Metadata-Version: 2.1
Name: minerva-ui
Version: 0.20
Summary: An out-of-the-box GUI tool for data-driven deep reinforcement learning
Home-page: https://github.com/takuseno/minerva
Author: Takuma Seno
Author-email: takuma.seno@gmail.com
License: MIT License
Description: <div align="center"><img src="assets/logo.jpg" width="800"/></div>
        
        # MINERVA: An out-of-the-box GUI tool for data-driven deep reinforcement learning
        [![PyPI version](https://badge.fury.io/py/minerva-ui.svg)](https://badge.fury.io/py/minerva-ui)
        ![test](https://github.com/takuseno/minerva/workflows/test/badge.svg)
        ![format check](https://github.com/takuseno/minerva/workflows/format%20check/badge.svg)
        [![Docker Cloud Build Status](https://img.shields.io/docker/cloud/build/takuseno/minerva)](https://hub.docker.com/r/takuseno/minerva)
        [![Documentation Status](https://readthedocs.org/projects/minerva-ui/badge/?version=latest)](https://minerva-ui.readthedocs.io/en/latest/?badge=latest)
        [![Maintainability](https://api.codeclimate.com/v1/badges/0573d1557dcc6a4321f5/maintainability)](https://codeclimate.com/github/takuseno/minerva/maintainability)
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        ![MIT](https://img.shields.io/badge/license-MIT-blue)
        [![Gitter](https://img.shields.io/gitter/room/d3rlpy/minerva)](https://gitter.im/d3rlpy/minerva)
        
        MINERVA is an Out-of-the-box GUI Tool for Data-Driven Deep Reinforcement
        Learning, designed for everyone including non-programmers to do reinforcement
        learning as a tool.
        
        <div align="center"><img src="assets/screenshot1.jpg" width="800"/></div>
        
        Documentation: https://minerva-ui.readthedocs.io
        
        ## key features
        ### :zap: All You Need Is Dataset
        MINERVA only requires datasets to start data-driven deep reinforcement learning.
        Any combinations of vector observations and image observations with discrete
        actions and continuous actions are supported.
        
        ### :beginner: Stunning GUI
        MINERVA provides designed with intuitive GUI to let everyone lerverage extremely
        powerful algorithms without barriers. The GUI is developed as a Single Page
        Application (SPA) to make it work in the eye-opening speed.
        
        ### :rocket: Powerful Algorithm
        MINERVA is powered by [d3rlpy](https://github.com/takuseno/d3rlpy), a powerful
        data-driven deep reinforcement learning library for Python, to provide
        extremely powerful algorithms in an out-of-the-box way. The trained policy can
        be exported as [TorchScript](https://pytorch.org/docs/stable/jit.html) and
        [ONNX](https://onnx.ai/).
        
        ## installation
        ### PyPI
        ```
        $ pip install minerva-ui
        ```
        
        ### Docker
        ```
        $ docker run -d --gpus all -p 9000:9000 --name minerva takuseno/minerva:latest
        ```
        
        ## update guide
        
        If you update MINERVA, the database schema should be also updated as follows:
        ```
        $ pip install -U minerva-ui
        $ minerva upgrade-db
        ```
        
        ## usage
        ### run server
        At the first time, `~/.minerva` will be automatically created to store
        database, uploaded datasets and training metrics.
        ```
        $ minerva run
        ```
        By default, you can access to MINERVA interface at http://localhost:9000 .
        You can change the host and port with `--host` and `--port` arguments
        respectively.
        
        ### delete data
        You can delete entire data (`~/.minerva`) as follows:
        ```
        $ minerva clean
        ```
        
        ## contributions
        ### build
        ```
        $ npm install
        $ npm run build
        ```
        
        ### coding style
        This repository is fully formatted with [yapf](https://github.com/google/yapf)
        and [standard](https://github.com/standard/standard).
        You can format the entire scripts as follows:
        ```
        $ ./scripts/format
        ```
        
        ### lint
        This repository is fully analyzed with [Pylint](https://github.com/PyCQA/pylint),
        [ESLint](https://github.com/eslint/eslint) and [sass-lint](https://github.com/sasstools/sass-lint).
        You can run analysis as follows:
        ```
        $ ./scripts/lint
        ```
        
        ### test
        The unit tests are provided as much as possible.
        This repository is using `pytest-cov` instead of `pytest`.
        You can run the entire tests as follows:
        ```
        $ ./scripts/test
        ```
        
        ## acknowledgement
        This work is supported by Information-technology Promotion Agency, Japan
        (IPA), Exploratory IT Human Resources Project (MITOU Program) in the fiscal
        year 2020.
        
        The concept of the GUI software for deep reinforcement learning is inspired by
        [DeepAnalyzer](https://ghelia.com/en/product/) from Ghelia inc.
        I'm showing the great respect to the team here.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Requires-Python: >=3.5.0
Description-Content-Type: text/markdown
