{"id":23944914,"url":"https://github.com/aysenurcftc/FastAPI-Flower-Classification","last_synced_at":"2025-09-12T03:31:26.442Z","repository":{"id":271122754,"uuid":"910809024","full_name":"aysenurcftc/FastAPI-Flower-Classification","owner":"aysenurcftc","description":"A FastAPI app for classifying flower images using a pre-trained Vision Transformer (ViT) model, containerized with Docker for easy deployment.","archived":false,"fork":false,"pushed_at":"2025-01-11T19:38:24.000Z","size":1893,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-14T06:33:53.772Z","etag":null,"topics":["classification","docker","fastapi","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/aysenurcftc.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":"2025-01-01T13:52:11.000Z","updated_at":"2025-01-11T19:40:21.000Z","dependencies_parsed_at":"2025-01-05T17:28:35.290Z","dependency_job_id":"d70e1535-5da1-4973-b61c-88d69836ff39","html_url":"https://github.com/aysenurcftc/FastAPI-Flower-Classification","commit_stats":null,"previous_names":["aysenurcftc/flower-classification","aysenurcftc/fastapi-flower-classification"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/aysenurcftc/FastAPI-Flower-Classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FFastAPI-Flower-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FFastAPI-Flower-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FFastAPI-Flower-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FFastAPI-Flower-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aysenurcftc","download_url":"https://codeload.github.com/aysenurcftc/FastAPI-Flower-Classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aysenurcftc%2FFastAPI-Flower-Classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":274748240,"owners_count":25341941,"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":"2025-09-12T02:00:09.324Z","response_time":60,"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":["classification","docker","fastapi","pytorch"],"created_at":"2025-01-06T07:16:36.131Z","updated_at":"2025-09-12T03:31:26.434Z","avatar_url":"https://github.com/aysenurcftc.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# FastAPI Flower Classification\n\nA FastAPI-based application that classifies flower images using a pre-trained Vision Transformer (ViT) model. The application provides an API for image classification and is containerized using Docker for easy deployment.\n\n\n## Installation\n\n\n```bash\n  git clone Flower-Classification\n  cd Flower-Classification\n```\n```bash\ndocker build -t flower-classification .\n\ndocker run -p 8000:8000 flower-classification\n\n```\n\nAccess the application at http://localhost:8000/\n\n\n\n    \n## Run Locally\nTo run the application locally without Docker, you can use uvicorn:\n\n```bash\n pip install -r requirements.txt\n```\n\n\n```bash\n  uvicorn app:app --reload\n```\n\n\n\n\n\n## Acknowledgements\n\n- Vision Transformer (ViT) for the pre-trained model.\n- FastAPI: for building fast APIs.\n- PyTorch: for providing the deep learning framework.\n- Docker: for containerizing the application.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faysenurcftc%2FFastAPI-Flower-Classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faysenurcftc%2FFastAPI-Flower-Classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faysenurcftc%2FFastAPI-Flower-Classification/lists"}