====================
Aydin CLI Tutorials
====================

We have few CLI tutorials below to demonstrate how to use various features
of the CLI Aydin provides.

Checking if Aydin CLI can read and interpret your image right
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to get information about how Aydin will be
interpreting their image file.

.. code-block:: bash

   $ aydin info image.tif

   ├╗ Reading image file at: /PATH/TO/IMAGE/image.tif
   │├ Reading file /PATH/TO/IMAGE/image.tif as TIF file
   │├ Metadata:  is_folder=False, ext=tif, axes=YX, shape=(321, 481), batch_axes=(False, False), channel_axes=(False, False), dtype=uint8, format=tif
   │┴« 4.24 milliseconds
   │



Viewing your image with Aydin CLI
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to view their image with help of integrated
napari in Aydin CLI.

.. code-block:: bash

   $ aydin view image.tif


.. image:: ../resources/cli_tutorials/aydin_view_ss.png

**Note:** `aydin view` command would work as expected only on the machines with
screen access.

Denoising a single image
~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to denoise a single image with default
options.

.. code-block:: bash

   $ aydin noise2self image.tif


Denoising a single image with customized options
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have made it possible for users to play with various parameters and options
related to the denoising approach they have chosen and save their specific set
of parameters into a JSON file. We also made it possible to pass such JSON file
to Aydin CLI. One can achieve this as shown below:


.. code-block:: bash

   $ aydin noise2self image.tif --lower-level-args=image_options.json



Denoising a single image with a pre-trained Aydin model
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to denoise a single image with a pre-trained
Aydin model. You can use the Aydin Studio GUI to play with different parameters
and train a model to pass here to the Aydin CLI.

.. code-block:: bash

   $ aydin noise2self image.tif --model-path=image_model.zip --use-model



Denoising multiple image files
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to denoise multiple image files with default
options:

.. code-block:: bash

   $ aydin denoise image1.tif image2.tif image3.tif

Or alternatively one can use glob patterns such as:

.. code-block:: bash

   $ aydin denoise image*.tif


Deconvolving a single image
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to deconvolve a single image with default
options.

.. code-block:: bash

   $ aydin lucyrichardson image.tif


Using your PSF to deconvolve your image
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to deconvolve a single image with default
options and their own psf. Passed psf file assumed to be a single psf image
in a lossless format.

.. code-block:: bash

   $ aydin lucyrichardson image.tiff psf.tif



Choosing the computational backend
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can use the following line to denoise or deconvolve a single image
with their choice of computational backend.

.. code-block:: bash

   $ aydin denoise image.tif --backend="noise2selffgr-nn"
   $ aydin lucyrichardson image.tif --backend="cupy"