{"id":29272027,"url":"https://github.com/bukalapak/pybrisque","last_synced_at":"2025-07-05T00:10:25.224Z","repository":{"id":32835791,"uuid":"143156668","full_name":"bukalapak/pybrisque","owner":"bukalapak","description":"A python implementation of BRISQUE Image Quality Assessment","archived":false,"fork":false,"pushed_at":"2022-05-13T18:26:58.000Z","size":700,"stargazers_count":239,"open_issues_count":13,"forks_count":48,"subscribers_count":286,"default_branch":"master","last_synced_at":"2025-06-10T09:19:12.206Z","etag":null,"topics":["brisque","computer-vision","image-processing","image-quality-assessment","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bukalapak.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}},"created_at":"2018-08-01T13:01:03.000Z","updated_at":"2025-05-15T06:58:26.000Z","dependencies_parsed_at":"2022-08-09T03:30:24.418Z","dependency_job_id":null,"html_url":"https://github.com/bukalapak/pybrisque","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/bukalapak/pybrisque","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bukalapak%2Fpybrisque","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bukalapak%2Fpybrisque/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bukalapak%2Fpybrisque/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bukalapak%2Fpybrisque/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bukalapak","download_url":"https://codeload.github.com/bukalapak/pybrisque/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bukalapak%2Fpybrisque/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263636825,"owners_count":23492312,"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":["brisque","computer-vision","image-processing","image-quality-assessment","python"],"created_at":"2025-07-05T00:10:24.582Z","updated_at":"2025-07-05T00:10:25.213Z","avatar_url":"https://github.com/bukalapak.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# PyBRISQUE\nAn implementation of BRISQUE (Blind/Referenceless Image Spatial Quality \nEvaluator) in Python from the paper: [\"No-Reference Image Quality Assessment \nin the Spatial Domain\"](https://ieeexplore.ieee.org/document/6272356/).\n\n\n## Installation\nLibSVM is required. On ubuntu or other debian-based system, you can install ```libsvm-dev``` package from apt as follows:\n\n```apt-get install libsvm-dev```\n\nThe package is in PyPI so you can install it simply by this command:\n\n```pip install --process-dependency-links pybrisque```\n\n## Usage\nInitialize once:\n```\nbrisq = BRISQUE()\n```\nand get the BRISQUE feature or score many times:\n```\nbrisq.get_feature('/path')\nbrisq.get_score('/image_path')\n```\n\n\n## Limitations\nThis implementation is heavily adopted from the original Matlab \nimplementation in [here](https://github.com/dsoellinger/blind_image_quality_toolbox/tree/master/%2Bbrisque). There is one catch though, the bicubic interpolation when resizing image in \nMatlab and OpenCV is a bit different as explained in [here](https://stackoverflow.com/questions/26823140/imresize-trying-to-understand-the-bicubic-interpolation). For now, it uses ```nearest``` interpolation \nwhich gives the most similar output with the original implementation.\n\nComparing with Matlab original implementation on reference images of TID 2008: \n\n![Comparison](examples/comparison.png)\n \nAnd the absolute differences' stat is as follows: \n```\n{'min': 0.17222238726479588,\n 'max': 16.544924728934404,\n 'mean': 3.9994322498322754,\n 'std': 3.0715344507521416}\n```\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbukalapak%2Fpybrisque","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbukalapak%2Fpybrisque","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbukalapak%2Fpybrisque/lists"}