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Mask Detection Classifier with deployment feature

This project allows users to classify images using a pretrained Convolutional Neural Network (CNN) directly in their browser. With just one line of code, you can deploy and test this mask detection app effortlessly.

Features

  • Browser-Based: The app runs directly in your browser—no additional setup required.
  • Simple to Use: Just upload a photo, and the app will quickly determine if a face is wearing a mask or not.
  • Customizable: Leverage the pretrained model to classify your own content.

Installation

To get started:

  1. Ensure you have the latest stable version of Python installed on your system.
  2. Clone this repository and install the required dependencies:
    pip install -r requirements.txt
    

Model Training

The pretrained model was trained on Kaggle resources and offers excellent accuracy. For those interested, you can retrain or modify the model by following this Kaggle Notebook. It’s fast and easy to use!

Usage

  1. Create directory models and save your model in that folder using name mask_model.h5.
  2. Run the app with the following command:
    python app.py
  3. Open the link displayed in your Python console (e.g., http://127.0.0.1:5000/).
  4. Upload any photo to the app interface.
  5. View the classification result in seconds!

Contact

For questions, support, or feedback, please refer to the contact information in my GitHub profile description.

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Simple web app.

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