{"id":23406919,"url":"https://github.com/bee1997/people-counting-in-out","last_synced_at":"2026-04-29T00:34:16.599Z","repository":{"id":269276983,"uuid":"906929086","full_name":"Bee1997/People-Counting-In-Out","owner":"Bee1997","description":"People Counting System that tracks and counts individuals entering and exiting a predefined region","archived":false,"fork":false,"pushed_at":"2024-12-22T10:57:21.000Z","size":9808,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-09T00:07:12.598Z","etag":null,"topics":["computer-vision","machine-learning","opencv","yolo11"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Bee1997.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2024-12-22T10:38:24.000Z","updated_at":"2025-03-04T06:29:21.000Z","dependencies_parsed_at":"2024-12-22T11:35:26.340Z","dependency_job_id":"45dcde64-0240-4c91-aaa1-63d9ffc2aab4","html_url":"https://github.com/Bee1997/People-Counting-In-Out","commit_stats":null,"previous_names":["bee1997/people-counting-in-out"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bee1997%2FPeople-Counting-In-Out","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bee1997%2FPeople-Counting-In-Out/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bee1997%2FPeople-Counting-In-Out/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Bee1997%2FPeople-Counting-In-Out/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Bee1997","download_url":"https://codeload.github.com/Bee1997/People-Counting-In-Out/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247947860,"owners_count":21023066,"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","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","machine-learning","opencv","yolo11"],"created_at":"2024-12-22T14:16:17.666Z","updated_at":"2026-04-29T00:34:16.556Z","avatar_url":"https://github.com/Bee1997.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# People-Counting-In-Out\n\nThis project implements a **People Counting System** that tracks and counts individuals entering and exiting a predefined region in a video. It uses **Ultralytics' Object Counter solution** with a YOLO model (`yolo11n.pt`). The system is ideal for applications in malls, offices, hospitals, and other facilities where monitoring foot traffic is essential.\n\n## Key Features\n\n- **Real-Time People Counting**: Tracks and counts people crossing a designated region in the video, providing separate counts for \"In\" and \"Out\" movements.\n- **Region-Based Tracking**: Supports rectangular regions for monitoring specific areas.\n- **Annotated Video Output**: Saves the output video with annotated bounding boxes, region markers, and counts.\n- **Performance**: Processes each frame in approximately **~200ms**, including:\n  - Reading the video frame\n  - Object detection\n  - Tracking and counting objects crossing the region\n  - Annotating the frame and writing to the output video\n\n## Applications\n\n- **Malls**: Monitor customer foot traffic for better management and analysis.\n- **Offices**: Track employee or visitor flow for security and resource allocation.\n- **Hospitals**: Count individuals entering and exiting specific zones for efficient crowd management.\n\n## System Performance\n\n- **Average Processing Time**: ~200ms per frame (includes frame reading, detection, tracking, counting, annotation, and writing output).\n- **System Specs**:\n  - Processor: Intel Core i5-6300U @ 2.40GHz\n  - RAM: 8GB\n  - **No GPU** was used for this project.\n\n## Example Output\n\nHere is a snapshot from the annotated output video:\n\n![Annotated Video Output](demo_out.gif)\n\nThe annotated video shows the bounding boxes, counts, and the designated region for tracking.\n\n## Prerequisites\n\n- Python 3.x\n- Video file (`demo.mp4`) for processing.\n- Custom YOLO model file (`yolo11n.pt`).\n\n## Setup\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/your-username/people-counting.git\n   cd people-counting\n   ```\n2. Install the required dependencies:\n```bash\n  pip install -r requirements.txt\n```\n3. Add the input video file (demo.mp4) to the repository.\n4. Ensure the custom YOLO model file (yolo11n.pt) is in the correct location.\n\n## Running the Code\n\nTo process the video and generate the output:\n```bash\n  python run.py\n```\n### Output\n- Annotated Video: The processed video will be saved as demo_out.avi.\n- Processing Time: Average processing time per frame is printed in the terminal after execution.\n\n## Future Enhancements\n- Real-Time Processing: Integrate with live camera feeds for real-time counting.\n- Improved Performance: Optimize processing time for faster frame rates.\n- Multi-Region Tracking: Extend support for monitoring multiple regions simultaneously.\n- Data Analytics: Log and analyze traffic data for insights and predictions.\n\n## Acknowledgments\nThis project uses:\n- Ultralytics Solutions for object detection and tracking.\n- OpenCV for video processing\n\n## Contact\nFor questions or contributions, feel free to contact me or open an issue in the repository.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbee1997%2Fpeople-counting-in-out","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbee1997%2Fpeople-counting-in-out","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbee1997%2Fpeople-counting-in-out/lists"}