.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_tif_processing_steps.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_tif_processing_steps.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_tif_processing_steps.py:


Tif Processing Steps
====================

This example applies common processing steps to a Zeiss SEM TIF image and
compares the intermediate results.

.. GENERATED FROM PYTHON SOURCE LINES 8-19

.. code-block:: Python


    from pathlib import Path

    import matplotlib.pyplot as plt

    import micromechanics
    from micromechanics.tif import Tif

    repository_root = Path(micromechanics.__file__).resolve().parents[1]
    file_name = repository_root / "examples" / "Zeiss" / "Zeiss.tif"








.. GENERATED FROM PYTHON SOURCE LINES 20-22

Load the Zeiss SEM image and crop to a region of interest. Keeping a copy after
each stage makes it easy to compare the effect of each processing step.

.. GENERATED FROM PYTHON SOURCE LINES 22-27

.. code-block:: Python


    image = Tif(str(file_name))
    image.crop(xMin=50, xMax=450, yMin=50, yMax=350)
    cropped = image.image.copy()





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

       After cropping: new size of image:  400 300




.. GENERATED FROM PYTHON SOURCE LINES 28-30

Apply a median filter to suppress isolated pixel noise, then a Gaussian filter
for mild smoothing. The two filters target different kinds of image noise.

.. GENERATED FROM PYTHON SOURCE LINES 30-35

.. code-block:: Python


    image.medianFilter(level=2)
    image.gaussFilter(level=1)
    filtered = image.image.copy()








.. GENERATED FROM PYTHON SOURCE LINES 36-38

Adjust contrast and add a scale bar. The processed copy is the version that
would typically be used in a figure or report.

.. GENERATED FROM PYTHON SOURCE LINES 38-43

.. code-block:: Python


    image.contrast(magnitude=1.4, offset=0.45, save=True)
    image.addScaleBar(site="BR", length=1)
    processed = image.image.copy()








.. GENERATED FROM PYTHON SOURCE LINES 44-46

Compare the intermediate results side by side. This helps tune the crop,
filtering, and contrast parameters before saving a final image.

.. GENERATED FROM PYTHON SOURCE LINES 46-56

.. code-block:: Python


    fig, axes = plt.subplots(1, 3, figsize=(9, 3))
    for ax, title, data in zip(axes,
                              ["cropped", "filtered", "processed"],
                              [cropped, filtered, processed]):
      ax.imshow(data, cmap="gray")
      ax.set_title(title)
      ax.axis("off")

    plt.tight_layout()



.. image-sg:: /auto_examples/images/sphx_glr_plot_tif_processing_steps_001.png
   :alt: cropped, filtered, processed
   :srcset: /auto_examples/images/sphx_glr_plot_tif_processing_steps_001.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.174 seconds)


.. _sphx_glr_download_auto_examples_plot_tif_processing_steps.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_tif_processing_steps.ipynb <plot_tif_processing_steps.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_tif_processing_steps.py <plot_tif_processing_steps.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_tif_processing_steps.zip <plot_tif_processing_steps.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_