😷 Face Mask Detection

An ML based solution to detect and ensure if the people are wearing a face mask in public places using TensorFlow and Keras.

The face detection model is trained on a dataset of 686 images with human faces. And the face mask detection model is trained on a dataset of 690 images of people wearing a mask.

Samples -

Outputs of detection performed on random images from google images -

How to install -

Install Python 3.5 or newer.
Clone this repository into your local machine using command -

git clone https://github.com/visitishan/Face_Mask_Detection.git

Navigate to your newly created folder and create a python virtual environment using

python -m venv --system-site-packages .\venv

Activate the virtual environment -

.\venv\Scripts\activate

Install the required packages -

pip install -r requirements.txt

Verify the installation of TensorFlow. If a tensor is returned, it means TensorFlow is installed successfully. (Optional)

python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"

Great!! You are ready to use the code now.

How to use -

If you want to re-train the model from the images dataset or with your custom images, you can do it by running -

python train_mask_detector.py --dataset dataset

This will save a new model file with the name mask_detector.model in the working directory.

To test the model on images, you can use the file detect_mask_image.py. Run the following command -

python detect_mask_image.py --image examples/example_01.png

Here we are running the code for a test image stored in the examples folder. You can change the argument value with the path of your custom image to test.

To detect face mask on a continuous video stream from your webcam, you can run -

python detect_mask_video.py

Live Webcam -

Yet to be captured and updated 😉