COVID-19 Medical Face Mask Detection using ResNet34

[DarshAgrawal14]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : COVID-19 Medical Face Mask Detector
:red_circle: Aim :Develop a deep learning model to detect whether the person is wearing a facemask or not . This model can be used in hospitals as well as clean room monitoring where it is necessary to wear a facemask . This is necessity in all industries where sanitation is required .
:red_circle: Dataset : Facemask Detection Dataset (images + annotations)
:red_circle: Approach : process images with XML annotations to detect three states: properly worn masks, incorrectly worn masks, and no masks. The implementation leverages a pretrained ResNet34 model with a modified final layer for 3-class classification, while keeping the feature extraction layers frozen. The system preprocesses images to 224x224 pixels, crops face regions based on bounding box annotations, and uses a 70/30 train-test split. Training employs SGD optimization with CrossEntropyLoss over 2 epochs, achieving classification of mask wear states from facial images.

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📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

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:red_circle::yellow_circle: Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

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:white_check_mark: To be Mentioned while taking the issue :

• Full name : Darsh Agrawal
• GitHub Profile Link : https://github.com/DarshAgrawal14
• Email ID : agrawaldarsh14@gmail.com
• Participant ID (if applicable):
• Approach for this Project : mentioned Above
• What is your participant role? GSSoC'24 extended and Hactoberfest'24

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[github-actions[bot]]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[abhisheks008]

Similar problem statement is already present in this repository. Hence clsoing this issue as duplicate entry.