semvec/pypi-packages huggingface dataset:
seeded-graph-matching 1.0.5
Python port of seeded graph matching (SGM)
License: MIT

### sgm

Python port of [seeded graph matching (SGM)](https://arxiv.org/pdf/1209.0367.pdf)

#### Example Usage

Simple example:
```
cd examples/synthetic
python main.py
```

More complex example:
```
cd examples/kasios/
python kasios.py --num-nodes 1000 --num-seeds 32 --backend scipy.classic.jv
```
palettify 0.0.6
Apply color palettes on images.
License: MIT
Requires Python: >=3.6.0,<3.11

# palettify - Apply color palettes to images within seconds

## Requirements
You will need either [pillow](https://github.com/python-pillow/Pillow) or [pillow-simd](https://github.com/uploadcare/pillow-simd). The latter might give a performance boost, however it does not support as many architectures.

## Installation
The installation itself is quite easy, simply run:
```
pip install palettify
```
<details>
<summary>
    Didn't work?
</summary>

- `pip` is not in `PATH`
    ```sh
    python -m pip install palettify
    ```

- Check if the path of your python executable matches the path of the interpreter you run your code with<br>
    In UNIX-like systems:
    ```sh
    which python
    ```

</details>

## Usage
You can use either the command-line or the python API to palettify an image.

Through the command-line:
Invoke palettify using `palettify` or `python -m palettify`.

### paths [paths ...] (required)
You can input multiple images, each one pointing to an existing file. A list of supported image formats can be found [here](https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html).

### -p/--palette (required)
The color palette to use. If an integer `n`, palettify will try to find the `n` most dominant colors in the original image and build the palette using those colors. Otherwise, a path to a JSON file should be specified, containing a list of RGB channels.
```json
[
    [255, 255, 255],
    [0, 0, 0],
    [0, 255, 0],
    [255, 255, 0]
]
```

### -o/--output (optional)
If more than one input path is given, the output path **has** to be an existing directory. If only one input path is given, the output path can be either a directory or the path to a file. If no output path is given, palettify will create path duplicates of the input paths and add a `-palettified` suffix.

### -a/--autoscale (optional)
If autoscale is enabled, palettify tries to find the desktop resolution and resizes the image accordingly, while keeping the original ratio. A display server is required Defaults to `False`.

### -w/--width (optional)
The width of the palettified image. If `-h/--height` is not given, palettify will calculate the height to keep the original ratio.

### -H/--height (optional)
The height of the palettified image. If `-w/--width` is not given, palettify will calculate the width to keep the original ratio. If neither `width` or `height` are given, palettify will use the resolution of the original image.

### -t/--threads (optional)
The number of threads to start for a single image. Defaults to `10`.

### -v/--verbose (optional)
Whether to explain what is being done. Defaults to `False`.

## Invoking palettify through python
```py
from palettify import palettify_image

palettify_image(...)
```

You can pass in the same arguments as in the command-line. However, optional arguments are keyword-only.