{"id":22942055,"url":"https://github.com/rishic3/strepdetection","last_synced_at":"2026-05-03T06:35:40.874Z","repository":{"id":210278806,"uuid":"726184755","full_name":"rishic3/StrepDetection","owner":"rishic3","description":"An interpretable deep learning approach to detect strep throat directly from cell phone videos.","archived":false,"fork":false,"pushed_at":"2025-01-16T19:19:37.000Z","size":73715,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-01T21:18:08.240Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","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/rishic3.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-12-01T18:04:10.000Z","updated_at":"2025-01-16T19:19:39.000Z","dependencies_parsed_at":"2023-12-08T02:30:02.701Z","dependency_job_id":"1afb8c96-280b-477c-92cf-2324b804c2d5","html_url":"https://github.com/rishic3/StrepDetection","commit_stats":null,"previous_names":["rishic3/strepdetection"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/rishic3/StrepDetection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishic3%2FStrepDetection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishic3%2FStrepDetection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishic3%2FStrepDetection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishic3%2FStrepDetection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rishic3","download_url":"https://codeload.github.com/rishic3/StrepDetection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rishic3%2FStrepDetection/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32560782,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-03T03:21:47.309Z","status":"ssl_error","status_checked_at":"2026-05-03T03:21:43.884Z","response_time":103,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: 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":"2024-12-14T13:46:27.324Z","updated_at":"2026-05-03T06:35:40.844Z","avatar_url":"https://github.com/rishic3.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# StrepDetection\n\nDetection of strep throat directly from cell phone videos.  \nEmploying intermediate symptom classification combined with rule-based decisions for interpretable results.  \nImplementing strategies (hard-negative mining, contrastive learning) to combat limited and imbalanced data.  \n\n## Parsing data from CVAT:  \n\n1. Download data from CVAT\n   * `Actions \u003e Export Dataset \u003e Export Format: CVAT for video 1.1`.\n   * This will download a folder containing an xml file with the dataset annotations.\n3. Parse annotations via `parse_xml.py`  \n   * Set the xml file path and run `parse_xml.py`.\n   * This will produce a .csv file with the video, frame, and relevant labels.\n4. Merge CVAT data with .xlsx data\n   * Follow the steps in `data_process.ipynb`.\n   * This will merge the annotations from the `.xlsx` training review with the CVAT labels, checking for any overlap.\n\n## Model Checkpoints:\n[OneDrive folder](https://livejohnshopkins-my.sharepoint.com/:f:/g/personal/rchand18_jh_edu/Eqpi0aQnp_ZNmqp5sNe990EBUEEEuu3CyJAAGzhS831qXQ?e=kVGbqF) containing model checkpoints.  \n\nAuthored by Rishi Chandra, rchand18@jhu.edu, as part of the [ARCADE Lab](https://arcade.cs.jhu.edu/) at Johns Hopkins University. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frishic3%2Fstrepdetection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frishic3%2Fstrepdetection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frishic3%2Fstrepdetection/lists"}