Face Mask Detection

This project involves building a face detection model using Convolutional Neural Networks (CNN) with Keras. The model is designed to classify images into two classes: whether a person is wearing a mask or not. The architecture consists of multiple convolutional layers followed by dense layers, with dropout layers to prevent overfitting.

Dataset

https://www.kaggle.com/datasets/omkargurav/face-mask-dataset

Installation

To run this model, ensure you have the following dependencies installed:

pip install tensorflow
pip install numpy

Parameters

• input_shape: The shape of the input images (default is (128, 128, 3)).
• num_of_class: The number of classes for classification (default is 2 for binary classification).

Getting Started

1. Clone the repository.
2. Install the required dependencies.
3. Load your dataset and preprocess it.
4. Define and compile the model.
5. Train the model on your dataset.
6. Evaluate and make predictions with the model.

Output

Happy Coding 👦