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README.md

+[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](http://www.gnu.org/licenses/gpl-3.0)
+[![Build Status](https://gitlab.lis-lab.fr/baptiste.bauvin/summit/badges/develop/pipeline.svg)](https://gitlab.lis-lab.fr/baptiste.bauvin/summit/badges/develop/pipeline.svg)
+# Supervised MultiModal Integration Tool's Readme
+
+This project aims to be an easy-to-use solution to run a prior benchmark on a dataset and evaluate mono- & multi-view algorithms capacity to classify it correctly.
+
+## Getting Started
+
+### Prerequisites (will be automatically installed)
+
+To be able to use this project, you'll need :
+
+* [Python 3.6](https://docs.python.org/3/) 
+
+And the following python modules :
+
+* [numpy](http://www.numpy.org/), [scipy](https://scipy.org/),
+* [matplotlib](http://matplotlib.org/) - Used to plot results,
+* [sklearn](http://scikit-learn.org/stable/) - Used for the monoview classifiers,
+* [joblib](https://pypi.python.org/pypi/joblib) - Used to compute on multiple threads,
+* [h5py](https://www.h5py.org) - Used to generate HDF5 datasets on hard drive and use them to spare RAM,
+* [pickle](https://docs.python.org/3/library/pickle.html) - Used to store some results,
+* [pandas](https://pandas.pydata.org/) - Used to manipulate data efficiently,
+* [six](https://pypi.org/project/six/) - 
+* [m2r](https://pypi.org/project/m2r/) - Used to generate documentation from the readme,
+* [docutils](https://pypi.org/project/docutils/) - Used to generate documentation,
+* [pyyaml](https://pypi.org/project/PyYAML/) - Used to read the config files,
+* [plotly](https://plot.ly/) - Used to generate interactive HTML visuals,
+* [tabulate](https://pypi.org/project/tabulate/) - Used to generated the confusion matrix.
+
+
+### Installing
+
+Once you cloned the project from the [gitlab repository](https://gitlab.lis-lab.fr/baptiste.bauvin/summit/), you just have to use :  
+
+```
+cd path/to/summit/
+pip install -e .
+```
+In the `summit` directory to install SuMMIT and its dependencies.
+
+### Running on simulated data
+
+In order to run it you'll need to try on **simulated** data with the command
+```python 
+from multiview_platform.execute import execute
+execute("example 1")
+```
+This will run the first example. 
+
+For more information about the examples, see the [documentation](http://baptiste.bauvin.pages.lis-lab.fr/summit/).
+Results will be stored in the results directory of the installation path : 
+`path/to/summit/multiview_platform/examples/results`.
+
+The documentation proposes a detailed interpretation of the results through [6 tutorials](http://baptiste.bauvin.pages.lis-lab.fr/summit/). 
+
+### Discovering the arguments
+
+All the arguments of the platform are stored in a YAML config file. Some config files are given as examples. 
+The file stored in `summit/config_files/config.yml` is documented and it is highly recommended
+to read it carefully before playing around with the parameters.   
+
+You can create your own configuration file. In order to run the platform with it, run : 
+```python
+from multiview_platform.execute import execute
+execute(config_path="/absolute/path/to/your/config/file")
+```
+
+For further information about classifier-specific arguments, see the [documentation](http://baptiste.bauvin.pages.lis-lab.fr/summit/). 
+ 
+
+### Dataset compatibility
+
+
+In order to start a benchmark on your own dataset, you need to format it so SuMMIT can use it. To do so, a [python script](https://gitlab.lis-lab.fr/baptiste.bauvin/summit/-/blob/master/format_dataset.py) is provided.
+
+For more information, see [Example 6](http://baptiste.bauvin.pages.lis-lab.fr/summit/tutorials/example4.html)
+
+### Running on your dataset 
+
+Once you have formatted your dataset, to run SuMMIT on it you need to modify the config file as  
+```yaml
+name: ["your_file_name"]
+*
+pathf: "path/to/your/dataset"
+```
+This will run a full benchmark on your dataset using all available views and labels.
+ 
+It is highly recommended to follow the documentation's [tutorials](http://baptiste.bauvin.pages.lis-lab.fr/summit/tutorials/index.html) to learn the use of each parameter. 
+ 
+
+## Author
+
+* **Baptiste BAUVIN**
+* **Dominique BENIELLI**
+* **Alexis PROD'HOMME**
+