face-mask-detector's Introduction

Face-Mask-Detector

Face Mask Detector built with OpenCV, TensorFlow/Keras using Deep Learning CNN and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams.

⭐ TechStack/framework used

📁 Dataset

The dataset used can be downloaded here - Click to Download

This dataset consists of 4095 images belonging to two classes:

with_mask: 2165 images
without_mask: 1930 images

The images used were real images of faces wearing masks. The images were collected from the following sources:

Bing Search API (See Python script)
Kaggle datasets
RMFD dataset (See here)(medium article link)

🔑 Prerequisites

All the dependencies and required libraries are included in the file requirements.txt Run the following command in your Terminal/Command Prompt to install the libraries required

$ pip3 install -r requirements.txt

💡 Working

Open terminal. Go into the cloned project directory and type the following command:

$ python3 train_mask_detector.py --dataset dataset

To detect face masks in an image type the following command:

$ python3 detect_mask_image.py --image images/pic1.jpeg

To detect face masks in real-time video streams type the following command:

$ python3 detect_mask_video.py

📑Streamlit app

Face Mask Detector webapp using Tensorflow & Streamlit

command

$ streamlit run app.py

☑️Result

Hyperparameter: - batch size: 32 - Learing rate: 0.0001 - Input size: 64x64x3

The Pre-trained models used can be downloaded here - Click to Download

Model result

Model	Test Accuracy	Size	Params	Memory consumption
CNN	87.67%	27.1MB	2,203,557	72.58 MB
VGG16	93.08%	62.4MB	288,357	18.06 MB
MobileNetV2 (fine tune)	97.33%	20.8MB	1,094,373	226.67 MB
Xception	98.33%	96.6MB	1,074,789	368.18 MB