semvec/pypi-packages huggingface dataset:
keebsound 0.0.2
Keeb generates realistic keyboard sounds depending on the input
License: MIT
Keywords: KEYBOARD,SOUND,MECHANICAL KEYBOARD

# Keebsound

Keebsound is a package that I built to generate realistic keyboard tap sounds. You can provide a string and it will "type" those characters out, providing ASMR goodness. 
It also supports hooking into the keyboard and replacing your keytap sound with whichever key switch profile you desire. 

## Getting Started

TODO

### Prerequisites

What things you need to install the software and how to install them

```
Give examples
```

### Installing

TODO

## Usage

```bash
Options:
  --hook           This hooks into your keyboard and plays a sound when you
                   type

  --switches TEXT  Provide the sound profile, by default it's set to gateron-
                   red

  --delay FLOAT    Sound delay multiplier for playing keyboard sound from a
                   string

  --string TEXT    Pass some arbitrary string to play a keyboard typing sound
                   typing said string

  --help           Show this message and exit.
```

### Playing the sound of a string

`python main.py --string "Foo bar is not enough. What are you up to?" --delay 3`

### Hooking to the keyboard

`python main.py --hook`

You can now start typing and it will generate sounds for you. 

### Using explicit key switch sounds

`python main.py --string "Foo bar is not enough. What are you up to?" --switches gateron-red`

## Contributing

TODO

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details

## Acknowledgments

* Hat tip to anyone whose code was used
* Inspiration
* etc
pysaber 1.0.0
Python package that implements a systems approach to blur estimation and reduction (SABER)
License: MIT

# PySABER

## Documentation
Documentation for PySABER is available at the link [https://pysaber.readthedocs.io/](https://pysaber.readthedocs.io/). 

## Introduction
PySABER is a python package for characterizing the X-ray source and detector blurs in cone-beam X-ray imaging systems. SABER is an abbreviation for systems approach to blur estimation and reduction. Once the parameters of both source and detector blurs are estimated, this package is also useful to reduce blur in radiographs using deblurring algorithms. 


## References
K. Aditya Mohan, Robert M. Panas, and Jefferson A. Cuadra. "SABER: A Systems Approach to Blur Estimation and Reduction in X-ray Imaging." arXiv preprint arXiv:1905.03935 (2019) [pdf](https://arxiv.org/pdf/1905.03935.pdf)


## License
This project is licensed under the MIT License. LLNL-CODE-766837.


## Installation and Usage
Please refer to the documentation at the link [https://pysaber.readthedocs.io/](https://pysaber.readthedocs.io/).


## Contributors
* [K. Aditya Mohan](https://orcid.org/0000-0002-0921-6559)
* Robert M. Panas
* Jefferson A. Cuadra


## Changelog
* May 2020: Added documentation and released version 1.0.0 with changes to improve ease of use. 
* May 2020: Moved repository from [https://github.com/sabersw/pysaber](https://github.com/sabersw/pysaber) to [https://github.com/LLNL/pysaber](https://github.com/LLNL/pysaber).