{"id":41838151,"url":"https://github.com/prp-e/chehro","last_synced_at":"2026-01-25T09:17:11.390Z","repository":{"id":62591909,"uuid":"498603211","full_name":"prp-e/chehro","owner":"prp-e","description":"A face detection library with mediapipe backend","archived":false,"fork":false,"pushed_at":"2022-06-01T06:12:53.000Z","size":32,"stargazers_count":19,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2026-01-05T03:25:36.617Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/prp-e.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-06-01T05:30:49.000Z","updated_at":"2025-07-09T00:14:07.000Z","dependencies_parsed_at":"2022-11-04T07:16:58.311Z","dependency_job_id":null,"html_url":"https://github.com/prp-e/chehro","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/prp-e/chehro","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prp-e%2Fchehro","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prp-e%2Fchehro/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prp-e%2Fchehro/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prp-e%2Fchehro/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/prp-e","download_url":"https://codeload.github.com/prp-e/chehro/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/prp-e%2Fchehro/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28750872,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-25T09:00:19.176Z","status":"ssl_error","status_checked_at":"2026-01-25T09:00:04.131Z","response_time":113,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":"2026-01-25T09:17:11.290Z","updated_at":"2026-01-25T09:17:11.365Z","avatar_url":"https://github.com/prp-e.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Chehro\n\nChehro is a face detection library for python with a _[mediapipe](https://google.github.io/mediapipe)_ backend. It is faster and more accurate comparing to the old _HAARCASCADE Classifier_ way of face detection in python/OpenCV. \n\n![Tested on a picture of Elon Musk](https://github.com/prp-e/chehro/raw/master/result.jpg)\n\n## Installation guide\n\n### From source\n\nFirst of all, you have to clone this repository to your local machine:\n\n```\ngit clone https://github.com/prp-e/chehro\n```\n\nThen, you move to the source directory and run:\n\n```\npip3 install -e .\n```\n\n_NOTE_: In some systems(specially Linux based ones) _pip3_ might be just _pip_, since most of moderl Linux distributions just left Python2 behind. \n\n### From PyPi\n\nIn case you want this package to be installed using _pip_ then just run this command:\n\n```\npip3 install chehro\n```\n\n_NOTE_: In some systems(specially Linux based ones) _pip3_ might be just _pip_, since most of moderl Linux distributions just left Python2 behind. \n\n## How to use\n\nFirst, create a new python environment or project. Then you easily can do this:\n\n```python\nimport cv2\nfrom chehro import Chehro\n\nimage = cv2.imread('faces.jpg')\ndetector = Chehro(image)\n\nresult, bboxes = detector.detect()\n\n# In case you might need no bounding box drawn around faces, just run it like this\nresult, bboxes = detector.detect(draw=False)\n```\n\n_NOTE_ : `detect()` method returns a tuple made of an image (or the result) and a list of bounding boxed. All bounding boxes are normalized and you don't need to normalize it manually.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprp-e%2Fchehro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprp-e%2Fchehro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprp-e%2Fchehro/lists"}