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seaborn-image: image data visualization
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.. |img1| image:: /auto_examples/images/thumb/sphx_glr_plot_image_hist_thumb.png
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:height: 180px
.. |img2| image:: /auto_examples/images/thumb/sphx_glr_plot_filter_thumb.png
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.. |img3| image:: /auto_examples/images/thumb/sphx_glr_plot_fft_thumb.png
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.. |img4| image:: /auto_examples/images/thumb/sphx_glr_plot_filtergrid_thumb.png
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.. .. |img5| image:: /auto_examples/images/thumb/sphx_glr_plot_image_robust_thumb.png
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Description
===========
Seaborn-image is a Python **image** visualization library based on matplotlib
and provides a high-level API to **draw attractive and informative images quickly**
**and effectively**.
It is heavily inspired by `seaborn `_, a high-level visualization library
for drawing attractive statistical graphics in Python.
To view example images, check out the :doc:`gallery page ` and :doc:`reference `.
For specific how-to questions, refer to the :doc:`tutorial page `.
Check out the source code on `github `_.
If you come across any bugs/issues, please open an `issue `_.
Installation
============
.. code-block:: bash
pip install -U seaborn-image
Quick Usage
===========
Visualize 2-D images
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.. code-block:: python
import seaborn_image as isns
"""Global settings for images"""
isns.set_context("notebook")
isns.set_image(cmap="deep", despine=True)
isns.set_scalebar(color="red")
pol = isns.load_image("polymer")
"""Image with a scalebar"""
ax = isns.imgplot(pol, dx=0.01, units="um")
"""Get basic image stats"""
isns.imgplot(data, describe=True)
Visualize image distribution
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.. code-block:: python
f = isns.imghist(pol)
Multi-dimensional images
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.. code-block:: python
cells = isns.load_image("cells")
g = isns.ImageGrid(cells, slices=[10, 20, 30, 40])
For more information check out examples in :doc:`tutorial `, :doc:`api ` and :doc:`gallery `.
Contents
========
.. toctree::
:maxdepth: 1
Gallery
Reference
Tutorial
License
Authors
GitHub
Changelog
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`