semvec/pypi-packages huggingface dataset:
qrclipboard 0.1.3
This script reads the content of the clipboard and displays it as a QR code.
License: MIT
Requires Python: >=3.6

# QRClipboard

QRClipboard is a Python package that creates QR codes from the contents of the clipboard.

![QRClipboard](https://github.com/Friedjof/QRClipboard/blob/main/media/test-image-01.png)

## Installation
### PyPi.org with pipx
https://pypi.org/project/QRClipboard/

```sh
pipx install QRClipboard
```

### Manually
To install the package, follow these steps:

1. First, create the package by running the `make build` command. This command will generate the source distribution (`sdist`) and wheel (`bdist_wheel`) for the package.

2. Once the package is built, you can install it using `pipx` with the `make install` command. This command installs the package in an isolated environment to avoid any conflicts with other packages.

## Usage
After installing the package, you can execute it using the `qrclip` command:

```sh
qrclip
```

This command will read the current content of the clipboard, generate a QR code from it, and display the QR code.

## Development
To contribute to this project, follow these steps:

1. Fork the repository on GitHub.
2. Create a new branch for your feature or bug fix:
   ```sh
   git checkout -b feature-new-feature
   ```
3. Make your changes and commit them with a meaningful message:
   ```sh
   git commit -m 'Add new feature'
   ```
4. Push your changes to GitHub:
   ```sh
   git push origin feature-new-feature
   ```
5. Open a pull request on GitHub to merge your changes.

## Commands
The project includes a `Makefile` that simplifies various tasks:

- To build the package, use `make build`. This command runs the `setup.py` script to create the source distribution and wheel for the package.

- To install the package, use `make install`. This command utilizes `pipx` to install the package in an isolated environment.

- To uninstall the package, use `make uninstall`. This command removes the package installed by `pipx`.

- To clean the build directories, use `make clean`. This command deletes the `build`, `dist`, and `.egg-info` directories to ensure a clean state.

- To run unit tests, use `make test`. This command executes all unit tests located in the `tests` directory to verify that the package works as expected.

- To upload the package to PyPI, use `make upload`. This command uses `twine` to upload the built distributions to the Python Package Index (PyPI). This step is optional and requires the `twine` module to be installed.

- To run the main script of the package, use `make run`. This command executes the main function defined in the `QRClipboard.main` module.

## License
This project is licensed under the MIT License. For more details, refer to the `LICENSE` file.
vdms 0.0.22
VDMS Client Module
License: MIT
Requires Python: !=3.0.*,!=3.1.*,!=3.2.*,<4,>=2.6

# VDMS Client Python Module

This is the client module for Intel Lab's Visual Data Management System (VDMS).
It provides utilities for interacting with the VDMS server.

## Installing
To install this client, run the following:
```bash
pip install vdms
```

## Connect to VDMS Server
To connect to a VDMS server, you must provide the `HOST` and `PORT` where the VDMS server is deployed.
By default, the `HOST` and `PORT` are `localhost` and `55555`, respectively.
```python
import vdms
db = vdms.vdms()
db.connect()
```
or you can specify other values for `HOST` and `PORT`:
```python
import vdms
db = vdms.vdms()
db.connect(HOST, PORT)
```

For more information, visit [VDMS Documentation](https://intellabs.github.io/vdms/).
mkdocs-codeforces-plugin 0.1.2
MkDocs plugin to display Codeforces user statistics as beautiful cards
License: MIT
Requires Python: >=3.7

# mkdocs-codeforces-plugin

一个 MkDocs 插件，用于在文档网站上以美观的卡片形式展示 Codeforces 用户的统计信息。

## 功能特点

- 显示用户的用户名、等级、积分等基本信息
- 展示最近的提交记录及其状态
- 展示最近参加的比赛及积分变化
- 可自定义卡片宽度和主题（浅色/深色）
- 内置缓存系统，避免频繁调用 API
- 响应式设计，适配各种设备屏幕

## 安装方式

使用 pip 安装插件：

```bash
pip install mkdocs-codeforces-plugin
```

或者将其添加到你的 `requirements.txt` 文件中：

```
mkdocs-codeforces-plugin==0.1.2
```

## 配置说明

在你的 `mkdocs.yml` 文件中添加插件配置：

```yaml
plugins:
  - codeforces:
      cache_dir: '.cache/codeforces'  # 缓存目录
      cache_ttl: 3600                 # 缓存有效期（秒）
      default_username: ''            # 默认 Codeforces 用户名
      default_width: '100%'           # 默认卡片宽度
      default_theme: 'light'          # 默认主题（'light' 或 'dark'）
```

CSS 文件已内置到插件中，无需手动添加到 `extra_css`。插件会自动管理样式，确保卡片显示正常。

## 使用方法

在你的 Markdown 文件中，使用 `codeforces` 标签来显示用户的统计信息：

```markdown
{% codeforces username="你的_codeforces用户名" width="80%" theme="light" %}
```

参数说明：
- `username`: Codeforces 用户名（必需）
- `width`: 卡片宽度（可选，默认为配置中的值）
- `theme`: 卡片主题，'light' 或 'dark'（可选，默认为配置中的值）

### 示例

```markdown
# 我的 Codeforces 个人资料

这是我的 Codeforces 个人资料：

{% codeforces username="Eurekaimer" width="100%" theme="light" %}
```

## 缓存管理

插件会缓存 API 响应以减少对 Codeforces 的请求次数。你可以：
- 通过 `cache_ttl` 调整缓存持续时间
- 通过删除 `cache_dir` 中的文件手动清除缓存
- 插件会在每次构建后自动清理过期的缓存文件

## 修改用户名

要修改插件中显示的用户名，您需要在 mkdocs.yml 配置文件中更新插件的配置：

```yaml
plugins:
  - codeforces:
      username: Your_Codeforces_Username  # 在这里修改为您的用户名
      cache_dir: .cache/codeforces
      cache_ttl: 3600
```

或者，您也可以在使用 `codeforces` 标签时直接指定用户名参数：

```markdown
<codeforces username="Your_Codeforces_Username" width="100%" theme="light"/>
```


## 许可证

本项目采用 MIT 许可证 - 详见 LICENSE 文件。
deep-person 0.2.0
Person re-identification component for Vbot framework
License: MIT
Requires Python: >=3.11
Keywords: computer-vision, deep-learning, person-reid, resnet, yolo

# DeepPerson

[![PyPI version](https://badge.fury.io/py/deep-person.svg)](https://badge.fury.io/py/deep-person)
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A simple person re-identification system with automatic person detection and embedding generation.

## Installation

```bash
pip install deep-person
```

## Quick Start

```python
from deep_person import DeepPerson

dp = DeepPerson()

# Generate embeddings
result = dp.represent("person.jpg")

# Verify if two images show the same person
result = dp.verify("person1.jpg", "person2.jpg")
print(f"Same person: {result['verified']}")
```

## Features

- **Automatic person detection** - YOLO-based detection
- **Multi-modal embeddings** - Body (2048-dim) + Face (512-dim) or via Model Registry
- **Identity verification** - Cosine/Euclidean distance metrics
- **GPU acceleration** - Automatic CUDA detection with CPU fallback
- **Batch processing** - Efficient multi-image handling

## Requirements

- Python 3.11+
- Models downloaded automatically on first use
- Optional: CUDA GPU for faster processing