semvec/pypi-packages huggingface dataset:
phonexia_referential_deepfake_detection_client 1.0.0
Client script for communication with Phonexia referential deepfake detection microservice.
Requires Python: <4.0,>=3.9
Keywords: grpc, voice, voice-biometry, speech, referential, deepfake, detection

![](https://www.phonexia.com/wp-content/uploads/phonexia-logo-transparent-500px.png)

# Phonexia referential deepfake detection client

This module contains client for communication with [Referential Deepfake Detection microservice](https://hub.docker.com/repository/docker/phonexia/referential-deepfake-detection/general) developed by [Phonexia](https://phonexia.com).

To use this client you will first need a running instance of any *Phonexia Referential Deepfake Detection microservice*. If you don't yet have any running instance, don't hesitate to [contact our sales department](mailto:info@phonexia.com).

You can learn more about the speaker identification technology [here](https://docs.phonexia.com/technologies/speaker-identification/).

On [this page](https://docs.phonexia.com/products/speech-platform-4/grpc/api/phonexia/grpc/technologies/referential_deepfake_detection/v1/referential_deepfake_detection.proto), you will find a *gRPC API* reference for *Referential Deepfake Detection microservice*.
progan-h 0.1.0
A CLI tool to provide documentation and examples for machine learning algorithms
Requires Python: >=3.6

# Progan-H

A command-line tool that provides interactive documentation and examples for machine learning algorithms.

## Installation

```bash
pip install progan-h
```

## Usage

Get documentation for specific algorithms:

```bash
progan-h knn
```

List all available algorithms:

```bash
progan-h list
```

## Features

- Beautiful terminal-based documentation
- Code examples for various ML algorithms
- Easy-to-follow tutorials
- Interactive learning experience

## Supported Algorithms

- KNN (K-Nearest Neighbors)
- More algorithms coming soon!

## License

MIT License
hawkeyezero 1.0.0
Hawkeye-Zero - special trained model to detect 11 diffrent types of space debris. The idea wasn’t to build a perfect system — just to explore how far object detection can go in real-world space debris applications. Also very important thing was to care about easy and quick access to use model functions and data, so I've created special structure for this project to allowed developers to use model in diffrent environments in API's or as a simple python tool.
Keywords: yolo, computer vision, deep learning, machine learning, object detection, python, automation, data science, ai, neural networks, image processing, data preparation

![hawkeye_banner (1)](https://github.com/user-attachments/assets/2fc19973-58b3-459d-9dd0-968a7ba8cbc4)

Hawkeye-Zero - special trained model to detect 11 diffrent types of space debris. 
The idea wasn’t to build a perfect system — just to explore how far object detection can go in real-world space debris applications.
It’s still early, but the results are promising. The model's trained on YOLO11 model created from ultralytics. Also very important thing was to care about easy and quick access to use model functions and data, so I've created special structure for this project to allowed developers to use model in diffrent environments in API's or as a simple python tool.

## 📄 Docs
[![PyPI - Version](https://img.shields.io/pypi/v/ultralytics?logo=pypi&logoColor=white)]()  [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ultralytics?logo=python&logoColor=gold)]()

[Read documentation->]()


### Usage
#### Python
```python
from hawkeyeZero import HawkeyeZero

hawkeye = HawkeyeZero(is_dev_mode=True)

hawkeye.use_model()
```

## 🤝 Contributing
That would be a huge pleasure to make this project better, because of your job, so if you want to help me out with this project [Check out this file]()

## 📜License
Current license: [AGPL-3.0 License](https://github.com/Gabrli/Hawkeye-Zero/blob/main/LICENSE)
## 📘Used dataset
[Read more](https://www.kaggle.com/datasets/muhammadzakria2001/space-debris-detection-dataset-for-yolov8?select=data.yaml)

## 📞 Contact
For bug reports and feature requests related to Hawkeye-Zero software, please visit GitHub Issues. For questions, discussions, and community support.
jdk4py 21.0.8.0
A JDK shipped in a Python package
Requires Python: >=3.10
Keywords: jdk, java, jvm, jre

# jdk4py

A JDK shipped in a Python package.

[![PyPI version](https://badge.fury.io/py/jdk4py.svg)](https://badge.fury.io/py/jdk4py)

## Install

```bash
pip install jdk4py
```

or as a Conda package:

```bash
conda config --add channels https://conda.atoti.io
conda install jdk4py
```

## Usage

```python
>>> from jdk4py import JAVA, JAVA_HOME, JAVA_VERSION
>>> JAVA_HOME
PosixPath('/Users/johndoe/dev/jdk4py/jdk4py/java-runtime')
>>> JAVA
PosixPath('/Users/johndoe/dev/jdk4py/jdk4py/java-runtime/bin/java')
>>> JAVA_VERSION
(21, 0, 8)
>>> from subprocess import run
>>> some_java_options = ["-Xmx16G", "-Xms2G"]
>>> run(
...     [JAVA, "-jar", "HelloWorld.jar", *some_java_options],
...     capture_output=True,
...     check=True,
...     text=True,
... ).stdout.strip()
"Hello, World!"
```

## Versioning

`jdk4py`'s version contains 4 numbers:

- The first 3 numbers correspond to the JDK version.
- The fourth number is the library API version.