{"id":20409650,"url":"https://github.com/tayyabwaqar/webcam-image-object-detector","last_synced_at":"2026-06-11T09:31:37.234Z","repository":{"id":262507667,"uuid":"850001685","full_name":"tayyabwaqar/webcam-image-object-detector","owner":"tayyabwaqar","description":"This app, built with Streamlit and YOLOv8, is designed for real-time object detection in images and video streams. It can identify and label various objects in both uploaded images and live webcam feeds.","archived":false,"fork":false,"pushed_at":"2024-11-12T19:22:16.000Z","size":5885,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-05T02:42:56.956Z","etag":null,"topics":["computer-vision","image","image-classification","object-detection","webcam"],"latest_commit_sha":null,"homepage":"https://detectifyai.streamlit.app/","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/tayyabwaqar.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":"2024-08-30T17:14:54.000Z","updated_at":"2024-11-12T19:22:19.000Z","dependencies_parsed_at":"2024-11-12T20:35:21.297Z","dependency_job_id":null,"html_url":"https://github.com/tayyabwaqar/webcam-image-object-detector","commit_stats":null,"previous_names":["tayyabwaqar/webcam-image-object-detector"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/tayyabwaqar/webcam-image-object-detector","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tayyabwaqar%2Fwebcam-image-object-detector","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tayyabwaqar%2Fwebcam-image-object-detector/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tayyabwaqar%2Fwebcam-image-object-detector/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tayyabwaqar%2Fwebcam-image-object-detector/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tayyabwaqar","download_url":"https://codeload.github.com/tayyabwaqar/webcam-image-object-detector/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tayyabwaqar%2Fwebcam-image-object-detector/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34192870,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-11T02:00:06.485Z","response_time":57,"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":["computer-vision","image","image-classification","object-detection","webcam"],"created_at":"2024-11-15T05:42:50.944Z","updated_at":"2026-06-11T09:31:37.206Z","avatar_url":"https://github.com/tayyabwaqar.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI-Powered Object Detection App\n\n## Overview\n\nThe **AI-Powered Object Detection App** is a web application built with Streamlit and YOLO, designed for real-time object detection in images and video streams. This app leverages AI technology to identify and label various objects in both uploaded images and live webcam feeds.\n\n## Live Demo\n\nYou can try the live demo of the application at the following link: \n[Live Demo - Detectify](https://detectifyai.streamlit.app/)\n\n## Key Features\n\n- **Real-Time Detection**: Utilize your webcam to detect and classify objects in real-time, with instant feedback on detected items.\n- **Image Upload**: Easily upload images to perform object detection, with results displayed alongside the original image.\n- **Customizable Settings**: Adjust the confidence threshold and select specific object classes to tailor detection to your needs.\n- **Interactive Interface**: A clean and intuitive user interface that allows for seamless interaction and visualization of detection results.\n- **Detection Summary Table**: View a summary of detected objects, including counts for each type, presented in a neatly formatted table.\n\n## Technologies Used\n\n- **Streamlit**: For creating the interactive web interface.\n- **OpenCV**: For image processing and handling webcam input.\n- **YOLOv8**: For advanced object detection capabilities.\n- **Pandas**: For creating and manipulating the detection summary dataframe.\n- **streamlit-webrtc**: For handling real-time video streaming from the webcam.\n\n## Installation\n\nTo run the app locally, clone the repository and install the required dependencies:\n\n```bash\ngit clone https://github.com/tayyabwaqar/webcam-image-object-detector\ncd \u003crepository-directory\u003e\npip install -r requirements.txt\nstreamlit run app.py\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftayyabwaqar%2Fwebcam-image-object-detector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftayyabwaqar%2Fwebcam-image-object-detector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftayyabwaqar%2Fwebcam-image-object-detector/lists"}