.log(np.abs(unselected_fft))
+
+    # inverse fft to reconstruct image using only the unselected part of the fft
+    iw.managed_graphics[5].data = scipy.fftpack.ifft2(unselected_fft)
+    iw.managed_graphics[5].reset_vmin_vmax()
+
+
+# set initial selection to top right corner
+rs.selection = (400, 512, 0, 100)
+
+
+figure = iw.figure
+
+# NOTE: `if __name__ == "__main__"` is NOT how to use fastplotlib interactively
+# please see our docs for using fastplotlib interactively in ipython and jupyter
+if __name__ == "__main__":
+    print(__doc__)
+    fpl.run()