Helmet Detection and Automatic License Plate Recognition (ALPR)
This project demonstrates the use of machine learning for helmet detection and automatic license plate recognition (ALPR). It utilizes computer vision techniques and machine learning models to achieve these functionalities.
Features
Helmet Detection:
Uses a trained machine learning model to detect whether a person is wearing a helmet or not.
Provides bounding boxes around detected helmets in images or videos.
Automatic License Plate Recognition (ALPR):
Recognizes license plates from images or videos.
Utilizes optical character recognition (OCR) techniques to extract alphanumeric characters from license plates.
Installation
To install and run this project locally, follow these steps:
Clone the repository:
bash
Copy code
git clone https://github.com/your-username/helmet-alpr.git cd helmet-alpr
Set up environment:
Create a virtual environment (optional but recommended).
Install dependencies:
bash
Copy code
pip install -r requirements.txt
Download pretrained models (if necessary):
Follow instructions in models/README.md to download pretrained models for helmet detection and ALPR.
Replace path/to/image_or_video with the path to your input image or video file. The recognized license plates and their bounding boxes will be saved at path/to/save/result.
Contributing
Contributions are welcome! Please fork the repository and submit pull requests.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
This project uses pretrained models from Model Zoo.
Special thanks to contributors and maintainers.
This project combines two advanced computer vision applications: Helmet Detection using Machine Learning and Automatic License Plate Recognition (ALPR). The Helmet Detection component utilizes deep learning models to detect the presence of helmets in images or video streams, providing real-time detection and bounding box visualization. This is particularly useful for safety monitoring in construction sites, industrial environments, and sports events. On the other hand, the ALPR module employs image processing techniques and optical character recognition (OCR) to accurately extract license plate numbers from vehicles in images or videos.
Helmet Detection and Automatic License Plate Recognition (ALPR)
This project demonstrates the use of machine learning for helmet detection and automatic license plate recognition (ALPR). It utilizes computer vision techniques and machine learning models to achieve these functionalities.
Features
Installation
To install and run this project locally, follow these steps:
Clone the repository:
bash
Copy code
git clone https://github.com/your-username/helmet-alpr.git cd helmet-alpr
Set up environment:
Create a virtual environment (optional but recommended).
Install dependencies:
bash
Copy code
pip install -r requirements.txt
Download pretrained models (if necessary):
models/README.md
to download pretrained models for helmet detection and ALPR.Usage
Helmet Detection
To use helmet detection, run:
bash
Copy code
python helmet_detection.py --input path/to/image_or_video --output path/to/save/result
Replace
path/to/image_or_video
with the path to your input image or video file. The output will be saved atpath/to/save/result
.Automatic License Plate Recognition (ALPR)
To perform ALPR, run:
bash
Copy code
python alpr.py --input path/to/image_or_video --output path/to/save/result
Replace
path/to/image_or_video
with the path to your input image or video file. The recognized license plates and their bounding boxes will be saved atpath/to/save/result
.Contributing
Contributions are welcome! Please fork the repository and submit pull requests.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
This project combines two advanced computer vision applications: Helmet Detection using Machine Learning and Automatic License Plate Recognition (ALPR). The Helmet Detection component utilizes deep learning models to detect the presence of helmets in images or video streams, providing real-time detection and bounding box visualization. This is particularly useful for safety monitoring in construction sites, industrial environments, and sports events. On the other hand, the ALPR module employs image processing techniques and optical character recognition (OCR) to accurately extract license plate numbers from vehicles in images or videos.
yolo weights :- https://drive.google.com/drive/folders/1uoNASEOVJ2rP9HxuyIiiNZt682rDV7Pg?usp=drive_link
Here is the output with some images