semvec/pypi-packages huggingface dataset:
skeraton 0.1.0
Keras implementation of skeleton transformer module
License: MIT
Keywords: Skeleton-Transformer Python Keras Action-Recognition Skeleton Pose-Estimation

# Skeleton Transformer in Keras

Keras implementation of "skeleton transformer module", which is mentioned in [Skeleton-based Action Recognition with Convolutional Neural Networks](https://arxiv.org/abs/1704.07595).

## Install

You can install this module from [PyPI](https://pypi.org/project/skeraton) as `skeraton`.

```sh
pip install skeraton
```

## How to use

### Module

#### skeraton.SkeletonTransformer

##### Parameters:

All parameters are required.

**timesteps:** Timesteps of input time-series data (equal to number of frames, mentioned as 'T' in the paper)  
**kpts_dim:** Dimentions of keypoints (usually 2 (x, y) or 3 (x, y, z))
**output_dim:** Dimentions of output (mentioned as 'M' in the paper)

##### Input:

**x:** 3-dimentional tensor of shape (batchsize, timesteps, kpts_dim*N) where N is number of joints

## Pytorch implementation

We also have Pytorch implementation of this module:  
[https://github.com/Yutsuro/skeleton-transformer-Pytorch](https://github.com/Yutsuro/skeleton-transformer-Pytorch)
galaxywitness 0.2.4
Package for topological data analysis of the big data. It is attempt to study distribution of galaxies in the universe via TDA
License: MIT
Requires Python: >=3.8

# GalaxyWitness
[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg?style=flat)](http://choosealicense.com/licenses/mit/)
[![CodeFactor](https://www.codefactor.io/repository/github/davidosx/galaxywitness/badge/master)](https://www.codefactor.io/repository/github/davidosx/galaxywitness/overview/master)
[![Documentation Status](https://readthedocs.org/projects/galaxywitness/badge/?version=latest)](https://galaxywitness.readthedocs.io/en/latest/?badge=latest)
[![PyPI version](https://badge.fury.io/py/galaxywitness.svg)](https://badge.fury.io/py/galaxywitness)


Package for topological data analysis of the big data. It is attempt to study distribution of galaxies in the universe via TDA. Based on [GUDHI](https://gudhi.inria.fr) and [Astropy](https://www.astropy.org)

## Requirements
1. Python 3.8+ and pip
2. git (for development)

OS X or Linux

## Installation
For the best experience, use python virtual environment:
```sh
pip3 install virtualenv
virtualenv env (or python3 -m virtualenv galaxy-witness)
. ./env/bin/activate
```
Install this package from PyPI via ```pip install galaxywitness```

## Documentation
You can find our technical documentation here: [Docs](https://galaxywitness.rtfd.io)
### For developers
[Sphinx](https://www.sphinx-doc.org/en/master/index.html) generates documentation for delelopers from sources in <code>./docs</code> folder. HTML files of documentation are in <code>./docs/build/html</code> and you can open it with browser. 
If you want to build documentation yourself:
```sh
cd docs
make html
```
or if you want to get .pdf with documentation:
```sh
cd docs
make latexpdf
```

## Usage
To run just type:
```sh   
python -m galaxywitness
```

In runtime the program will request you to choose file with your data. This file have to be in folder ```./data```

If you want to finish a work with package and deactivate virtual environment just type:
```sh
deactivate
```

## Development
You can use python virtual environment and install dependencies manually:
### Create and activate a virtual environment
This will create a new virtual environment called "galaxy-witness":
```sh
pip3 install virtualenv
virtualenv galaxy-witness (or python3 -m virtualenv galaxy-witness)
. ./galaxy-witness/bin/activate
``` 
This will clone the repository "GalaxyWitness" on your local machine, install dependencies and install this package 'galaxywitness':
```sh
git clone https://github.com/davidosx/GalaxyWitness
cd GalaxyWitness
pip install -r requirements.txt
python setup.py install
```

Or poetry package manager:
### Poetry
```sh
git clone https://github.com/davidosx/GalaxyWitness
cd GalaxyWitness
poetry install
```

### Uninstalling
For uninstalling (include dependencies and an virtual environment):
```sh
rm -r GalaxyWitness
rm -r galaxy-witness
```
skeletorch 0.1.1
Pytorch implementation of skeleton transformer module
License: MIT
Keywords: Skeleton-Transformer Python Pytorch Action-Recognition Skeleton Pose-Estimation

# Skeleton Transformer Module in Pytorch

Pytorch implementation of "skeleton transformer module", which is mentioned in [Skeleton-based Action Recognition with Convolutional Neural Networks](https://arxiv.org/abs/1704.07595).

## Install

You can install this module from [PyPI](https://pypi.org/project/skeletorch/0.1.0/).

```sh
pip install skeletorch
```

## How to use

### Module

#### skeletorch.SkeletonTransformer

##### Parameters:

All parameters are required.

**timesteps:** Timesteps of input time-series data (equal to number of frames, mentioned as 'T' in the paper)  
**kpts_dim:** Dimentions of keypoints (usually 2 (x, y) or 3 (x, y, z))  
**input_kpts_num:** Number of joints in original keypoints (mentioned as 'N' in the paper)  
**output_dim:** Dimentions of output (mentioned as 'M' in the paper)

##### Input:

**x:** 2-dimentional tensor of shape (timesteps, input_kpts_num*kpts_dim)

## Example        

```python
import torch
from skeletorch import SkeletonTransformer

# parameters
timesteps = 20
kpts_dim = 3
input_kpts_num = 17
output_dim = 10

# input (the size is (20, 51) in this example)
x = torch.Tensor(torch.randn(timesteps, kpts_dim*input_kpts_num))

# make layer
layer = SkeletonTransformer(timesteps, kpts_dim, input_kpts_num, output_dim)

layer(x)
```

Of course you can use this module in your Pytorch network.

## Keras implementation

We also have Keras implementation of this module:  
[https://github.com/Yutsuro/skeleton-transformer-Keras](https://github.com/Yutsuro/skeleton-transformer-Keras)