Metadata-Version: 2.1
Name: shapeandshare-dicebox-core
Version: 2.1.2
Summary: Dicebox Core
Home-page: https://github.com/shapeandshare/dicebox.core
Author: Joshua C. Burt
Author-email: joshburt@shapeandshare.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy (==1.19.0)
Requires-Dist: tensorflow (==2.2.0)
Requires-Dist: pillow (==7.2.0)
Requires-Dist: configparser (==5.0.0)
Requires-Dist: pika (==1.1.0)
Requires-Dist: requests (==2.24.0)
Requires-Dist: typing (==3.7.4.1)

# Dicebox Core Libraries

Core libraries for the dicebox API platform.

Notes
-----
* run_unit_tests.sh created to wrap python unit test runner.

Requirements
------------

**Python Module Requirements**

The requirements can be automatically installed using the below command:
```
    pip install -r requirements.txt
```

References
----------

[Matt Harvey](https://github.com/harvitronix) thank you, for without you dicebox would not be.  Much of the current implementation of dicebox comes from Matt's project below.  I originally forked Matt's work and used it until it outgrew what it was.

* [Blog Post](https://blog.coast.ai/lets-evolve-a-neural-network-with-a-genetic-algorithm-code-included-8809bece164) & [Code](https://github.com/harvitronix/neural-network-genetic-algorithm)

**Projects that I worked with heavily during prior implementations of dicebox**

* [Tensorflow & the 'slim' samples](https://github.com/tensorflow/tensorflow)
* [Tensorflow models](https://github.com/tensorflow/models)
* [EasyTensorflow](https://github.com/calvinschmdt/EasyTensorflow)

**Additional projects used here, or were reference material for dicebox**

* D20 Roll Fairness Evaluation | [Blog Post](http://www.markfickett.com/stuff/artPage.php?id=389) & [Code](https://github.com/markfickett/dicehistogram)
* Keras | [Site](https://keras.io/) & [Code](https://github.com/fchollet/keras)
* [JPG-and-PNG-to-MNIST](https://github.com/gskielian/JPG-PNG-to-MNIST-NN-Format)


Contributing
------------
1. Fork the repository on Github
2. Create a named feature branch (like `add_component_x`)
3. Write your change
4. Write tests for your change (if applicable)
5. Run the tests, ensuring they all pass
6. Submit a Pull Request using Github

License and Authors
-------------------
MIT License

Copyright (c) 2017-2020 Joshua C. Burt

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


