Mask Detection and Proper Wear

python code for mask detection and for classifying proper wear.

Detailed report can be found under report file.

To get the code simply clone it - git clone https://github.com/scaperex/Mask-Detection-and-Proper-Wear.git

Then, to setup the environment -

• cd Mask-Detection-and-Proper-Wear
• conda env create -f environment.yml

Activate it by - conda activate mask_detection

Finally, to evaluate the pretrained model simply run python predict.py <PATH_TO_FOLDER>.

This saves a prediction.csv file with the predictions.

Additionally, the code consists of -

• Training the model uses the train.py script. This makes use of the model as defined in LightningModel.py and by the parameters given by config.py. The data loading process is defined in maskData.py
• For visualing the prediction results run visualizeResults.py with the matching parameters.

Note, the data is expected to be given in the same format as used for training.

To view tensorboard logs:

tensorboard --logdir lightning_logs --bind_all

Then in browser: <PUBLIC_IP>:<PORT>