Nargesmohammadi / Face-Mask-Detection-CNN

Implementing a face mask detection model using a convolutional neural network. The model is trained on a dataset of images with and without masks, and can classify whether a person in an input image is wearing a mask or not. The code includes data preprocessing, model training, and prediction on

Face Mask Detection using Convolutional Neural Networks

This project is a simple implementation of a Convolutional Neural Network (CNN) for detecting whether a person is wearing a face mask or not. The model is trained on a dataset of images containing people with and without masks.

Dataset

The dataset used for this project is the Face Mask Dataset by Omkar Gurav, which contains over 7,000 images of people with and without masks.

Requirements

To run this project, you will need the following:

• Python 3.x
• TensorFlow 2.x
• NumPy
• Matplotlib
• OpenCV
• scikit-learn

I've installed these dependencies using pip:

pip install tensorflow numpy matplotlib opencv-python scikit-learn

Results

The model achieves an accuracy 94% on the test set.

Below is the results of the code for predicting the images: