Updated README; added installation instructions

README.md

-# Deep Learning
-This repository hosts code to build deep convolutional neural networks in [PyTorch](https://pytorch.org/).
-The code is designed for semantic image segmentation of multispectral satellite imagery. However, most of the
-code can also be used for image classification and object detection.
+# PySegCNN: Image segmentation with convolutional neural networks in Python
+This repository hosts a Python package called ``pysegcnn``. The package is
+primarily designed to build deep fully convolutional neural networks for
+semantic image segmentation of multispectral satellite imagery. ``pysegcnn``
+is based on the machine learning framework [PyTorch](https://pytorch.org/).
+
+## Requirements
+``pysegcnn`` requires **Python 3.7** or greater.
+
+## Installation
+You can download ``pysegcnn`` from [this repository's website](https://gitlab.inf.unibz.it/REMSEN/ccisnow/deep-learning/)
+or alternatively use ``git`` from terminal:
+
+```bash
+git clone https://gitlab.inf.unibz.it/REMSEN/ccisnow/deep-learning/
+```
+This creates a copy of the repository in your current directory on the file
+system.
+
+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:
+
+```bash
+conda config --add channels conda-forge
+```
+To finally 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** (``/pysegcnn``) and type:
+
+```bash
+conda env create -f environment.yml
+```
+This may take a while. The first line in ``environment.yml`` defines the
+environment name, in this case ``pysegcnn``. Activate your environment using:
+
+```bash
+conda activate pysegcnn
+```
+After activating your environment, type:
+
+```bash
+pip install -e .
+```
+This will install ``pysegcnn`` - if successful, you should be able to import
+``pysegcnn`` from any Python interpreter using
+
+```python
+import pysegcnn
+```
 
 ## Datasets
-Currently, the following publicly available satellite imagery datasets are supported out-of-the-box:
+Currently, the following publicly available satellite imagery datasets are
+supported out-of-the-box:
 
-- Spatial Procedures for Automated Removal of Cloud and Shadow ([SPARCS](https://www.usgs.gov/land-resources/nli/landsat/spatial-procedures-automated-removal-cloud-and-shadow-sparcs-validation)) by Hughes M.J. & Hayes D.J. ([2014](https://www.mdpi.com/2072-4292/6/6/4907))
-- [Cloud-38](https://github.com/SorourMo/38-Cloud-A-Cloud-Segmentation-Dataset) and [Cloud-95](https://github.com/SorourMo/95-Cloud-An-Extension-to-38-Cloud-Dataset) by Mohajerani S. & Saeedi P. ([2019](https://arxiv.org/abs/1901.10077), [2020](https://arxiv.org/abs/2001.08768))
+- Spatial Procedures for Automated Removal of Cloud and Shadow([SPARCS](https://www.usgs.gov/land-resources/nli/landsat/spatial-procedures-automated-removal-cloud-and-shadow-sparcs-validation)) by Hughes M.J. & Hayes D.J. ([2014](https://www.mdpi.com/2072-4292/6/6/4907))
+- [Cloud-38](https://github.com/SorourMo/38-Cloud-A-Cloud-Segmentation-Dataset)
+and [Cloud-95](https://github.com/SorourMo/95-Cloud-An-Extension-to-38-Cloud-Dataset)
+by Mohajerani S. & Saeedi P. ([2019](https://arxiv.org/abs/1901.10077), [2020](https://arxiv.org/abs/2001.08768))
 
 ## Contributors & Contact
 - [Daniel Frisinghelli](http://www.eurac.edu/en/research/mountains/remsen/staff/Pages/staffdetails.aspx?persId=37603)
 
-For further information or ideas for future development please contact: daniel.frisinghelli@eurac.edu
+For further information or ideas for future development please contact:
+daniel.frisinghelli@eurac.edu
 
 ## License
-If not explicitly stated otherwise, this repository is licensed under the **GNU GENERAL PUBLIC LICENSE v3.0**
-(see [LICENSE](https://gitlab.inf.unibz.it/REMSEN/ccisnow/deep-learning/-/blob/master/LICENSE)).<br>
-<br>![](http://www.eurac.edu/Style%20Library/logoEURAC.jpg)<br><br>
\ No newline at end of file
+If not explicitly stated otherwise, this repository is licensed under the
+**GNU GENERAL PUBLIC LICENSE v3.0**
+(see [LICENSE](https://gitlab.inf.unibz.it/REMSEN/ccisnow/deep-learning/-/blob/master/LICENSE)).
+
+## Acknowledgements
+I wrote a part of the code base for the ``pysegcnn`` package while I was working
+at the [Institute for Earth Observation](http://www.eurac.edu/en/research/mountains/remsen/Pages/default.aspx) of
+[Eurac Research](http://www.eurac.edu/en/Pages/default.aspx), Bolzano.