semvec/pypi-packages huggingface dataset:
Dio-Images 0.0.1
projeto python leitura da imagem
Requires Python: >=3.8

# package_name

Description. 
The package package_name is used to:
	Processing:
		- Histogram matching
		- Structural similatiy
		- Resize Imagem
	Utils:
		- Road imagem
		- Save Imagem
		- Plot Image
		- Plot result
		- Plot hitogram 

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install image_processing
```

## Usage

```python
from package_name.module1_name import file1_name
file1_name.my_function()
```

## Author
Theoldwine

## License
[MIT](https://choosealicense.com/licenses/mit/)
ananimlib 0.0.1.1
Mathematically Precise Animations, Intuitive and Extensible API


============================================================
Welcome to *AnAnimLib*
============================================================

.. image:: docs/Logo.gif
  :width: 100%

|

AnAnimlib was inspired by `ManimLib <https://github.com/3b1b/manim>`_ by Grant
Sanderson of `3Blue1Brown <https://www.youtube.com/c/3blue1brown>`_.  The aim of AnAnimlib is to facilitate the creation
of mathematically preceise animations through an intuitive and extensible API.

As a simple example, the following code spins a square it as it moves across the canvas.

.. code-block:: python

    import ananimlib as al

     rect = al.Rectangle([1,1])

     al.Animate(
         al.AddAnObject(rect),
         al.MoveTo(rect,[-3.0,0.0]),
         al.RunParallel(
             al.Move(rect, [6,0], duration=1.0),
             al.Rotate(rect, 2*3.1415, duration=1.0),
         ),
         al.Wait(1.0)
    )

    al.play_movie()


.. image:: quickstart_ex3.gif
    :width: 95%
    :align: center
 

Installation instructions:

.. code-block::

    > pip install ananimlib
    
Documentation available at `Read The Docs <https://ananimlib.readthedocs.io/en/latest/index.html>`_
mumuzi 1.2.3
ctf全栈全自动解题姬mumuzi
Requires Python: >=3.6

description
======
------

什么是mumuzi
------
套娃之神mumuzi，在misc题基础上创造性地融入了围棋和套娃元素，开创了musc新分类，他出的题被亲切地称为“一题顶过去五题”，做完之后腰酸了，背疼了，跳楼也有劲了。


更新记录
=======
-------
v0.0.1 beta版本。

v0.1.0 更新txt文档的套娃功能。

v0.1.1 更新套神必须先说话再套娃的功能。

v0.1.2 更新套神语录。

v0.1.3 更新txt文档的解套功能；更新压缩文件的加套功能；拆分套神语录。

v0.1.4 更新txt文档的加套解套功能，去除效率极低的base92和hex。

v1.0.0 更新套神说话时添加分隔符；更新了套题算法并去掉了效率低下的套题算法。删除了不能解题的解题功能，目前正式发布mumuzi的套娃姬版本，版本号为v1.0.0。

v1.0.1 更新zip加密算法；添加了套神口算md5的技能。

v1.0.2 更新了help()函数，现在可以用mumuzi.help()来查看功能了。修复套娃函数只能套一层的奇怪bug。

v1.0.3 更新了套神夸人的功能，修改口算md5，有一定概率失败，这边建议您抽卡。

v1.0.4 更新启动界面。

v1.1.0 解题姬正式上线，更新了套神的解题功能，但是给不给你解要看套神的心情。顺便修复口算md5的逻辑bug，并提高套神夸人概率，现在更容易获得套神的夸奖了。

v1.1.1 修复部分bug。

v1.1.2 根据热心群友的建议，优化部分交互文本。

v1.1.3 更新了套神的笔算BTC的技能，有一定概率失败，这边建议您抽卡。

v1.1.4 更新了套神的手撸算式的技能，有一定概率失败，这边建议您抽卡。另外现在可以封套神的号了，如果你有管理员的身份，现在可以ban掉套神了，不过又有谁舍得ban掉套套子呢?

v1.1.5 考虑到套神实际的计算能力，适当提升了套神手撸算式算法的真实性。

v1.2.0 套神解封，喜大普奔，恭迎套神归位！！！此为ctfshow红包题，是个梗题，上班摸鱼的时候写的，所以代码丑陋，各位大师傅轻喷。现在国庆已过，上线真正能解题的版本。

v1.2.1 套神太炫了！！！！！

v1.2.2 套神更炫了！！！！！！！！！！但是请你不要再黑我电脑了好不好，网费不够用了！！！！！！！！！！

v1.2.3 套宝~嘿嘿~我的套宝~嘿嘿
gofile-dl 1.2.2
Download files from gofile.io
Requires Python: >=3.6

# gofile-dl

## Features
- Download files and folders (including nested items) from Gofile.
- Even works with "overloaded" content.

## Installation
### via [`pipx`](https://packaging.python.org/guides/installing-stand-alone-command-line-tools/) (recommended)
```
pipx install gofile-dl
```

### via [`pip`](https://pip.pypa.io/en/stable/installation/)
```
pip install --user gofile-dl
```

## Usage
```
$ gofile-dl -h
usage: gofile-dl [-h] [--input-file <file>] [--output-dir <directory>] [--flatten] [--password <password>] [--token <token>] [--dry-run] [--verbose] [--version]
                 [link ...]

