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https://github.com/ahmad-ali-rafique/yolo-helmet-detection-app
This project implements a helmet detection system using YOLOv3 (You Only Look Once) and Streamlit. The application allows users to upload an image and detect helmets in real-time. The system uses OpenCV and pre-trained YOLOv3 weights to identify helmets in uploaded images, displaying the results with bounding boxes and confidence scores.
https://github.com/ahmad-ali-rafique/yolo-helmet-detection-app
artificial-intelligence datascience deep-neural-networks helmet-detection image-processing machine-learning modeling opencv streamlit-dashboard yolov3
Last synced: about 2 months ago
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This project implements a helmet detection system using YOLOv3 (You Only Look Once) and Streamlit. The application allows users to upload an image and detect helmets in real-time. The system uses OpenCV and pre-trained YOLOv3 weights to identify helmets in uploaded images, displaying the results with bounding boxes and confidence scores.
- Host: GitHub
- URL: https://github.com/ahmad-ali-rafique/yolo-helmet-detection-app
- Owner: Ahmad-Ali-Rafique
- Created: 2024-08-24T11:52:05.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-08-26T13:05:51.000Z (4 months ago)
- Last Synced: 2024-08-26T15:25:05.772Z (4 months ago)
- Topics: artificial-intelligence, datascience, deep-neural-networks, helmet-detection, image-processing, machine-learning, modeling, opencv, streamlit-dashboard, yolov3
- Language: Python
- Homepage:
- Size: 10.1 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
## Ahmad Ali Rafique
I am an AI & Machine Learning Specialist with expertise in developing and deploying machine learning models for various applications. With a strong foundation in deep learning, computer vision, and data science, I am dedicated to building innovative solutions that address real-world challenges.
### Project Overview
This repository features a Streamlit-based application designed for real-time helmet detection using the YOLOv3 (You Only Look Once) model. The application provides an interactive interface where users can upload images to detect helmets and visualize detection results with bounding boxes and confidence scores.
### Key Features
- **Real-Time Detection:** The YOLOv3 model performs fast and accurate helmet detection in images.
- **User Interface:** Built with Streamlit to offer an easy-to-use interface for image uploads and results display.
- **Visual Feedback:** Provides immediate visual feedback with bounding boxes and confidence scores for detected helmets.
- **Personalized Sidebar:** Includes personal information and contact details for easy connectivity.
### Skills and Technologies Used
- **Streamlit:** For creating the interactive web application interface.
- **OpenCV:** For image processing and object detection.
- **NumPy:** For handling numerical operations and manipulating image data.
- **Pillow:** For image handling and processing.
### About the Model
The YOLOv3 model used in this project is a state-of-the-art object detection model known for its speed and accuracy. It has been trained to detect various objects, including helmets, and is capable of real-time detection with high performance.
### Contact
Feel free to connect with me for any questions or collaborations:
- **GitHub:** [Ahmad-Ali-Rafique](https://github.com/Ahmad-Ali-Rafique)
- **LinkedIn:** [Ahmad Ali Rafique](https://www.linkedin.com/in/ahmad-ali-rafique/)
- **Email:** [[email protected]](mailto:[email protected])
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Thank you for exploring my project! I am always eager to take on new challenges and collaborate on innovative solutions in the fields of machine learning and AI.