semvec/pypi-packages huggingface dataset:
image-processing-navpack 0.2.7
A package for processing and analyzing images.
License: MIT

 # 🖼️ Image Processing Navpack

Um projeto Python para processamento de imagens, utilizando bibliotecas como `scikit-image` e `imageio` para comparar, transformar e salvar imagens.

## 📁 Estrutura do Projeto

```plaintext
image-processing-navpack/
├── image_processing_navpack/
│   ├── imgs/
│   │   ├── imagem1.jpg
│   │   └── imagem2.jpg
│   ├── processing/
│   │   ├── __init__.py
│   │   ├── combination.py
│   │   └── transformation.py
│   ├── utils/
│   │   ├── __init__.py
│   │   ├── io.py
│   │   └── plot.py
│   └── tests/
│       ├── __init__.py
│       ├── test_processing.py
│       └── test_utils.py
├── setup.py
├── README.md
└── test_image.py
🚀 Instalação
Clone o Repositório:

bash
Copiar código
git clone https://github.com/Fabianonavarro/image-processing-navpack.git
Navegue para o Diretório do Projeto:

bash
Copiar código
cd image-processing-navpack
Instale as Dependências Usando setuptools:

Se você não estiver usando um ambiente virtual, é recomendável criar um. Você pode instalar o pacote diretamente no ambiente atual com:

bash
Copiar código
pip install .
Para desenvolver o pacote e fazer alterações, use:

bash
Copiar código
pip install -e .
Ative o Ambiente Virtual (se aplicável):

Se estiver usando um ambiente virtual criado com venv, ative-o com:

bash
Copiar código
source .venv/bin/activate  # No Linux ou macOS
.venv\Scripts\activate  # No Windows
🛠️ Uso
Coloque suas imagens no diretório image_processing_navpack/imgs.

Execute o script principal para processar as imagens:

bash
Copiar código
python test_image.py
Resultados: Os resultados serão salvos no diretório image_processing_navpack/imgs com os seguintes nomes:

difference_image.jpg
histogram_matched_image.jpg
🧪 Testes
Para executar os testes, use o comando:

bash
Copiar código
pytest
📋 Contribuições
Sinta-se à vontade para abrir issues e pull requests para melhorias ou correções.

📜 Licença
Este projeto está licenciado sob a Licença MIT.

📚 Referências
Scikit-Image Documentation
ImageIO Documentation
markdown
Copiar código

### Atualizar `test_image.py`

Certifique-se de que o `test_image.py` não esteja referenciando o nome antigo do projeto e atualize os imports, se necessário.

### Publicar no PyPI

1. **Certifique-se de que o novo nome está disponível no PyPI.**

2. **Construa os arquivos de distribuição:**

   ```bash
   python setup.py sdist bdist_wheel
Publique o pacote:

bash
Copiar código
pip install twine
twine upload dist/*
Verifique a publicação acessando o PyPI e buscando pelo novo nome do pacote.
twitchify 3.2.0
Real-time Twitch Event Handling and Helix API Integration in Python
License: MIT
Requires Python: >=3.8.0

# Twitchify

**Notice:** This package is a mirror.  

For the latest updates and features, it's recommended to install [`twitch.py`](https://pypi.org/project/twitch.py), as `twitchify` is no longer maintained.
faststream-prometheus 0.1.5
FastStream Based Metrics Collection for Prometheus
License: MIT
Requires Python: <4,>=3.9
Keywords: faststream, prometheus

# FastStream Prometheus Collector

FastStream Based Metrics Collection for Prometheus

[![PyPI](https://img.shields.io/pypi/v/faststream-prometheus)](https://pypi.org/project/faststream-prometheus/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/faststream-prometheus)](https://pypi.org/project/faststream-prometheus/)
[![GitLab last commit](https://img.shields.io/gitlab/last-commit/rocshers/python/faststream-prometheus)](https://gitlab.com/rocshers/python/faststream-prometheus)
[![Docs](https://img.shields.io/badge/docs-exist-blue)](https://projects.rocshers.com/open-source/faststream-prometheus/docs)

[![Test coverage](https://codecov.io/gitlab/rocshers:python/faststream-prometheus/graph/badge.svg)](https://codecov.io/gitlab/rocshers:python/faststream-prometheus)
[![Downloads](https://static.pepy.tech/badge/faststream-prometheus)](https://pepy.tech/project/faststream-prometheus)
[![GitLab stars](https://img.shields.io/gitlab/stars/rocshers/python/faststream-prometheus)](https://gitlab.com/rocshers/python/faststream-prometheus)

## Functionality

- Collection metrics via `middleware`
- Collecting general metrics
- Collecting `details kafka` metrics

## Installation

`pip install faststream-prometheus`

## Quick start

See [example](https://gitlab.com/rocshers/python/faststream-prometheus/-/blob/release/test_app.py) for details

```python
import uvicorn
from fastapi import FastAPI
from faststream.kafka.fastapi import KafkaRouter
from prometheus_fastapi_instrumentator import Instrumentator

# Import Faststream Middleware for collect metrics 
from faststream_prometheus import FaststreamPrometheusMiddleware

# Adding middleware 
faststream_router = KafkaRouter(
    'localhost:9092',
    middlewares=[FaststreamPrometheusMiddleware(prefix='test_faststream')],
)

# Setup export metrics via FastAPI -> HTTP GET /metrics
app = FastAPI(lifespan=faststream_router.lifespan_context)
app.include_router(faststream_router)

instrumentator = Instrumentator().instrument(app, metric_namespace='fastapi').expose(app)

```

```bash
# see default metrics
curl localhost:8000/metrics
```

## Contribute

Issue Tracker: <https://gitlab.com/rocshers/python/faststream-prometheus/-/issues>  
Source Code: <https://gitlab.com/rocshers/python/faststream-prometheus>

Before adding changes:

```bash
make install-dev
```

After changes:

```bash
make format test
```
omnetpypy 0.1.4
An omnet++-like simulation framework fully implemented on Python, with the possibility to support different simulation backends such as SimPy.
License: MIT

An omnet++-like simulation framework fully implemented on Python, with the possibility to support different simulation backends such as SimPy.

Visit the tutorial and documentation page [here](https://lbacciottini.github.io/OmnetPyPy/).
textipic 0.1
A script to generate images from text
License: MIT

# Textipic

`textipic` is a Python script that converts text files into images. The script allows customization of text color, background color, and image format.

## Installation

You can install the package from PyPI using pip:

```bash
pip install textipic


Usage
After installation, you can run the script from the command line:

textipic



Follow the interactive prompts to specify the text file, choose colors, and save the image.

Author
Avinion