Project Outline/Description:
The purpose of this project is to develop a system that can detect whether a motorcyclist is wearing a helmet or not. This system will be based on the TensorFlow & Keras frameworks in conjunction with OpenCV. The system will employ an artificial neural network to detect whether a motorcyclist is wearing a helmet or not. The system will be trained on a dataset of images containing both helmet-wearing and helmet-less motorcyclists. The system will then be used to detect violations of the helmet rule on roads and highways.
Data Collection The data for this project will be collected from the internet. Images of motorcyclists wearing helmets and motorcyclists not wearing helmets will be collected from various sources and compiled into a dataset. The dataset will then be used to train the system.
Model The model used for this project will be a convolutional neural network. The neural network will be trained on the dataset of images collected, and will be able to detect whether a motorcyclist is wearing a helmet or not.
Training The dataset will be split into training and testing sets. The training set will be used to train the neural network, while the test set will be used to evaluate.
Applications
The system is designed to run in real-time on videos from surveillance cameras, alerting law enforcement officials of any violations in order to ensure the safety of motorcyclists.
To detect motorcyclist helmet rule violations automatically.
Hardware and software requirements:
Hardware requirement :
- Computer with GPU
- Webcam
Software requirement:
- Â Tensorflow
- Keras
- OpenCV
- Python 3+
Tensorflow: Tensorflow is an open source library for numerical computation and machine learning. It is used for creating deep learning models and provides support for neural networks.
Keras: Keras is a high-level API for deep learning written in Python. It is used for creating neural networks and allows developers to quickly build and deploy models.
OpenCV: OpenCV (Open Source Computer Vision) is a library for computer vision applications. It provides tools for image and video processing, object detection, machine learning, and more.
Python: Python is a high-level programming language used for general purpose programming. It is used for creating applications, websites, and more.
What You’ll Learn after doing this project
- Gain a comprehensive understanding of how to leverage deep learning and computer vision to detect motorcyclist helmet rule violations automatically.
- Build and train a deep learning model using Tensorflow and Keras in OpenCV and how to deploy the model in a real-time scenario.
- Gain experience in integrating our model with surveillance cameras to detect violations.
- Model deployment using tkinter.
- Display the performance metrics Specificity, Sensitivity, Accuracy, respectively.
Curriculum
- 6 Sections
- 0 Lessons
- 15 Hours
- Introduction to Computer Vision and Deep Learning.0
- Setting up OpenCV and Tensorflow.0
- Building and training a deep learning model for helmet rule violation detection.0
- Integrating the model into camera for automatic violation detection.0
- Using Tkinter to create a user interface.0
- Testing and evaluating the system.0
