Mask_Detection

This project amis to detect if a person is wearing a face mask and weather they wear the masks correctly. This detector is a two-stage detector which means it first extract face images from the original picture, then it use a classifier to determine which class dose these face belong to. Fianlly, show the processed images on monitors.

First Install Pytorch

pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio===0.9.0 -f https://download.pytorch.org/whl/torch_stable.html

Use requirements.txt to install the packages

pip install -r requirements.txt

Run MaskDetector.py

python MaskDetector.py

Use your own classifier

Put your model files in "./classifier_model"

python detect.py --model ./classifier_model/your_model.pt --img-size YOUR_MODEL_INPUT_IMAGE_SIZE

This project will do the preporcess to the input images before feeding them to the model, which will change images from 'BGR' to 'RGB', pixel range from [0,255] to [0,1] and numpy image formate to PIL formate.

So when you train your model, make sure the model input images are 'RGB',[0,1] and PIL formate

Reference

https://github.com/YonghaoHe/LFFD-A-Light-and-Fast-Face-Detector-for-Edge-Devices https://pytorch.org/hub/pytorch_vision_resnet/