{"id":22788479,"url":"https://github.com/darsan-in/pixteroid","last_synced_at":"2025-04-16T01:27:21.896Z","repository":{"id":265027194,"uuid":"821585397","full_name":"darsan-in/Pixteroid","owner":"darsan-in","description":"Pixteroid is a Node.js API designed for efficient image upscaling and restoration, powered by AI and utilizing the NCNN framework. It employs Real-ESRGAN and ESRGAN model weights to upscale and restore images, providing three distinct levels of detail and size customization to suit various needs.","archived":false,"fork":false,"pushed_at":"2024-12-08T11:12:47.000Z","size":16471,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-15T22:46:56.048Z","etag":null,"topics":["ai-image-processing","ai-powered","custom-image-scaling","detail-enhancement","e-commerce-tools","esrgan","graphic-design-tools","high-resolution-images","image-quality","image-restoration","image-upscaling","ncnn-framework","node-js-image-api","open-source","performance-optimization","photography-enhancement","print-media","real-esrgan","scaling-algorithms","web-development"],"latest_commit_sha":null,"homepage":"https://www.npmjs.com/package/pixteroid","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/darsan-in.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-06-28T22:18:37.000Z","updated_at":"2025-02-11T12:58:47.000Z","dependencies_parsed_at":"2024-11-27T08:46:34.484Z","dependency_job_id":"d14ee381-4621-4a32-8581-9a3173dd2454","html_url":"https://github.com/darsan-in/Pixteroid","commit_stats":null,"previous_names":["darsan-in/pixteroid"],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/darsan-in%2FPixteroid","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/darsan-in%2FPixteroid/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/darsan-in%2FPixteroid/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/darsan-in%2FPixteroid/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/darsan-in","download_url":"https://codeload.github.com/darsan-in/Pixteroid/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249181294,"owners_count":21225878,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai-image-processing","ai-powered","custom-image-scaling","detail-enhancement","e-commerce-tools","esrgan","graphic-design-tools","high-resolution-images","image-quality","image-restoration","image-upscaling","ncnn-framework","node-js-image-api","open-source","performance-optimization","photography-enhancement","print-media","real-esrgan","scaling-algorithms","web-development"],"created_at":"2024-12-12T01:31:44.563Z","updated_at":"2025-04-16T01:27:21.878Z","avatar_url":"https://github.com/darsan-in.png","language":"TypeScript","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n# Pixteroid - AI-Powered Image Upscaling and Restorative API\n\n\u003cp id=\"intro\"\u003ePixteroid is a Node.js API designed for efficient image upscaling and restoration, powered by AI and utilizing the NCNN framework. It employs Real-ESRGAN and ESRGAN model weights to upscale and restore images, providing three distinct levels of detail and size customization to suit various needs.\u003c/p\u003e\n\n\n### Supported Platforms\n\n[![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge\u0026logo=linux\u0026logoColor=black)]()\n[![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge\u0026logo=windows\u0026logoColor=white)]()\n[![Node JS](https://img.shields.io/badge/Node.js-43853D?style=for-the-badge\u0026logo=node.js\u0026logoColor=white)]()\n\n\n---\n\n\n\u003cp\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"https://github.com/darsan-in/Pixteroid/commits/main\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/last-commit/darsan-in/Pixteroid?display_timestamp=committer\u0026style=for-the-badge\u0026label=Updated%20On\" alt=\"GitHub last commit\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/commit-activity/m/darsan-in/Pixteroid?style=for-the-badge\u0026label=Commit%20Activity\" alt=\"GitHub commit activity\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003c/p\u003e\n\n---\n\n\u003cp\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"LICENSE\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/license/darsan-in/Pixteroid?style=for-the-badge\u0026label=License\" alt=\"GitHub License\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"https://github.com/darsan-in/Pixteroid/releases\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/v/release/darsan-in/Pixteroid?include_prereleases\u0026sort=date\u0026display_name=tag\u0026style=for-the-badge\u0026label=Latest%20Version\" alt=\"GitHub Release\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003c/p\u003e\n\n\u003cp\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"https://www.codefactor.io/repository/github/darsan-in/Pixteroid/issues/main\"\u003e\n    \u003cimg