semvec/pypi-packages huggingface dataset:
Minecraft-Skin-Converter 1.2
Convert minecraft skins from steve to alex and vice versa
License: MIT
Requires Python: >=3
Keywords: minecraft,skin-converter,minecraft_skin_converter,minecraft-skin-converter

# Minecraft Skin Converter

[![Build Status](https://github.com/skillor/minecraft-skin-converter/actions/workflows/test-python.yml/badge.svg)](https://github.com/skillor/minecraft-skin-converter/actions/workflows/test-python.yml) [![PyPi version](https://badgen.net/pypi/v/minecraft-skin-converter/)](https://pypi.org/project/minecraft-skin-converter)

This is a simplified version of https://github.com/811Alex/MCSkinConverter, ported to python.
Big Thanks to the original creator [811Alex](https://github.com/811Alex)

Convert skins from alex to steve and vice versa.

## Installation

```bash
pip install minecraft-skin-converter
```

## Basic Usage
```python
from minecraft_skin_converter import SkinConverter

sc = SkinConverter()
sc.load_from_file('steve.png')
print(sc.is_steve())
sc.steve_to_alex()
sc.save_to_file('steve_as_alex.png')
```
atom3d 0.2.6
ATOM3D: Tasks On Molecules in 3 Dimensions
License: MIT

# ATOM3D: Tasks On Molecules in 3 Dimensions

[![Documentation
Status](https://readthedocs.org/projects/atom3d/badge/?version=latest)](http://atom3d.readthedocs.io/?badge=latest)
![Package](https://github.com/drorlab/atom3d/workflows/package/badge.svg)
[![codecov](https://codecov.io/gh/drorlab/atom3d/branch/master/graph/badge.svg?token=DHH78W45AB)](https://codecov.io/gh/drorlab/atom3d)
[![PyPI version](https://badge.fury.io/py/atom3d.svg)](https://badge.fury.io/py/atom3d)

[ATOM3D](https://www.atom3d.ai/) enables machine learning on three-dimensional molecular structure.

## Features

* Access to several datasets involving 3D molecular structure. 
* LMDB data format for storing lots of molecules (and associated metadata).
* Utilities for splitting/filtering data based on many criteria.

For more detailed information, [read the documentation](https://atom3d.readthedocs.io/en/latest/).

## Installation

Install with:

```
pip install atom3d
```
    
To use rdkit functionality, please install within conda:

```
conda create -n atom3d python=3.6 pip rdkit
conda activate atom3d
pip install atom3d
```

## Usage


### Downloading a dataset

From python:
```
import atom3d.datasets as da
da.download_dataset('lba', PATH_TO_DATASET) # Download LBA dataset.
```

Or, download and unzip from the [website](https://www.atom3d.ai/).

### Loading a dataset

From python:
```
import atom3d.datasets as da
dataset = da.load_dataset(PATH_TO_DATASET, {'lmdb','pdb','silent','sdf','xyz','xyz-gdb'})
print(len(dataset))  # Print length
print(dataset[0].keys())  # Print keys
```

### LMDB datasets

LMDB allows for compressed, fast, random access to your structures, all within a
single database.  Currently, we support creating LMDB datasets from PDB files, silent files, and xyz files.

#### Creating an LMDB dataset

From command line:
```
python -m atom3d.datasets PATH_TO_PDB_DIR PATH_TO_DATASET --filetype {pdb,silent,xyz,xyz-gdb} 
```

For more usage, please see the [documentation](https://atom3d.readthedocs.io/en/latest/).

## Contribute

As a living repository, we welcome contributions of additional datasets, methods, and functionality!  See the [Contributing](https://atom3d.readthedocs.io/en/latest/contributing.html) section of the documentation for details.

## Support

For support, please file an issue at https://github.com/drorlab/atom3d/issues.

## License

The project is licensed under the [MIT license](https://github.com/drorlab/atom3d/blob/master/LICENSE).

## Reference

We provide an overview on ATOM3D and details on the preparation of all datasets in our preprint:

> R. J. L. Townshend, M. Vögele, P. Suriana, A. Derry, A. Powers, Y. Laloudakis, S. Balachandar, B. Jing, B. Anderson, S. Eismann, R. Kondor, R. B. Altman, R. O. Dror "ATOM3D: Tasks On Molecules in Three Dimensions", [arXiv:2012.04035](https://arxiv.org/abs/2012.04035)
  
Please cite this work if some of the ATOM3D code or datasets are helpful in your scientific endeavours. For specific datasets, please also cite the respective original source(s), given in the preprint.