{"id":18497069,"url":"https://github.com/jakubvojvoda/bayes-classifier","last_synced_at":"2025-05-14T04:37:01.574Z","repository":{"id":109048178,"uuid":"68550931","full_name":"JakubVojvoda/bayes-classifier","owner":"JakubVojvoda","description":"Binary classification of images using Bayes classifier","archived":false,"fork":false,"pushed_at":"2016-09-22T11:43:57.000Z","size":44,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-12-25T17:29:51.098Z","etag":null,"topics":["bayes-classifier","bayesian-classifier","bmp","classification","cpp","cross-validation","evaluation","image-processing","machine-learning"],"latest_commit_sha":null,"homepage":null,"language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"lgpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/JakubVojvoda.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":"2016-09-18T22:34:44.000Z","updated_at":"2023-12-04T15:33:49.000Z","dependencies_parsed_at":"2023-04-04T05:14:23.035Z","dependency_job_id":null,"html_url":"https://github.com/JakubVojvoda/bayes-classifier","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JakubVojvoda%2Fbayes-classifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JakubVojvoda%2Fbayes-classifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JakubVojvoda%2Fbayes-classifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JakubVojvoda%2Fbayes-classifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/JakubVojvoda","download_url":"https://codeload.github.com/JakubVojvoda/bayes-classifier/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239212615,"owners_count":19600844,"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":["bayes-classifier","bayesian-classifier","bmp","classification","cpp","cross-validation","evaluation","image-processing","machine-learning"],"created_at":"2024-11-06T13:33:16.090Z","updated_at":"2025-02-17T00:18:10.180Z","avatar_url":"https://github.com/JakubVojvoda.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Bayes classifier\nBinary classification of images using Bayes classifier\n\n### Usage\nThere are defined 3 usage cases\n\n1. Evaluate trained classifier on the test set \n * `./bayes --evaluate --test p1.txt n1.txt --train p2.txt n2.txt --threshold NUM [...]` \n2. Get table which contains precision and recall for possible threshold values (computed using cross-validation) \n * `./bayes --analyze --train pos.txt neg.txt [--q 2^NUM] [--method BAYESIAN_RGB | --method BAYESIAN_R] [--subsample]`\n3. Calculate a probability for image `img.bmp` (only .bmp format supported)\n * `./bayes --predict --train pos.txt neg.txt --image img.bmp [--q 2^NUM] [--method BAYESIAN_RGB | --method BAYESIAN_R] [--subsample]`\n\n### Command line arguments\nRun `./bayes VARIANT INPUT OPTIONAL` where\n\n* `VARIANT`\n * `--evaluate`: evaluation of implemented method\n * `--analyze`: show table of rates for training samples \n * `--predict`: predict probability for sample using defined threshold\n\n* `INPUT`\n * `--test positive.txt negative.txt`\n * `--train positive.txt negative.txt`\n\n* `OPTIONAL`\n * `--method`: possible values `BAYESIAN_R` or `BAYESIAN_RGB` (default is `BAYESIAN_RGB`)\n * `--q NUM`: change size of histogram dimensions (default 16)\n * `--subsample`: subsample images to descrease exec time (default not use)\n\n### Examples\n\n* `./bayes --evaluate --threshold 0.37 --subsample`\n* `./bayes --evaluate --train p1.txt n1.txt --test p2.txt n2.txt --threshold 0.34`\n* `./bayes --analyze --train p.txt n.txt`\n* `./bayes --train p1.txt n1.txt --test --image img.bmp`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjakubvojvoda%2Fbayes-classifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjakubvojvoda%2Fbayes-classifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjakubvojvoda%2Fbayes-classifier/lists"}