Metadata-Version: 2.1
Name: hcai-discover
Version: 1.0.0
Summary: DISCOVER is a lightweight server designed to create and manage machine learning jobs based on requests.
Author-email: Dominik Schiller <dominik.schiller@uni-a.de>, Tobias Hallmen <tobias.hallmen@uni-a.de>, Tobias Baur <tobias.baur@uni-a.de>, Fabio Hellmann <fabio.hellmann@uni-a.de>
Project-URL: Documentation, https://hcmlab.github.io/nova-server/docbuild/
Project-URL: Repository, https://github.com/hcmlab/discover
Keywords: DISCOVER,NOVA,machine learning
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: flask==3.0.0
Requires-Dist: hcai-discover-utils
Requires-Dist: waitress
Requires-Dist: python-dotenv
Requires-Dist: psutil
Requires-Dist: numpy<2.0,>=1.24

# DISCOVER - A Modular Software Framework for Human Behavior Analysis


## Overview

DISCOVER is an open-source software framework designed to facilitate computational-driven data exploration in human behavior analysis. This user-friendly and modular platform streamlines complex methodologies, enabling researchers across disciplines to engage in detailed behavioral analysis without extensive technical expertise.

Key Features

* Modularity: DISCOVER's modular architecture allows for easy integration of new features and customization.
* User-Friendliness: Intuitive interface simplifies the data exploration process, making it accessible to non-technical users.
* Flexibility: Supports a wide range of data types and analysis workflows.
* Scalability: Handles large datasets with ease.

Use Cases

* Interactive Semantic Content Exploration
* Visual Inspection
* Aided Annotation
* Multimodal Scene Search

## Getting Started

DISCOVER provides a set of blueprints for exploratory data analysis, serving as a starting point for researchers to engage in detailed behavioral analysis.

### Prerequesites

Before starting to install NOVA-Server you need to install Python and FFMPEG. While other Python versions may work as well the module is only tested for the following versions:

3.9.x
You can download the current version of python for your system here.

Download the current version off FFMPEG binaries from here for your system and make sure to extract them to a place that is in your system path. It is recommended to setup a separate virtual environment to isolate the NOVA server installation from your system python installation. To do so, open a terminal at the directory where your virtual environment should be installed and paste the following command:

python -m venv nova-server-venv

You can then activate the virtual environment like this:

.\nova-server-venv\Scripts\activate

Setup

Install NOVA-Server using pip like this:

pip install hcai-nova-server

Start the server

To start DISCOVER you just open a Terminal and type

```discover```

DISCOVER takes the following optional arguments as input:

```
--env: '' : Path to a dotenv file containing your server configuration

--host: 0.0.0.0 : The IP for the Server to listen

--port : 8080 : The port for the Server to be bound to

--cml_dir : cml : The cooperative machine learning directory for Nova

--data_dir : data : Directory where the Nova data resides

--cache_dir : cache : Cache directory for Models and other downloadable content

--tmp_dir : tmp : Directory to store data for temporary usage

--log_dir : log : Directory to store logfiles.
```

Internally DISCOVER converts the input to environment variables with the following names: 

```DISCOVER_SERVER_HOST```, ```DISCOVER_PORT```, ```DISCOVER_CML_DIR```, ```DISCOVER_CML_DIR```, ```DISCOVER_CML_DIR```, ```DISCOVER_CML_DIR```, ```DISCOVER_CML_DIR```

All variables can be either passed directly as commandline argument, set in a dotenv file or as system wide environment variables. During runtime the arguments will be prioritized in this order commandline arguments -> dotenv file -> environment variable -> default value.

If the server started successfully your console output should look like this:

Starting nova-backend server...
HOST: 0.0.0.0
PORT: 8080
DISCOVER_CML_DIR : cml
DISCOVER_DATA_DIR : data
DISCOVER_CACHE_DIR : cache
DISCOVER_TMP_DIR : tmp
DISCOVER_LOG_DIR : log
...done

You can find the full documentation of the project [here](https://hcmlab.github.io/nova-server/docbuild/html).

## Citation
If you use DISCOVER consider citing the following paper: 

```
@article{schiller2024discover,
title={DISCOVER: A Data-driven Interactive System for Comprehensive Observation, Visualization, and ExploRation of Human Behaviour},
author={Schiller, Dominik and Hallmen, Tobias and Withanage Don, Daksitha and Andr{\'e}, Elisabeth and Baur, Tobias},
journal={arXiv e-prints},
pages={arXiv--2407},
year={2024}
}
```
