{"id":30842840,"url":"https://github.com/nusu-github/imageops-kit","last_synced_at":"2025-09-06T21:11:11.758Z","repository":{"id":299196945,"uuid":"1001570738","full_name":"nusu-github/imageops-kit","owner":"nusu-github","description":null,"archived":false,"fork":false,"pushed_at":"2025-09-05T06:42:42.000Z","size":268,"stargazers_count":0,"open_issues_count":10,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-09-05T08:31:15.157Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Rust","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/nusu-github.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE-APACHE","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,"zenodo":null}},"created_at":"2025-06-13T15:57:20.000Z","updated_at":"2025-07-13T17:47:28.000Z","dependencies_parsed_at":"2025-06-15T09:30:33.947Z","dependency_job_id":"49055ce0-6673-40e5-aec2-7738b2fa886f","html_url":"https://github.com/nusu-github/imageops-kit","commit_stats":null,"previous_names":["nusu-github/imageops-ai","nusu-github/imageops-kit"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/nusu-github/imageops-kit","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nusu-github%2Fimageops-kit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nusu-github%2Fimageops-kit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nusu-github%2Fimageops-kit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nusu-github%2Fimageops-kit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nusu-github","download_url":"https://codeload.github.com/nusu-github/imageops-kit/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nusu-github%2Fimageops-kit/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273962606,"owners_count":25198600,"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","status":"online","status_checked_at":"2025-09-06T02:00:13.247Z","response_time":2576,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2025-09-06T21:11:10.623Z","updated_at":"2025-09-06T21:11:11.739Z","avatar_url":"https://github.com/nusu-github.png","language":"Rust","readme":"# imageops-kit\n\nA Rust library for image processing operations and utilities.\n\n[![Crates.io](https://img.shields.io/crates/v/imageops-kit.svg)](https://crates.io/crates/imageops-kit)\n[![Documentation](https://docs.rs/imageops-kit/badge.svg)](https://docs.rs/imageops-kit)\n[![License](https://img.shields.io/badge/license-Apache--2.0-blue.svg)](LICENSE-APACHE)\n[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE-MIT)\n\n## Overview\n\nThis crate provides a collection of image processing operations and utilities.\n\n### Key Features\n\n- **Alpha Pre-multiplication**: Premultiplies alpha values across color channels\n- **Alpha Mask Application**: Applies a grayscale mask to an RGB image to generate an RGBA image\n- **Blur-Fusion Foreground Estimation**: Estimates the foreground using the Blur-Fusion algorithm\n- **Boundary Clipping**: Automatically detects and clips to the minimum boundary\n- **Padding**: Smart padding at various positions\n- **NL-Means Denoising**: Noise reduction utilizing similarity between neighboring pixels\n- **One-Sided Box Filter**: Edge-preserving smoothing filter for image denoising\n- **INTER_AREA Resize**: High-quality image downscaling using OpenCV's INTER_AREA algorithm\n\n## Usage Example\n\n```rust\nuse imageops_kit::{PremultiplyAlphaAndDropExt, ApplyAlphaMaskExt, PaddingExt, Position, OneSidedBoxFilterExt, InterAreaResizeExt};\nuse imageproc::definitions::Image;\nuse image::{Rgb, Rgba, Luma};\n\n# fn example() -\u003e Result\u003c(), Box\u003cdyn std::error.Error\u003e\u003e {\n// Premultiplied conversion from RGBA to RGB image\nlet rgba_image: Image\u003cRgba\u003cu8\u003e\u003e = Image::new(100, 100);\nlet rgb_image = rgba_image.premultiply_alpha_and_drop()?;\n\n// Apply alpha mask to RGB image\nlet rgb_image: Image\u003cRgb\u003cu8\u003e\u003e = Image::new(100, 100);\nlet mask: Image\u003cLuma\u003cu8\u003e\u003e = Image::new(100, 100);\nlet rgba_result = rgb_image.apply_alpha_mask(\u0026mask)?;\n\n// One-Sided Box Filter for edge-preserving smoothing\nlet image: Image\u003cRgb\u003cu8\u003e\u003e = Image::new(100, 100);\nlet smoothed = image.one_sided_box_filter(2, 5)?; // radius=2, iterations=5\n\n// INTER_AREA resize for high-quality downscaling\nlet image: Image\u003cRgb\u003cu8\u003e\u003e = Image::new(100, 100);\nlet resized = image.resize_area(50, 50)?;\n\n// Image padding\nlet image: Image\u003cRgb\u003cu8\u003e\u003e = Image::new(50, 50);\nlet (padded, position) = image.add_padding(\n    (100, 100),\n    Position::Center,\n    Rgb([255, 255, 255])\n)?;\n# Ok(())\n# }\n```\n\n## Installation\n\nAdd the following to your `Cargo.toml`:\n\n```toml\n[dependencies]\nimageops-kit = \"0.1\"\n```\n\n## Documentation\n\nFor detailed API specifications, see [docs.rs](https://docs.rs/imageops-kit).\n\n## References\n\n- **Blur-Fusion**: A. Germer, \"Approximate Fast Foreground Colour Estimation,\" ICIP 2021.\n\n## Contribution\n\nWe welcome bug reports and pull requests. Please contact us via\nthe [issue tracker](https://github.com/nusu-github/imageops-kit/issues) on GitHub.\n\n## License\n\nThis project is published under the MIT or Apache-2.0 license.","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnusu-github%2Fimageops-kit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnusu-github%2Fimageops-kit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnusu-github%2Fimageops-kit/lists"}