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on my machine](https://img.shields.io/badge/works-on%20my%20machine-green)\n\n[![Python](https://img.shields.io/badge/Python-%203.10-blue.svg)](https://www.python.org/downloads/)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)\n[![Stargazers](https://img.shields.io/github/stars/tdh8316/triangler.svg)](https://github.com/tdh8316/triangler/stargazers)\n[![Twitter URL](https://img.shields.io/twitter/url?style=social\u0026url=https%3A%2F%2Fgithub.com%2Ftdh8316%2Ftriangler)](https://twitter.com/intent/tweet?text=Convert%20images%20to%20Low-Poly%20art:\u0026url=https%3A%2F%2Fgithub.com%2Ftdh8316%2Ftriangler)\n\n# Overview\n\n📐 Convert images to Low-Poly art using [Delaunay triangulation](https://en.wikipedia.org/wiki/Delaunay_triangulation).\n\n![sample](images/triangler-monroe.jpg)\n\n## Table of contents\n\n1. [Installation](#installation)\n2. [Usage](#usage)\n3. [Use as a library](#api)\n4. [Sample](#sample)\n5. [License](#license)\n\n## Installation\n\nYou need [Python](https://www.python.org/) 3.10 or higher.\n\nI strongly recommend to use virtual environment such as Anaconda.\nYou can [download Anaconda here](https://www.anaconda.com/distribution/#download-section).\n\nFollow manual below to create conda virtual environment for Triangler with the Anaconda.\n\n```cmd\n$ conda create -n triangler python=3.12\n$ activate triangler\n(triangler)$ python -m pip install git+https://github.com/tdh8316/triangler/\n```\n\n## Usage\n\n```\n(triangler)$ python -m triangler -h\npositional arguments:\n  input                 Input image\n\noptions:\n  -h, --help            show this help message and exit\n  -o OUTPUT, --output OUTPUT\n                        Output image name\n  -p POINTS, --points POINTS\n                        Number of sample points to use\n  -e {canny,entropy,sobel}, --edge-detector {canny,entropy,sobel}\n                        Edge detection algorithm\n  -s {poisson_disk,threshold}, --sampler {poisson_disk,threshold}\n                        Point sampling algorithm\n  -r {centroid,mean}, --renderer {centroid,mean}\n                        Color polygon rendering algorithm\n  -l, --reduce          Reduce the result image size to match the input image\n  -V, --version         show program's version number and exit\n  -d, --debug           Enable debug mode\n```\n\n## API\n\nYou can also use Triangler as a library.\n\n```python\nimport triangler\n\ntriangler.convert(\n    img=\"INPUT_IMAGE.jpg\",\n    save_path=\"OUTPUT_IMAGE.jpg\",\n)\n```\n\n## Sample\n\n### Effect of the number of points\n\n|                Original Image                |                 5000 Points                  |\n|:--------------------------------------------:|:--------------------------------------------:|\n|         ![sample](images/monroe.jpg)         | ![sample](images/triangler-monroe-5000p.jpg) |\n|               **1000 Points**                |                **500 Points**                |\n| ![sample](images/triangler-monroe-1000p.jpg) | ![sample](images/triangler-monroe-500p.jpg)  |\n\n### More samples\n\n| Original                    | Triangler                             |\n|-----------------------------|---------------------------------------|\n| ![sample](images/birds.jpg) | ![sample](images/triangler-birds.jpg) |\n\n\n## License\n\nLicensed under the MIT License.\n\nCopyright 2024 `Donghyeok Tak`\n\n## Credits\n\nSome algorithms, including the Poisson disk sampling, are based\non [pmaldonado/PyTri](https://github.com/pmaldonado/PyTri).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftdh8316%2Ftriangler","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftdh8316%2Ftriangler","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftdh8316%2Ftriangler/lists"}