positional arguments:
  link                  link to content to download (passing multiple links is supported)

options:
  -h, --help            show this help message and exit
  --input-file <file>, -i <file>
                        file containing Gofile links
  --output-dir <directory>, -o <directory>
                        directory in which to save downloaded files
  --flatten             save all files in the same directory
  --password <password>, -p <password>
                        password of password-protected files
  --token <token>, -t <token>
                        Gofile account token (guest account will be used if omitted)
  --dry-run, --simulate
                        build the download target list but do not download anything
  --verbose, -v         increase output verbosity
  --version             show program's version number and exit
```
gofile-client 1.0.1
Interact with the gofile.io API

# gofile-client
A wrapper around the [gofile.io API](https://gofile.io/api).

## Installation
### via [`pip`](https://pip.pypa.io/en/stable/installation/)
```
pip install --user gofile-client
```

## Usage
```python
from gofile import Gofile

client = Gofile(token='<your-token>')

# Upload a file
response = client.upload_file('path/to/file')
print(response)

# Get the link to a file
folder_contents = client.get_content('<file-id>')
for _, item in folder_contents:
    print(item['link'])
```
base64-to-image 0.0.1
Image to base64 and back.

# Library for converting RGB / Grayscale numpy images from to base64 and back.

## Installation
```
pip install -U image_to_base_64
```

## Conversion

### RGB to base 64
```
base64 = rgb2base64(rgb_image, image_format)
```
where image format is `JPEG`, `PNG`

### Grayscale to base 64

```
base64 = grayscale2base64(grayscale_image)
```

### Base64 to RGB image

```
rgb_image = base64_to_rgb(base64)
```

### Base64 to Grayscale image
```
grayscale_image = base64_to_grayscale(base64)
```


#### Issues
For some reason I cannot convert `RGB` image to `JPEG` representation in base 64 and back without losses.
=> test only for `PNG` and not `JPEG`
image-to-base-64 0.0.1
Image to base64 and back.

# Library for converting RGB / Grayscale numpy images from to base64 and back.

## Installation
```
pip install -U image_to_base_64
```

## Conversion

### RGB to base 64
```
base64 = rgb2base64(rgb_image, image_format)
```
where image format is `JPEG`, `PNG`

### Grayscale to base 64

```
base64 = grayscale2base64(grayscale_image)
```

### Base64 to RGB image

```
rgb_image = base64_to_rgb(base64)
```

### Base64 to Grayscale image
```
grayscale_image = base64_to_grayscale(base64)
```


#### Issues
For some reason I cannot convert `RGB` image to `JPEG` representation in base 64 and back without losses.
=> test only for `PNG` and not `JPEG`
regi0 0.2.4
A Python toolkit to complement and verify biological records.
Requires Python: <3.10,>=3.7

# Regi0

Regi0 is a Python package with useful functions to complement and verify biological records. These functions are divided into two main modules (geographic and taxonomic) and rely on both user data and several web APIs (*e.g.* GNR, IUCN and Species+).

## Installation

Regi0 works with Python versions 3.7 through 3.9.

Using `pip`:
```shell
pip install regi0
```

Using `conda`:
```shell
conda install -c conda-forge
```

## Execution
To check whether the installation of `wiutils` was successful, execute the following command:

```shell
python -c "import regi0"
```
If this does not throw any error, the installation was successful.

You can use any `regi0` function by importing the package from a Python console or script. You can also execute flexible and predefined geographic and taxonomic verification workflows using `regi0`'s command line interface (CLI). For more information about the available functions and the CLI, check the [documentation](https://regi0.readthedocs.io).

## How to contribute

It is recommended to install the package using a [virtual environment](https://www.python.org/dev/peps/pep-0405/) to avoid tampering other Python installations in your system.

1. Clone this repo in your computer:
```shell
git clone https://github.com/PEM-Humboldt/regi0.git
```

2. Go to the project's root:
```shell
cd regi0
```

3. Install the package in development mode:
```shell
pip install --editable .[dev,docs,test]
```

Considering `regi0` has dependencies such as `fiona` and `rasterio`, which may require additional installation steps to the ones described above (see [1] and [2]), it is also recommended using a [`conda` virtual environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) to install it and avoid having to manually install other dependencies.

1. Go to the project's root and create the `conda` virtual environment:
```shell
conda env create -f environment.yml
```

2. Activate the `conda` virtual environment:
```shell
conda activate regi0-dev
```

3. Install the package in development mode:
```shell
pip install --editable .[dev,docs,test]
```

### Unit tests
Go to the project's root and execute:

```
pytest tests/
```

## Authors and contributors

* Erika Suarez-Valencia - [erikasv](https://github.com/erikasv)
* Helena Olaya-Rodríguez - [heleolaya](https://github.com/heleolaya)
* Marcelo Villa-Piñeros - [marcelovilla](https://github.com/marcelovilla)

## License
This project is licensed under the MIT License - see the [LICENSE.txt](LICENSE.txt) file for details.

[1]: https://github.com/Toblerity/Fiona#installation
[2]: https://github.com/mapbox/rasterio#installation