semvec/pypi-packages huggingface dataset:
fantasy-face 1.0.0
Add an animal mask to the face

# Fantasy Face

Add an animal mask to the face using OpenCV and Python.

## Description

`Fantasy Face` is a Python package that allows you to overlay an animal mask onto a face in an image. It uses OpenCV for image processing.

## Installation

To install the package, you can use the following command:

```sh
pip install git+https://github.com/SinaHosseini/amoo_sina_lion.git
```

## Usage

Here's an example of how to use the package:
``` python
import fantasy_face
import cv2

# Define the paths to the images
image_path = "path/to/your/image.jpg"
cow_path = "input/cow.jpg"

# Read the images
my_image = cv2.imread(image_path)
image_cow = cv2.imread(cow_path)

# Resize images if needed
my_image = cv2.resize(my_image, [640, 640])
image_cow = cv2.resize(image_cow, [640, 640])

# Apply the mask
image_cow_ghost, image_cow_transparent = fantasy_face.transparent_sticker(image_cow)
convert_image = my_image * image_cow_ghost + image_cow_transparent

# Save the result
cv2.imwrite("output/animal_face.jpg", convert_image)
```

You can also run the script directly from the command line:
```bash
python fantasy_face.py --image_path path/to/your/image.jpg
```
## Requirements
Python 3.6+<br>
OpenCV<br>
NumPy
## Author
Sina Hosseini

Email: sshosseinivaez@gmail.com
## License
This project is licensed under the MIT License - see the LICENSE file for details.
SubCMedians 0.0.10
Weight-based Subspace Clustering

# PySubCMedians

__Authors__: Sergio Peignier, Christophe Rigotti, Anthony Rossi and Guillaume Beslon

Python implementation of the SubCMedians algorithm. SubCMedians is a Subspace Clustering algorithm that extends the K-medians paradigm. SubCMedians is a simple hill climbing algorithm based on stochastic weighted local exploration steps. This median based algorithm exhibits satisfactory quality clusters when compared to well-established paradigms, while medians have still their own interests depending on the user application (robustness to noise/outliers and location optimality). Detailled description available in the paper "Weight-based search to find clusters around medians in subspaces" presented in the ACM SAC conference 2018.

# Installation



# Dependencies :

+ numpy
+ pandas
+ seaborn
+ scikit-learn
+ scipy
+ tqdm
visio-library 0.1.1
A library to automate Visio operations.
Requires Python: >=3.6

# Visio Library

A library to automate Visio operations.

## Installation

pip install visio_library

## Usage
### List Open Documents
from visio_library import loaded_docs
loaded_docs()

### Initialize Visio Application
from visio_library import vInit
vInit(0, globals_dict=globals())
print(c.visSectionUser)
espresso-machine 0.0.225
Quantum Espresso automation tool
Keywords: pypi, cicd, python

# Espresso Machine
Automation library for Quantum Espresso via python

# Start by executing adiabatic.sh
Edit parameters in the file for local environment. Such as HPC parameters, python, MPI, Quantum Espresso directories
## Input parameter
input.json file is supported in Example foldeer
## Calculation type
vc-relax, relax, scf, band
## Degauss parameter
Fermi-Dirac smearing width in Ry
## K points
nx ny nz type mesh grid or k space path
## Initial guess or poscar
Read from vc-relax or poscar file
text-adventure-game 0.1.3
冒险战斗恋爱文字游戏
Requires Python: >=3.6


# 冒险战斗恋爱文字游戏 (Adventure Battle Romance Text Game)

这是一个基于文本的冒险游戏，其中包括探索、战斗和恋爱元素。

This is a text-based adventure game that includes exploration, battles, and romance elements.

## 安装 (Installation)

```bash
pip install text-adventure-game
```

## 使用 (Usage)

```python
from text_adventure_game import game_run

if __name__ == "__main__":
    game_run()
```

## 开发 (Development)

如果你想参与开发，欢迎提交 Pull Request。

If you want to contribute to the development, feel free to submit a Pull Request.

