semvec/pypi-packages huggingface dataset:
paves 0.9.1
PDF, Analyse et Visualisation avancÉS
Requires Python: >=3.8
Keywords: graphics, pdf

# PAVÉS: Bajo los adoquines, la PLAYA 🏖️

[**PLAYA**](https://github.com/dhdaines/playa) is intended to get
objects out of PDF, with no dependencies or further analysis.  So,
over top of **PLAYA**, this package provides **P**DF, **A**nalyse et
**V**isualisation simplifi**É**e**S**.

Or, if you prefer, **P**DF **A**nalysis and **V**isualization for
dummi**ES**.

The goal here is not to provide elaborate, enterprise-grade,
battle-tested, cloud and AI-native, completely configurable and
confoundingly complex classes for ETL.  It's to give you some helpful
functions that you can use to poke around in PDFs and get useful
things out of them, often but not exclusively in the context of a
Jupyter notebook.

See the [documentation](https://dhdaines.github.io/paves) for more
information.  There will also be some helpful notebooks soon, to help
you.

## Installation

Install it from PyPI (as `paves`) with `pip` or `uv`, preferably in a
virtual environment.  That's all.  If you want to play around in the
source code you can use `hatch` or `uv` (your choice), for instance:

    # with hatch
    hatch shell
    # with uv
    uv venv
    uv sync
    . .venv/bin/activate

## License

`PAVÉS` is distributed under the terms of the
[MIT](https://spdx.org/licenses/MIT.html) license.
cucumberify 1.1.1
Cucumber is a free and lightweight vision classifier to detect nsfw, gore, scam, neutral from images
Requires Python: >=3.8

# Cucumber 🥒
Cucumber is a free and lightweight python library to detect nsfw, gore, scam, neutral from images. It utilizes machine learning vision model to do so.

# Installation
```py
pip install cucumberify
```

**NOTE FOR WINDOWS USER:**
This library uses a small compiled extension on Windows (sdist install).
So you must install Microsoft Visual C++ Build Tools first.

1. Download and install:
    https://visualstudio.microsoft.com/visual-cpp-build-tools/

2. During setup, select:
   "Desktop development with C++"

3. Then run:
```py
python -m pip install --upgrade pip setuptools wheel
pip install cucumberify
```

# Example usage (Local Image)
```py
from cucumberify import cucumber
print(cucumber("car.jpg"))
```

# Response example
```py
{'nsfw': 0.0, 'gore': 0.0, 'scam': 0.0, 'neutral': 1.0}
```

# Example usage (Image URL)
```py
from cucumberify import cucumber
print(cucumber('https://cdni.lamalinks.com/1280/1/171/32937397/32937397_001_8121.jpg'))
```

# Response example
```py
{'nsfw': 0.9, 'gore': 0.0, 'scam': 0.0, 'neutral': 0.0}
```

**Note that the values are floating points between 0 and 1**

# Made with ♥️ by [Blaze](https://discord.com/users/1238444724386533417)

# Feel free to DM me on discord if there's any issues :>