• This project aims at building an easy to use graphical interface that can streamline the configuration of the parameters controlling individual processing sub-routines and thus make it easy to design complicated data flow and execute them for EEG signal processing and classification.

• Workflows are designed using individual component blocks that have completely configurable inputs, outputs and properties. The Blocks can be combined and rearranged at runtime without making any modification to code.

• Efforts are also targeted to make the tool user friendly and enable easy deployment of workflows on distributed computing frameworks.

• GSoC 2020 EEG and deep learning workflow project is developed and handled by Ronak Doshi under the guidance and mentorship of Lukáš Vařeka

• This project is a continuation of the project developed in Google Summer of Code 2018 by Joey Pinto under the mentorship of the International Neuroinformatics Coordinating Facility, Sweden.

• In-order to contribute please check the documentation. It contains the system docs and contribution guide.

1. Clone the repo

$ git clone https://github.com/ronak66/EEG-Workflow-System.git
$ cd EEG-Workflow-System

2. Install and Create a Virtual Environment (If already installed, skip 1st command)

$ python3 -m pip install --user virtualenv
$ python3 -m venv env
$ source env/bin/activate

3. Install Redis server to run the workflow in the background

$ sudo apt-get install redis-server

4. Install all the required dependencies

$ pip3 install Flask-Script
$ pip3 install -r requirements.txt

5. Setup Database

$ python3 manage.py db upgrade

6. Run the system

• Run server on one terminal

$ python3 server.py

• Run redis worker on another terminal (inside EEG-Workflow-System directory and enviroment)

$ celery worker -A app.celery --loglevel=info

1. Install Docker: Installation Guide
2. Install Docker-Compose: Installation Guide
3. Clone the repo

$ git clone https://github.com/ronak66/EEG-Workflow-System.git  
$ cd EEG-Workflow-System

4. Build and run the docker image

$ sudo docker-compose up --build

This file is part of the EEG and Deep learning Workflow project

==========================================

Copyright (C) 2020 by University of West Bohemia (http:https://www.zcu.cz/en/)

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

   http:https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.