face mask detection

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  Prediction made for "wearing mask"

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  Web Page

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  Uploading an image

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  prediction made for "not wearing mask"

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  uploading without mask photo

Inspiration

1. During the COVID pandemic, face masks became crucial for safety. Although the system doesn't currently process live images, I still need to learn how to integrate the camera.
2. Face masks are also required for factory workers.

What it does

1. It uses machine learning to determine whether a person is wearing a mask based on the provided image input.

How I built it

1. The data was downloaded from Kaggle
2. Resized to meet the necessary requirements.
3. Neural networks were incorporated to improve the model's accuracy.
4. The flask was used to create the webpage and integrated with the jupyter notebook

Challenges I ran into

1. Integration of jupyter notebook with the webpage
2. The accuracy of the model

Accomplishments that I am proud of

1. Learnt the usage of pickle file which is used to save the trained model, allowing it to be easily loaded and reused without needing to retrain the model from scratch each time.

What I learned

1. Convolutional Neural Network.
2. Flask integration with trained model.
3. Reading the input as an image

What's next for face mask detection

1. Able to integrate the camera for live images to be taken as input.
2. able to detect other things too such as a person is wearing a PPE kit.

Built With

• flask
• jupyter
• kaggle
• python