semvec/pypi-packages huggingface dataset:
kelluwen 0.0.29
Open AI library for research and education.

# Kelluwen

Open AI library for research and education designed to be easy to use and develop with.

## Installation

```python
pip install kelluwen
```

## Usage

```python
from kelluwen.functions.transforms import generate_affine, apply_affine
from kelluwen.functions.tools import show_midplanes
from torch import rand

# Create image tensor of shape BxCxDxHxW
img = rand(2, 3, 100, 100, 100)

# Define parameters for affine transform. These transforms can be independent for each channel. If there is no channel dimension, the same transform will be applied for all channels.
parameters = dict(
    parameter_translation=rand(2,3),
    parameter_rotation=rand(2,3),
    parameter_scaling=rand(2,3),
    type_rotation="euler_xyz",
    transform_order="trs",
)

# Generate affine transform
transform = generate_affine(**parameters)

# Apply affine transform to image tensor
img_transformed = apply_affine(image=img, **transform)


# Show midplanes of volume. In this example we're using the RAS coordinate system, and we're scaling the features using a min-max method.
show_midplanes(
    image=img_transformed,
    title="Example midplanes",
    show=True,
    type_coordinates="ras",
    type_scaling="min_max")
# ```
VoXera 0.0.1
An Open-Source Persian Language Techs Toolkit with Python
Requires Python: >=3.8

<img src="https://github.com/VoXera/.github/blob/main/images/logo.png" width="35%" height="35%" align="right" />

# VoXera
The VoXera toolkit is an open-source NLP toolkit for the Persian language (text, speech, etc). In Voxera, we collect practical models and develop new ones with easy-to-use setups. VoXera is becoming more and more functional. Until now, we have made the following functionality available:

- [Automatic Speech Recognition](https://github.com/VoXera/VoXera/tree/master/src/VoXera/Automatic_Speech_Recognition)
  - Whisper
  - Vosk
- [Keyword Extraction](https://github.com/VoXera/VoXera/tree/master/src/VoXera/Keyword_Extraction/PerDeepKE)
  - PerDeepKE
- [Paraphrase Generation](https://github.com/VoXera/VoXera/tree/master/src/VoXera/ParaphraseGeneration)
  - Lab/Parrot
  - Lab/Pegasus
- > coming soon!
## Installation
In present, VoXera can be installed and used in two different ways.

## 1. From Github

1- [Fork](https://github.com/VoXera/VoXera/fork) Voxera

2- Clone VoXera from your Github profile

3- Run the below script in your terminal from VoXera directory:
```
pip install -r requirements.txt
```
## 2. From PyPi
>coming soon

## How to Use 

You can find a `test.py` file in each folders that shows how to use VoXera's features. For example, for using Persian vosk, you can run and modify [this](https://github.com/VoXera/VoXera/blob/master/src/VoXera/Automatic_Speech_Recognition/Vosk/test.py).

To see VoXera's hierarchy:
<img src="https://github.com/VoXera/VoXera/blob/master/VoXera.png" align="center" />

Also you can download [xmind version](https://github.com/VoXera/VoXera/blob/master/VoXera.xmind) of the hierarchy.