{"id":19662561,"url":"https://github.com/gold-roger33/mini-project-yolo-object-detection","last_synced_at":"2026-05-19T10:05:01.657Z","repository":{"id":232757579,"uuid":"774516747","full_name":"gold-roger33/mini-project-yolo-object-detection","owner":"gold-roger33","description":"Object Detection System using Raspberry Pi and python","archived":false,"fork":false,"pushed_at":"2024-06-12T12:59:42.000Z","size":18782,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-27T03:26:08.797Z","etag":null,"topics":["python","raspberry-pi","ultralytics"],"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/gold-roger33.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":"2024-03-19T17:26:04.000Z","updated_at":"2024-06-12T12:59:45.000Z","dependencies_parsed_at":null,"dependency_job_id":"40cd9fcc-f293-4ac5-b574-3eebd63ddaff","html_url":"https://github.com/gold-roger33/mini-project-yolo-object-detection","commit_stats":null,"previous_names":["gold-roger33/mini-project-yolo-object-detection"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/gold-roger33/mini-project-yolo-object-detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gold-roger33%2Fmini-project-yolo-object-detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gold-roger33%2Fmini-project-yolo-object-detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gold-roger33%2Fmini-project-yolo-object-detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gold-roger33%2Fmini-project-yolo-object-detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gold-roger33","download_url":"https://codeload.github.com/gold-roger33/mini-project-yolo-object-detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gold-roger33%2Fmini-project-yolo-object-detection/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273699597,"owners_count":25152282,"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":"2025-09-04T02:00:08.968Z","response_time":61,"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":["python","raspberry-pi","ultralytics"],"created_at":"2024-11-11T16:11:46.756Z","updated_at":"2026-05-19T10:05:01.596Z","avatar_url":"https://github.com/gold-roger33.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Object Detection System for Visually Impaired: Raspberry Pi \u0026 Python(Mini Project)\n\nThis repository is the code for my  mini project that demonstrates real-time object detection using the YOLO (You Only Look Once) model in Raspberry Pi pi 4B.\nThe project is designed to assist the visually impaired by detecting and announcing objects in their surroundings.\n\n\n\n## Features\n\n- Real-time object detection using YOLO model\n- Video input from the camera module/webcam\n- Detection of various classes of objects\n- Announcement of detected objects and their positions using text-to-speech engine\n\n## Requirements\n\n- Python 3.12\n- ultralytics library\n- pyttsx3 library\n- Pre-trained YOLO model (yolov8n.pt)\n- camera module (you can use web camera)\n- Raspberry Pi (You can also run on PC)\n\n## Usage\n\n1. Clone the repository:\n\n    ```bash\n    git clone https://github.com/gold-roger33/mini-project-yolo-object-detection.git\n    ```\n\n2. Install the required libraries:\n\n    ```bash\n    pip install ultralytics pyttsx3\n    ```\n\n3. Run the main script:\n\n    ```bash\n    cd final code\n    python livecam.py\n    ```\n4. Point the camera module towards the surroundings and listen to the announcements of detected objects.\n\n\n## Additionals \n\nThere is a test folder which i used to test some features like detecting objects from video\n\n## credits\n\n- Ultralytics YOLO: [Documentation](https://docs.ultralytics.com/quickstart/)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgold-roger33%2Fmini-project-yolo-object-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgold-roger33%2Fmini-project-yolo-object-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgold-roger33%2Fmini-project-yolo-object-detection/lists"}