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authorRémi Flamary <remi.flamary@gmail.com>2017-08-30 17:02:59 +0200
committerRémi Flamary <remi.flamary@gmail.com>2017-08-30 17:02:59 +0200
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+
+
+.. _sphx_glr_auto_examples_plot_otda_color_images.py:
+
+
+========================================================
+OT for domain adaptation with image color adaptation [6]
+========================================================
+
+This example presents a way of transferring colors between two image
+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 and 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, :]
+
+
+
+
+
+
+
+
+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_emd.transform(Xs=X1)
+ transp_Xt_sinkhorn = ot_emd.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 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
+
+
+
+
+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 16.043 seconds)
+
+
+
+.. 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>`
+
+.. rst-class:: sphx-glr-signature
+
+ `Generated by Sphinx-Gallery <http://sphinx-gallery.readthedocs.io>`_