Include directive is not supported in Readme.

README.rst

@@ -7,7 +7,99 @@ networks for semantic image segmentation. The package is primarily designed to
 work with multispectral satellite imagery. ``pysegcnn`` is based on the machine
 learning framework `PyTorch <https://pytorch.org/>`_.
 
-.. include:: ./docs/source/installation.rst
+Installation
+============
+
+Requirements
+------------
+``pysegcnn`` is a pure Python package that works on both Windows and Linux.
+
+.. important::
+
+    ``pysegcnn`` requires ``Python>=3.7``.
+
+Here is a list of all dependencies of ``pysegcnn``.
+
+    - numpy
+    - scipy
+    - matplotlib
+    - pytorch
+    - gdal
+
+Download
+---------
+You can download ``pysegcnn`` from this repository's
+`website <https://gitlab.inf.unibz.it/REMSEN/ccisnow/pysegcnn>`_
+or alternatively use ``git`` from terminal:
+
+.. code-block:: bash
+
+    git clone https://gitlab.inf.unibz.it/REMSEN/ccisnow/pysegcnn.git
+
+This creates a copy of the repository in your current directory on the file
+system.
+
+Conda package manager
+---------------------
+
+To install ``pysegcnn``, I recommend to use the ``conda`` package manager.
+You can download ``conda`` `here <https://docs.conda.io/en/latest/miniconda.html>`_.
+Once successfully installed ``conda``, I recommend to add ``conda-forge`` as
+your default channel:
+
+.. code-block:: bash
+
+    conda config --add channels conda-forge
+
+Conda environment
+-----------------
+
+To install ``pysegcnn``, I recommend to create a specific ``conda``
+`environment <https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`_,
+by using the provided ``environment.yml`` file. In a terminal, navigate to the
+**cloned git repositories root directory** and type:
+
+.. code-block:: bash
+
+    conda env create -f environment.yml
+
+This may take a while. The above command creates a conda environment with all
+required dependencies except the ``pytorch`` package. The first line in
+``environment.yml`` defines the environment name, in this case ``pysegcnn``.
+Activate your environment using:
+
+.. code-block:: bash
+
+    conda activate pysegcnn
+
+Install PyTorch
+---------------
+The installation of ``pytorch`` is heavily dependent on the hardware of your
+machine. Therefore, after activating your environment, install the version of
+`PyTorch <https://pytorch.org/>`_ that your system supports by following the
+official `instructions <https://pytorch.org/get-started/locally/>`_.
+
+If you have to build ``pytorch`` from source, follow this
+`guide <https://github.com/pytorch/pytorch#from-source>`_.
+
+To verify the installation, run some sample PyTorch
+`code <https://pytorch.org/get-started/locally/#linux-verification>`_.
+
+Install PySegCNN
+----------------
+To finally install ``pysegcnn`` run the below command **from this repositories
+root directory within the activated ``pysegcnn`` conda environment**:
+
+.. code-block:: bash
+
+    pip install -e .
+
+If successful, you should be able to import ``pysegcnn`` from any Python
+interpreter using:
+
+.. code-block:: python
+
+    import pysegcnn
 
 Datasets
 ========
@@ -42,7 +134,7 @@ at the `Institute for Earth Observation <http://www.eurac.edu/en/research/mounta
 .. _SPARCS:
     https://www.usgs.gov/land-resources/nli/landsat/spatial-procedures-automated-removal-cloud-and-shadow-sparcs-validation)
 
-.. _Hughes M.J. & Hayes D.J. 2014:
+.. _Hughes M.J. & Hayes D.J. (2014):
     https://www.mdpi.com/2072-4292/6/6/4907
 
 .. _Cloud-38:
@@ -55,4 +147,4 @@ at the `Institute for Earth Observation <http://www.eurac.edu/en/research/mounta
     https://arxiv.org/abs/1901.10077
 
 .. _2020:
-    https://arxiv.org/abs/2001.08768
\ No newline at end of file
+    https://arxiv.org/abs/2001.08768