Face-Mask-Detection

This project is for detection of people face and show whether he/she is wearing mask.

This project I have done by two ways one using Simple CNN While loss is categorical cross-entropy.(ACCURACY: 96%)

The second way is using Transfer Learning while loss is binary cross-entropy.(ACCURACY: 99%)

The dataset used here was made by Prajna Bhandary. It contains images of people wearing mask and not wearing mask.

with_mask: 690 images

without_mask: 686 images

Dataset Link: https://drive.google.com/file/d/1QZ3AHegRLQgM9BgVe_oRmc0T0BjrCFCb/view?usp=sharing

1. Load the Dataset from your device(I'm used Goggle colab here for my project).

2. Import the necessary Libraries.

3. Labelling the images(For EX: 0 for with_mask and 1 for without_mask).

4. Train the classifier using CNN and other is using VGG16.

5. Save your model into your local device.

6. For Detection of image run the code of imgdetect.py

7. For Real time Detection run Real_time_detection.py

I have attached an PPT for understanding how the models works. You can go thriugh that.