{"id":20380825,"url":"https://github.com/docsallover/helmet-and-plate-detection","last_synced_at":"2026-02-13T20:05:46.433Z","repository":{"id":216799475,"uuid":"742377080","full_name":"docsallover/helmet-and-plate-detection","owner":"docsallover","description":"Helmet and Number Plate Detection using YOLOv3 with opencv and python","archived":false,"fork":false,"pushed_at":"2025-01-01T08:31:35.000Z","size":16,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-01T09:23:12.216Z","etag":null,"topics":["data-science","detection","jupyter-notebook","machine-learning","numpy","opencv","python","tenserflow","yolo","yolov3"],"latest_commit_sha":null,"homepage":"https://docsallover.com/blog/data-science/helmet-and-number-plate-detection/","language":"Jupyter Notebook","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/docsallover.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":"2024-01-12T10:40:51.000Z","updated_at":"2025-01-01T08:31:39.000Z","dependencies_parsed_at":"2025-01-01T09:21:01.005Z","dependency_job_id":null,"html_url":"https://github.com/docsallover/helmet-and-plate-detection","commit_stats":null,"previous_names":["docsallover/helmet-and-plate-detection"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docsallover%2Fhelmet-and-plate-detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docsallover%2Fhelmet-and-plate-detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docsallover%2Fhelmet-and-plate-detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/docsallover%2Fhelmet-and-plate-detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/docsallover","download_url":"https://codeload.github.com/docsallover/helmet-and-plate-detection/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234001675,"owners_count":18764310,"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":["data-science","detection","jupyter-notebook","machine-learning","numpy","opencv","python","tenserflow","yolo","yolov3"],"created_at":"2024-11-15T02:09:15.097Z","updated_at":"2025-09-23T21:31:41.811Z","avatar_url":"https://github.com/docsallover.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Helmet and Number Plate Detection using YOLOv3 with OpenCV and Python\n\nThis project demonstrates the use of YOLOv3, a state-of-the-art object detection model, in conjunction with OpenCV and Python to detect helmets and number plates within images or videos.\n\n## Overview\nThe system leverages the power of YOLOv3, a convolutional neural network (CNN) architecture known for its speed and accuracy, to identify and localize helmets and number plates within visual data. OpenCV, a popular computer vision library, is employed for image processing tasks and integration with the YOLOv3 model.\n\nThe system consists of four main components:\n\n1. Real-time Detection: YOLOv3's efficiency enables near real-time processing of images and videos, making it suitable for applications requiring immediate detection.\n\n2. Customizable Model: The YOLOv3 model can be trained on custom datasets to detect objects beyond helmets and number plates, adapting it to specific use cases.\n\n3. Accuracy and Precision: YOLOv3 exhibits high accuracy and precision in object detection tasks, ensuring reliable identification of helmets and number plates.\n\n4. Integration with OpenCV: Seamless integration with OpenCV facilitates image preprocessing, visualization, and other computer vision operations.\n\n## How to Use\nTo use the system, follow these steps:\n1. Clone the repository.\n2. Create a virtual environment (venv or virtualenv) in the project directory.\n3. Activate the virtual environment.\n4. Install the required dependencies.\n   - Run `pip install -r requirements.txt`.\n5. Run the `detect.py` file to execute the system.\n   - If you are using Python 3, you can run `python detect.py`.\n6. Alternatively, you can run the `helmet.ipynb` notebook file in Jupyter Notebook/JupyterLab.\n7. Prepare Data: Ensure you have a dataset containing images or videos with annotated helmets and number plates.\n8. Train the Model (Optional): If you need to customize the model for your specific dataset, follow the provided training instructions.\n9. Run the Detection System: Execute the Python script (e.g., `detection.py`) to process images or videos.\n10. The script will display the detected helmets and number plates along with bounding boxes and labels.\n\n\nNote: The system is provided in both `.py` and `.ipynb` file formats.\n\n## Dependencies\nThe system requires the following dependencies:\n- OpenCV\n- TensorFlow/Keras\n- NumPy\n- imutils\n\n## License\nThis project is licensed under the MIT License. See the LICENSE file for more details.\n\n\n## Visit and Follow\nFor more details and tutorials, visit the website: [DocsAllOver](https://docsallover.com/).\n\nFollow us on:\n- [Facebook](https://www.facebook.com/docsallover)\n- [Instagram](https://www.instagram.com/docsallover.tech/)\n- [X.com](https://www.x.com/docsallover/)\n- [LinkedIn](https://www.linkedin.com/company/docsallover/)\n- [YouTube](https://www.youtube.com/@docsallover)\n- [Threads.net](https://threads.net/docsallover.tech)\n\nand visit our website to know more about our tutorials and blogs.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdocsallover%2Fhelmet-and-plate-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdocsallover%2Fhelmet-and-plate-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdocsallover%2Fhelmet-and-plate-detection/lists"}