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diff --git a/docs/source/auto_examples/plot_otda_color_images.rst b/docs/source/auto_examples/plot_otda_color_images.rst deleted file mode 100644 index ab0406e..0000000 --- a/docs/source/auto_examples/plot_otda_color_images.rst +++ /dev/null @@ -1,262 +0,0 @@ - - -.. _sphx_glr_auto_examples_plot_otda_color_images.py: - - -============================= -OT for image color adaptation -============================= - -This example presents a way of transferring colors between two images -with Optimal Transport as introduced in [6] - -[6] Ferradans, S., Papadakis, N., Peyre, G., & Aujol, J. F. (2014). -Regularized discrete optimal transport. -SIAM Journal on Imaging Sciences, 7(3), 1853-1882. - - - -.. code-block:: python - - - # Authors: Remi Flamary <remi.flamary@unice.fr> - # Stanislas Chambon <stan.chambon@gmail.com> - # - # License: MIT License - - import numpy as np - from scipy import ndimage - import matplotlib.pylab as pl - import ot - - - r = np.random.RandomState(42) - - - def im2mat(I): - """Converts an image to matrix (one pixel per line)""" - return I.reshape((I.shape[0] * I.shape[1], I.shape[2])) - - - def mat2im(X, shape): - """Converts back a matrix to an image""" - return X.reshape(shape) - - - def minmax(I): - return np.clip(I, 0, 1) - - - - - - - - -Generate data -------------- - - - -.. code-block:: python - - - # Loading images - I1 = ndimage.imread('../data/ocean_day.jpg').astype(np.float64) / 256 - I2 = ndimage.imread('../data/ocean_sunset.jpg').astype(np.float64) / 256 - - X1 = im2mat(I1) - X2 = im2mat(I2) - - # training samples - nb = 1000 - idx1 = r.randint(X1.shape[0], size=(nb,)) - idx2 = r.randint(X2.shape[0], size=(nb,)) - - Xs = X1[idx1, :] - Xt = X2[idx2, :] - - - - - - - - -Plot original image -------------------- - - - -.. code-block:: python - - - pl.figure(1, figsize=(6.4, 3)) - - pl.subplot(1, 2, 1) - pl.imshow(I1) - pl.axis('off') - pl.title('Image 1') - - pl.subplot(1, 2, 2) - pl.imshow(I2) - pl.axis('off') - pl.title('Image 2') - - - - - -.. image:: /auto_examples/images/sphx_glr_plot_otda_color_images_001.png - :align: center - - - - -Scatter plot of colors ----------------------- - - - -.. code-block:: python - - - pl.figure(2, figsize=(6.4, 3)) - - pl.subplot(1, 2, 1) - pl.scatter(Xs[:, 0], Xs[:, 2], c=Xs) - pl.axis([0, 1, 0, 1]) - pl.xlabel('Red') - pl.ylabel('Blue') - pl.title('Image 1') - - pl.subplot(1, 2, 2) - pl.scatter(Xt[:, 0], Xt[:, 2], c=Xt) - pl.axis([0, 1, 0, 1]) - pl.xlabel('Red') - pl.ylabel('Blue') - pl.title('Image 2') - pl.tight_layout() - - - - - -.. image:: /auto_examples/images/sphx_glr_plot_otda_color_images_003.png - :align: center - - - - -Instantiate the different transport algorithms and fit them ------------------------------------------------------------ - - - -.. code-block:: python - - - # EMDTransport - ot_emd = ot.da.EMDTransport() - ot_emd.fit(Xs=Xs, Xt=Xt) - - # SinkhornTransport - ot_sinkhorn = ot.da.SinkhornTransport(reg_e=1e-1) - ot_sinkhorn.fit(Xs=Xs, Xt=Xt) - - # prediction between images (using out of sample prediction as in [6]) - transp_Xs_emd = ot_emd.transform(Xs=X1) - transp_Xt_emd = ot_emd.inverse_transform(Xt=X2) - - transp_Xs_sinkhorn = ot_sinkhorn.transform(Xs=X1) - transp_Xt_sinkhorn = ot_sinkhorn.inverse_transform(Xt=X2) - - I1t = minmax(mat2im(transp_Xs_emd, I1.shape)) - I2t = minmax(mat2im(transp_Xt_emd, I2.shape)) - - I1te = minmax(mat2im(transp_Xs_sinkhorn, I1.shape)) - I2te = minmax(mat2im(transp_Xt_sinkhorn, I2.shape)) - - - - - - - - -Plot new images ---------------- - - - -.. code-block:: python - - - pl.figure(3, figsize=(8, 4)) - - pl.subplot(2, 3, 1) - pl.imshow(I1) - pl.axis('off') - pl.title('Image 1') - - pl.subplot(2, 3, 2) - pl.imshow(I1t) - pl.axis('off') - pl.title('Image 1 Adapt') - - pl.subplot(2, 3, 3) - pl.imshow(I1te) - pl.axis('off') - pl.title('Image 1 Adapt (reg)') - - pl.subplot(2, 3, 4) - pl.imshow(I2) - pl.axis('off') - pl.title('Image 2') - - pl.subplot(2, 3, 5) - pl.imshow(I2t) - pl.axis('off') - pl.title('Image 2 Adapt') - - pl.subplot(2, 3, 6) - pl.imshow(I2te) - pl.axis('off') - pl.title('Image 2 Adapt (reg)') - pl.tight_layout() - - pl.show() - - - -.. image:: /auto_examples/images/sphx_glr_plot_otda_color_images_005.png - :align: center - - - - -**Total running time of the script:** ( 3 minutes 55.541 seconds) - - - -.. only :: html - - .. container:: sphx-glr-footer - - - .. container:: sphx-glr-download - - :download:`Download Python source code: plot_otda_color_images.py <plot_otda_color_images.py>` - - - - .. container:: sphx-glr-download - - :download:`Download Jupyter notebook: plot_otda_color_images.ipynb <plot_otda_color_images.ipynb>` - - -.. only:: html - - .. rst-class:: sphx-glr-signature - - `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_ |