src=\"https://img.shields.io/codefactor/grade/github/darsan-in/Pixteroid?style=for-the-badge\u0026label=Code%20Quality%20Grade\" alt=\"CodeFactor Grade\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003c/p\u003e\n\n---\n\n\u003cp\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"\"\u003e\n    \u003cimg src=\"https://img.shields.io/npm/d18m/pixteroid?style=for-the-badge\u0026label=Downloads%20On%20NPM\" alt=\"NPM Downloads\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003ca href=\"\"\u003e\n    \u003cimg src=\"https://img.shields.io/github/stars/darsan-in/Pixteroid?style=for-the-badge\u0026label=Stars\" alt=\"GitHub Repo stars\"/\u003e\n  \u003c/a\u003e\n\u003c/span\u003e\n\n\u003c/p\u003e\n\n\n---\n\n\u003c/div\u003e\n\n## Table of Contents 📝\n\n- [Features and Benefits](#features-and-benefits-)\n- [Use Cases](#use-cases-)\n- [Friendly request to users](#-friendly-request-to-users)\n\n- [Installation - Step-by-Step Guide](#installation---step-by-step-guide-)\n- [Usage](#usage)\n- [In-Action](#in-action-)\n\n- [License](#license-%EF%B8%8F)\n- [Contributing to Our Project](#contributing-to-our-project-)\n- [Website](#website-)\n\n- [Contact Information](#contact-information)\n- [Credits](#credits-)\n\n## Features and Benefits ✨\n\n* **AI-Powered Upscaling and Restoration**: Leverages AI-powered Real-ESRGAN and ESRGAN models to upscale and restore images with enhanced quality.\n* **Multiple Detail Levels**: Offers three levels of detail to cater to different use cases, from quick previews to high-resolution prints.\n* **Custom Size Scaling**: Supports custom size scaling to fit specific dimensions while preserving image quality.\n* **Efficient Performance**: Built on the NCNN framework, ensuring optimized performance across different platforms.\n* **Simple Integration**: Easily integrate into any Node.js project with straightforward API calls.\n* **Open Source**: Fully open-source, with ongoing updates and community contributions.\n\n## Use Cases ✅\n* **Graphic Design**: Enhance and restore low-resolution images for use in high-quality designs.\n* **E-commerce**: Automatically upscale and restore product images for better visual appeal.\n* **Print Media**: Prepare and restore images for print without losing detail, even from smaller sources.\n* **AI Research**: Utilize advanced upscaling and restoration models for experimental and research purposes.\n* **Web Development**: Improve and restore image quality on websites with minimal load time impact.\n* **Photography**: Restore and enhance old or low-resolution photographs.\n\n---\n\n### 🙏🏻 Friendly Request to Users\n\nEvery star on this repository is a sign of encouragement, a vote of confidence, and a reminder that our work is making a difference. If this project has brought value to you, even in the smallest way, **please consider showing your support by giving it a star.** ⭐\n\n_\"Star\" button located at the top-right of the page, near the repository name._\n\nYour star isn’t just a digital icon—it’s a beacon that tells us we're on the right path, that our efforts are appreciated, and that this work matters. It fuels our passion and drives us to keep improving, building, and sharing.\n\nIf you believe in what we’re doing, **please share this project with others who might find it helpful.** Together, we can create something truly meaningful.\n\nThank you for being part of this journey. Your support means the world to us. 🌍💖\n\n---\n\n## Installation - Step-by-Step Guide 🪜\n\n- **Step 1:** Install using npm.\n```bash\nnpm install pixteroid\n```\n- **Step 2:** Follow Demo repository - [pixteroid-demo](https://github.com/darsan-in/pixteroid-demo)\n\n## Usage\n#### Upscale single image at a time.\n```js\nconst { upscale } = require(\"pixteroid\");\nconst { join, relative } = require(\"path\");\n\nconst imagePath = \"image-samples/0200.png\";\nconst outputPath = join(\"single-output\", relative(process.cwd(), imagePath));\nconst level = \"level1\"; //level1 or level2 or level3 - low to higher level\n\nupscale(imagePath, outputPath, level)\n  .then(() =\u003e {\n    console.log(\"done\");\n  })\n  .catch((err) =\u003e {\n    console.log(err);\n  });\n```\n\n#### Upscale multiple images asynchronously.\n```js\nconst { globSync } = require(\"glob\");\nconst { upscaleAll } = require(\"pixteroid\");\n\n/* only 50 samples taken by slicing */\nconst imagePaths = globSync(\"image-samples/**.jpg\").slice(0, 50);\nconst destinationPath = \"output-samples\";\nconst level = \"level1\"; //level1 or level2 or level3 - low to higher level\nconst batchSize = 2; //This is optional parameter def=2\n\nupscaleAll(imagePaths, destinationPath, level, batchSize)\n  .then(() =\u003e {\n    console.log(\"done\");\n  })\n  .catch((err) =\u003e {\n    console.log(err);\n  });\n```\n\n\n## In-Action 🤺\n\n![pixteroid result 1](in-action/result-1.png)\n![pixteroid result 2](in-action/result-2.png)\n![pixteroid result 3](in-action/result-3.png)\n\n## License ©️\n\nThis project is licensed under the [Apache License 2.0](LICENSE).