semvec/pypi-packages huggingface dataset:
deep-kolibri 0.4.0
Deep Learning and more NLP toolkit
Requires Python: >=3.7

# Kolibri

A comprehensive multi modal machine learning platform
# Contents

```
├── README.md
├── config

```

- `README.md`: this documentation

# Setting up PyFreeLing in Mac OS Sierra

There are 4 types of dependencies:

- [Homebrew](https://brew.sh), a package manager to install software in Mac
- [FreeLing](http://nlp.lsi.upc.edu/freeling), an open source language analysis tool suite
- [Python 3](https://www.python.org)
- [lxml](http://lxml.de), a Python library to work with XML
- [libxml2](http://xmlsoft.org) and [libxslt](http://xmlsoft.org/libxslt) C libraries which are dependencies of `lxml`

## Install Homebrew

Follow [Neil Gee's guide](https://coolestguidesontheplanet.com/installing-homebrew-on-macos-sierra-package-manager-for-unix-apps) to install and set up homebrew for Mac OS Sierra

## Install FreeLing

Use Homebrew to install FreeLing by running this command:

```bash
brew install freeling
```

Homebrew will take care of any dependencies.

## Install Python 3

You can install Python 3 with Homebrew following the instructions from [The Hitchhiker's Guide to Python](http://python-guide-pt-br.readthedocs.io/en/latest/starting/install3/osx/) or following the very complete [Lisa Tagliaferri's guide](https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-local-programming-environment-on-macos).

Basically:

```bash
brew install python3
```

## Install libxml2 and libxslt

macOS Sierra already provides `libxml2` and `libxslt`. They can be installed through Homebrew though:

```bash
brew install libxml2
brew install libxslt
```

## Install lxml

Now, you are ready to install `lxml`:

```bash
pip3 install lxml
```



Once you have installed FreeLing and all the dependencies, you will always need to start a FreeLing analyzer in server mode


## Starting a FreeLing analyzer in server mode


```bash
analyze -f en.cfg --server --port 50005 &
```


# Install pyaudio

## install pyaudio in Windows
Intalling pyaudiocan be tricky in window platform and generally 'pip install pyaudio' will not work.
see the following stackoverflow response if you have any problem.

https://stackoverflow.com/questions/52283840/i-cant-install-pyaudio-on-windows-how-to-solve-error-microsoft-visual-c-14

## Install pyaudio in mac os x

First install portaudio

```bash
brew install portaudio 
```
the run the following command
```bash
pip install --global-option='build_ext' --global-option='-I/usr/local/include' --global-option='-L/usr/local/lib' pyaudio
```

# install pocketsphinx

Instaaling this library could be difficult on some systems.
If the command:
```bash
pip install pocketsphinx 
```
did not work for you then try the following steps
```bash
git clone --recursive https://github.com/bambocher/pocketsphinx-python
cd pocketsphinx-python
```

Edit file pocketsphinx-python/deps/sphinxbase/src/libsphinxad/ad_openal.c.

Change
```
#include <al.h>
#include <alc.h>
```

to
```
#include <OpenAL/al.h>
#include <OpenAL/alc.h>
```
and finally:
```bash
python setup.py install
```
vshinet 1.0.0
HINet function for VapourSynth
Requires Python: >=3.6

# HINet
Half Instance Normalization Network for Image Restoration, based on https://github.com/JingyunLiang/SwinIR.


## Dependencies
- [NumPy](https://numpy.org/install)
- [PyTorch](https://pytorch.org/get-started), preferably with CUDA. Note that `torchvision` and `torchaudio` are not required and hence can be omitted from the command.
- [VapourSynth](http://www.vapoursynth.com/)
- (Optional) [TensorRT](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html). Note that `uff` and `PyCUDA` are not required and hence can be skipped from the guide.
- (Optional) [torch2trt](https://nvidia-ai-iot.github.io/torch2trt/master/getting_started.html#install-without-plugins)


## Installation
```
pip install --upgrade vshinet
python -m vshinet
```


## Usage
```python
from vshinet import HINet

ret = HINet(clip)
```

See `__init__.py` for the description of the parameters.
checksums 0.0.1
A command line tool that show/verify checksums for a file.
Requires Python: >=3.6

# checksums

A command line tool that show/verify checksums for a file. Works on Windows, macOS and Linux.

## Installation

```
pip install checksums
```

## Usages

- Show checksums of a file:

```
$ checksums ./file.txt
```

- Verify the MD5 checksum of a file:

```
$ checksums check-md5 [MD5-checksum here] ./file.txt
```

- Verify the SHA-1 checksum of a file:

```
$ checksums check-sha1 [SHA-1-checksum here] ./file.txt
```

- Verify the SHA-256 checksum of a file:

```
$ checksums check-sha256 [SHA-256-checksum here] ./file.txt
```

- Verify the SHA-512 checksum of a file:

```
$ checksums check-sha512 [SHA-512-checksum here] ./file.txt
```