## 作者信息 (Author Information)

将和，qq:1727949032

Jiang He, QQ: 1727949032
jose-hello-world 0.0.1.1
Quicksample HelloWorld Test Package Demo
Requires Python: >=3.6

# Foobar

A sample python package deployment utility for Demo.


## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install foobar.

```bash
pip install foobar
```

## Usage

```python
import foobar

# returns 'words'
foobar.pluralize('word')

# returns 'geese'
foobar.pluralize('goose')

# returns 'phenomenon'
foobar.singularize('phenomena')
```

## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](https://choosealicense.com/licenses/mit/)

## How To Build
reliability-chatbot 0.34
A Django app for chatbot functionality.

# My Django Package

My Django Package is a web application for managing and querying documents using a chatbot interface. It supports multiple file formats, extracts text from documents, and uses an AI model to answer questions based on the content of uploaded documents.

## Features

- View and manage chat sessions

## Installation

### Prerequisites

- Python 3.11
- Django 3.2 or higher

### Steps

1. **Install the package:**

   ```bash
   pip install reliability-chatbot -t .
   ```

2. **Set up a virtual environment:**

   ```bash
   pip install virtualenv

   virtualenv env

   # On Windows
   .\env\Scripts\activate

   # On macOS/Linux
   source env/bin/activate

   pip install -r requirements.txt
   ```

3. **Set up the Django project:**

   ```bash
   python3.11 validate_api_key.py      # Enter api key
   python manage.py makemigrations
   python manage.py migrate
   python manage.py createsuperuser
   ```

## Usage

1. **Integrate the library in your code:**
   **settings.py:**

   Add `app1` to your `INSTALLED_APPS` list:

   ```python
   INSTALLED_APPS = [

       'app1',

   ]
   ```

**views.py:**

```python
from app1.views import save_to_database  # to save questions and answers in the database
from app1.views import get_answer_from_database  # to check answers from database before asking llm
```

**urls.py:**

```python
from django.urls import path
from app1.views import submit_feedback   # to send feedback for the generated or retrieved answer

urlpatterns = [
    path('submit_feedback/', submit_feedback, name='submit_feedback'),
    # other paths...
]
```

By following these instructions, you should be able to set up and use your Django package correctly.
heros-time-syncronizer 0.1.0
A Time Syncronizer for HEROS
Requires Python: >=3.9

1. 패키지를 빌드하기 위해 setuptools와 wheel을 설치합니다.: pip install setuptools wheel
2. 그런 다음 패키지를 빌드합니다: python setup.py sdist bdist_wheel
3. PyPI에 업로드하기 위해 twine을 설치합니다: pip install twine
4. PyPI에 업로드합니다: twine upload dist/*
hack4u-adraul 0.10.6
ejemplo de proyecto cursos Hack4u

# Hack4u Academy Library
 Una biblioteca Python pra consultar cursos de la academia Hack4u
 
 ## Cursos dispobibles:

- Introduccion a Linux [15 horas]
- Personalización de Linux[3 horas]
- Introduccion al Hacking[53 horas]

## Instalación

Instala el paquete usando `pip3`:

### Listar todos los cursos

```python
from hack4u import list_courses
for course in list_courses():
    print(course)
```

#### Obtener un curso por nombre

```python
from hack4u import search_by_name
course = search_by_name("Introduccion al Hacking"):
print(course)
```

#### calcular duracion total de los cursos

```python
from hack4u.utils import total_duration
print(f"Duracion total: {total_duration()} horas")
```
example-package-hamolicious 1.0.0
A small example package
Requires Python: >=3.12

# Example Package

This is a simple example package. You can use
[GitHub-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.


## Publishing
Use `make build` to generate the necessary files for upload. Then, use `make publish` to publish it upstream.
Use `__token__` as the username and the actual token as the password.