\n\n## Contributing to Our Project 🤝\n\nWe’re always open to contributions and fixing issues—your help makes this project better for everyone.\n\nIf you encounter any errors or issues, please don’t hesitate to [raise an issue](../../issues/new). This ensures we can address problems quickly and improve the project.\n\nFor those who want to contribute, we kindly ask you to review our [Contribution Guidelines](CONTRIBUTING) before getting started. This helps ensure that all contributions align with the project's direction and comply with our existing [license](LICENSE).\n\nWe deeply appreciate everyone who contributes or raises issues—your efforts are crucial to building a stronger community. Together, we can create something truly impactful.\n\nThank you for being part of this journey!\n\n## Website 🌐\n\n\u003ca id=\"url\" href=\"https://www.npmjs.com/package/pixteroid\"\u003enpmjs - pixteroid\u003c/a\u003e\n\n## Contact Information\n\nFor any questions, please reach out via hello@darsan.in or [LinkedIn](https://www.linkedin.com/in/darsan-in/).\n\n## Credits 🙏🏻\n\nI would like to extend our gratitude to [Xintao](https://github.com/xinntao) for implementing Real-ESRGAN with the NCNN framework. Special thanks to Tencent for creating the NCNN framework, a high-performance neural network inference computing framework optimized for mobile platforms. NCNN is designed with mobile deployment in mind, is cross-platform, and runs faster than all known open-source frameworks on mobile CPUs. It is currently used in various Tencent applications, such as QQ, Qzone, WeChat, and Pitu.\n\n---\n\n\u003cp align=\"center\"\u003e\n\n\u003cspan\u003e\n\u003ca href=\"https://www.linkedin.com/in/darsan-in/\"\u003e\u003cimg width='45px' height='45px' src=\"https://darsan.in/readme-src/footer-icons/linkedin.png\" alt=\"Darsan at Linkedin\"\u003e\u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003cimg width='20px' height='20px' src=\"https://darsan.in/readme-src/footer-icons/gap.png\" alt=\"place holder image\"\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n\u003ca href=\"https://www.youtube.com/@darsan-in\"\u003e\u003cimg width='45px' height='45px' src=\"https://darsan.in/readme-src/footer-icons/youtube.png\" alt=\"Darsan at Youtube\"\u003e\u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003cimg width='20px' height='20px' src=\"https://darsan.in/readme-src/footer-icons/gap.png\" alt=\"place holder image\"\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n\u003ca href=\"https://www.npmjs.com/~darsan.in\"\u003e\u003cimg width='45px' height='45px' src=\"https://darsan.in/readme-src/footer-icons/npm.png\" alt=\"Darsan at NPM\"\u003e\u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003cimg width='20px' height='20px' src=\"https://darsan.in/readme-src/footer-icons/gap.png\" alt=\"place holder image\"\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n\u003ca href=\"https://github.com/darsan-in\"\u003e\u003cimg width='45px' height='45px' src=\"https://darsan.in/readme-src/footer-icons/github.png\" alt=\"Darsan at Github\"\u003e\u003c/a\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n  \u003cimg width='20px' height='20px' src=\"https://darsan.in/readme-src/footer-icons/gap.png\" alt=\"place holder image\"\u003e\n\u003c/span\u003e\n\n\u003cspan\u003e\n\u003ca href=\"https://darsan.in/\"\u003e\u003cimg width='45px' height='45px' src=\"https://darsan.in/readme-src/footer-icons/website.png\" alt=\"Darsan Website\"\u003e\u003c/a\u003e\n\u003c/span\u003e\n\n\u003cp\u003e\n\n---\n\n#### Topics\n\n\u003cul id=\"keywords\"\u003e\n\u003cli\u003eimage upscaling\u003c/li\u003e\n\u003cli\u003eimage restoration\u003c/li\u003e\n\u003cli\u003eAI-powered\u003c/li\u003e\n\u003cli\u003eNode.js image API\u003c/li\u003e\n\u003cli\u003eNCNN framework\u003c/li\u003e\n\u003cli\u003eReal-ESRGAN\u003c/li\u003e\n\u003cli\u003eESRGAN\u003c/li\u003e\n\u003cli\u003ehigh-resolution images\u003c/li\u003e\n\u003cli\u003eAI image processing\u003c/li\u003e\n\u003cli\u003edetail enhancement\u003c/li\u003e\n\u003cli\u003ecustom image scaling\u003c/li\u003e\n\u003cli\u003eopen-source\u003c/li\u003e\n\u003cli\u003egraphic design tools\u003c/li\u003e\n\u003cli\u003ee-commerce tools\u003c/li\u003e\n\u003cli\u003eweb development\u003c/li\u003e\n\u003cli\u003ephotography enhancement\u003c/li\u003e\n\u003cli\u003eprint media\u003c/li\u003e\n\u003cli\u003eimage quality\u003c/li\u003e\n\u003cli\u003escaling algorithms\u003c/li\u003e\n\u003cli\u003eperformance optimization\u003c/li\u003e\n\u003c/ul\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdarsan-in%2Fpixteroid","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdarsan-in%2Fpixteroid","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdarsan-in%2Fpixteroid/lists"}