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docs/Installation/InstallationNotes/index.rst

@@ -283,10 +283,90 @@ compiling again in case you need to.
 
 Compiling with Matlab
 ---------
+Xmipp has a binding to MATLAB, which allows the user to run specific
+Xmipp functions inside MATLAB.
 
+Previous requirements
+^^^^^^^^^^^^^^^^^^^^
+
+It is required to have a regular MATLAB installation.
+
+Settings
+^^^^^^^^^^^^^^^^^^^^
+
+Make sure you have these settings in your Xmipp configuration file
+(``xmipp-bundle/xmipp.conf``) before compiling Xmipp:
+
+``MATLAB=True``
+
+``MATLAB_DIR=<path to your MATLAB instalation>`` (usually something
+like: ``MATLAB_DIR=/home/user/MATLAB/R2021b``)
+
+Run
+^^^^^^^^^^^^^^^^^^^^
+
+1. Compile Xmipp normally (once the settings are as above): ``./xmipp``
+   or ``scipion run ./xmipp``
+2. Open MATLAB
+3. In MATLAB, set the path to Xmipp binding:
+   ``HOME > Set Path > Add Folder...`` and select the path to the
+   binding (``<path to xmipp>/xmipp-bundle/build/bindings/matlab``),
+   then, click in ``Open`` and ``Save``
+4. Now you should be able to run functions like ``xmipp_read()`` in
+   MATLAB
 
 DeepLearningToolKit
 ---------------------
+The DeepLearningToolkit (DLTK) is a set of environments populated with
+several libraries related to deep learning and allows running protocols
+on Scipion which require deep learning tools. All of them are available
+for GPU or CPU only (the installator’ll detect your configuraction)
+
+Requirements
+^^^^^^^^^^^^^^^^^^^
+
+A nvidia drivers 450 or higher is required, to review the nvidia driver
+version please run ``nvidia-smi``. If older version is detected, the
+DLTK will be installed without GPU support.
+
+How to install
+^^^^^^^^^^^^^^^^^^^
+
+Run ``scipion3 installb deepLearningToolkit``
+
+It could take more than 30 minutes. To speedup the installation we
+propose to use libmamba solver (we experienced a x4 speedup) . It is
+only available for conda >=4.12 and has to be installed and setup on
+your conda installation. For more details, please visit:
+https://www.anaconda.com/blog/a-faster-conda-for-a-growing-community
+
+List environments
+^^^^^^^^^^^^^^^^^^^
+
+-  xmipp_DLTK_v0.3 > \* Protocols ussing it: screen_deeplearning,
+   deep_denoising, resolution_deepres, screen_deepConsensus > \*
+   python=3.7 > \* scikit-image=0.14 > \* tensorflow=1.15 > \* keras=2.2
+   > \* scikit-learn=0.22 > \* pip > \* numpy==1.21 > \* h5py==2.10.0
+
+-  xmipp_DLTK_v1.0 > \* Protocols ussing it: deep_misalingment_detection
+   > \* python=3.8 > \* tensorflow=2.7 > \* keras=2.7 > \* pip > \*
+   numpy==1.23
+
+-  xmipp_MicCleaner > \* Protocols ussing it: deepMicrographScreen > \*
+   python=3.6 > \* micrograph-cleaner-em=0.35
+
+-  xmipp_deepEMhancer > \* Protocols ussing it: protocol_deepEMhancer >
+   \* python=3.6 > \* deepemhancer=0.12 > \* numba=0.45
+
+-  xmipp_pyTorch > \* Protocols ussing it: deepHand > \* python=3.8 > \*
+   numpy=1.23 > \* mrcfile=1.4.3 > \* kornia=0.6.12 > \* starfile=0.4.12
+   > \* pytorch==1.11 > \* pytorch-cuda=11.7 > \* torchvision=0.12
+
+Troubleshooting
+^^^^^^^^^^^^^^^^^^^
+
+Visit:
+`troubleshooting <https://github.com/I2PC/xmipp/wiki/DeepLearningToolkit-troubleshooting>`__
 
 
 Troubleshooting