A Face Mask Detection system built with OpenCV, Deep Learning and Computer Vision.
The most effective way of protecting each other during the COVID-19 pandemic is wearing a face mask, thos is where the motivation of creating a system built using deep learning model to identify a person wearing a mask or not, what can be used in crowdy place such as station, schools etc.
THE data used in this project is from a Zindi Africa, The spot mask Challenge , after participating in the competition I had the idea of using the data to built a face mask detector.
I built a deep learning model TheSpotmask.ipynb , transfer learning used pretrained MobileNet application and performed a data augmentation by scaling the images to obtain a very accurate model.
Saved the model and used it to build a system video.py to predict if a person is wearing a face mask or not ina live video stream.
As mentioned earlier, the dataset is from a Zindi Africa competition, download it here CLICK HERE
This dataset consists of 3 elements:
- An image zip file that contains the images
- MASK: 1308 images
- NO-MASK: 509 images
- A train labels file
- A sample of the submission file
