semvec/pypi-packages huggingface dataset:
cilissa 0.8.0
Interactive tool for assessing digital image similarity
Requires Python: <3.12,>=3.9

<p align="center">
    <img src="https://raw.githubusercontent.com/exler/CILISSA/main/docs/_static/logo.png" width="328">
</p>
<p align="center">
    <strong>C</strong>omputer <strong>I</strong>mage <strong>Li</strong>keness A<strong>ss</strong>essing <strong>A</strong>utomation
</p>
<p align="center">
    <!-- Badges -->
    <img src="https://github.com/exler/CILISSA/actions/workflows/quality.yml/badge.svg">
    <img src="https://github.com/exler/CILISSA/actions/workflows/tests.yml/badge.svg">
    <a href="https://codecov.io/gh/exler/CILISSA">
        <img src="https://codecov.io/gh/exler/CILISSA/branch/main/graph/badge.svg?token=Dixb5buMQr"/>
    </a>
    <a href="https://cilissa.readthedocs.io/en/latest/">
        <img src="https://img.shields.io/readthedocs/cilissa">
    </a>    
</p>

## Overview

CILISSA allows for the use of various metrics to perform full-reference image comparisons.

It features the most popular full-reference image quality metrics, image transformations and translations. 
CILISSA is also very extensible and new operations can be easily added.

CILISSA has an optional Qt-based graphical interface that lets you experiment with various operations, their orders and properties.

## Requirements

* Python >=3.9,<3.12

## Installation

### Install from PyPI
```bash
$ pip install cilissa
```

### Releases

Binaries for Windows and Linux can be found on [GitHub releases](https://github.com/exler/CILISSA/releases).

## Usage

### GUI

Information about the GUI can be found in the [cilissa_gui/README.md](cilissa_gui/README.md) file.

### CLI

Currently the CLI only supports working with a single pair of images.

The parameters of metrics and transformations can be modified by passing them to the `--kwargs` argument using the following format:
```
<operation-name>-<parameter-name>=<value>
``` 
where `parameter-name` uses hyphens (-) instead of underscores (_)

## Documentation

Documentation is hosted on [Read the Docs](https://cilissa.readthedocs.io/).

## License

`CILISSA` is under the terms of the [MIT License](https://www.tldrlegal.com/l/mit), following all clarifications stated in the [license file](LICENSE).
leoid 1.1.6
LEOID Python Package
Requires Python: >=3.8

## Python Package for Machine Learning Model LEOID (Level-based Ensemble for Overcoming Imbalanced Data)
\
More information about LEOID and example usage is available on Kaggle. [www.kaggle.com/models/jayticku/leoid](https://www.kaggle.com/models/jayticku/leoid)
\
To see LEOID in action, go to [www.diabetes-predictor.com](https://www.diabetes-predictor.com).
openjsoncanvas 3.0.0
A python implementation of the JsonCanvas format: https://github.com/obsidianmd/jsoncanvas/blob/main/spec/1.0.md


# JsonCanvas Python Implementation

This project provides a Python implementation of the [JsonCanvas format](https://github.com/obsidianmd/jsoncanvas/blob/main/spec/1.0.md), designed to facilitate the creation, manipulation, and visualization of a structured canvas using objects and relations. It leverages Python's `pydantic` library to ensure data validation and management, supporting a range of node and edge types for comprehensive canvas construction.

## Features

- Robust model definitions for canvas elements (Nodes and Edges) with comprehensive validation and default settings via `pydantic`.
- Dynamic addition and manipulation of various node types including Text, File, Link, Group, and Edge elements.
- Enhanced canvas operations allowing easy addition of nodes and edges with automated type handling.
- Serialize canvas structures to standard Python dictionaries for easy integration with other systems.

## Installation

```bash
pip install openjsoncanvas
```

## Usage

### Creating a Canvas

Instantiate and manipulate a canvas with various nodes and edges:

```python
from openjsoncanvas import Canvas

canvas = Canvas()

canvas.create_text_node(id='1', x=0, y=0, width=100, height=100, text='Hello, World!')
canvas.create_file_node(id='2', x=100, y=100, width=100, height=100, file='example.md')
canvas.create_link_node(id='3', x=200, y=200, width=100, height=100, url='https://example.com')
canvas.create_group_node(id='4', x=300, y=300, width=100, height=100)
canvas.create_edge(id='5', fromNode='1', toNode='2', fromEnd='arrow', toEnd='arrow', color='red', label='Edge')

# you can save and load the canvas to/from a file
canvas.to_file('my_canvas.canvas')
canvas = Canvas.from_file('my_canvas.canvas')
```
korapay-client 0.1.0
A developer-friendly python client SDK for Korapay
Requires Python: >=3.10

# korapay-client

[![Total Downloads](https://static.pepy.tech/badge/korapay-client)](https://pepy.tech/project/korapay-client)
[![Monthly Downloads](https://static.pepy.tech/badge/korapay-client/month)](https://pepy.tech/project/korapay-client)
[![Weekly Downloads](https://static.pepy.tech/badge/korapay-client/week)](https://pepy.tech/project/korapay-client)

A developer-friendly python client SDK for [Korapay](https://www.korahq.com/)

## Documentation
See [Documentation](https://gray-adeyi.github.io/korapay_client/) for more on this package.
b2tob64 2.0.0
Custom converting b2/b42 to and from b64/b2
Requires Python: >=3.10

This package allows for custom encoding between base2 (bianary) and base 64. <br>
WARNING: THIS WILL NOT TRANSLATE other b64 encodings and will NOT be able to encode/decode the same values <br>
<br>
<br>
Ex. "10101010101000010111111001" --> "ppE9AA" --> "10101010101000010111111001"
<br><br>
Approx. 6x len reduction


<br>

Docs<br>
function b2tob64 requires a single string input of only 1's and 0's <br>
This will return a b64 string (NOTE: this can most likely be decoded ONLY by this program)<br>
<br>
<br>
<br>
function b64tob2 requires a single b64 string input created by the b2tob64 function. <br>
this will return the original binary string.
<br>
<br>
<br>
Unlike some b2 to b64 converters, this allows for conversions on the bit by bit level. <br>
Conviance is nice.
itsdangerous 2.2.0
Safely pass data to untrusted environments and back.
Requires Python: >=3.8

# ItsDangerous

... so better sign this

Various helpers to pass data to untrusted environments and to get it
back safe and sound. Data is cryptographically signed to ensure that a
token has not been tampered with.

It's possible to customize how data is serialized. Data is compressed as
needed. A timestamp can be added and verified automatically while
loading a token.


## A Simple Example

Here's how you could generate a token for transmitting a user's id and
name between web requests.

```python
from itsdangerous import URLSafeSerializer
auth_s = URLSafeSerializer("secret key", "auth")
token = auth_s.dumps({"id": 5, "name": "itsdangerous"})

print(token)
# eyJpZCI6NSwibmFtZSI6Iml0c2Rhbmdlcm91cyJ9.6YP6T0BaO67XP--9UzTrmurXSmg

data = auth_s.loads(token)
print(data["name"])
# itsdangerous
```


## Donate

The Pallets organization develops and supports ItsDangerous and other
popular packages. In order to grow the community of contributors and
users, and allow the maintainers to devote more time to the projects,
[please donate today][].

[please donate today]: https://palletsprojects.com/donate