🧑‍💻 Face-Mask-Recognition

Repository: Alauddinbukhari/Face-Mask-Recognition
Visibility: Public

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📌 Overview

Face-Mask-Recognition is a real-time face mask detection project built with Python, Keras, and OpenCV.
It trains a Convolutional Neural Network (CNN) to classify images as Mask or No Mask, and integrates with a webcam feed to detect faces and display results live.

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⚙️ Features

• CNN model trained on custom dataset (train/train and test/test).
• Real-time detection using Haar Cascade classifier.
• Bounding boxes with labels:
  • 🟥 No Mask → Red box
  • 🟩 Mask → Green box
• Data augmentation for robust training.
• Model checkpointing (model-010.h5) and final saved model (datamodel.h5).

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🛠️ Tech Stack

• Python 3.x
• Keras / TensorFlow
• OpenCV
• NumPy
• Scikit-learn

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📂 Repository Structure

Face-Mask-Recognition/
├── train/                        # Training dataset
├── test/                         # Validation dataset
├── train.py                      # Model training script
├── recognize.py                  # Real-time detection script
├── model-010.h5                  # Saved trained model checkpoint
├── datamodel.h5                  # Final trained model
├── haarcascade_frontalface_default.xml # Haar Cascade for face detection
├── more about dataset.txt        # Dataset details
└── README.md                     # Project documentation

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🚀 Getting Started

1. Clone the repository

git clone https://github.com/Alauddinbukhari/Face-Mask-Recognition.git
cd Face-Mask-Recognition

2. Install dependencies

pip install -r requirements.txt

3. Train the model

python train.py

This will train the CNN using images in train/ and test/ directories, and save the model as datamodel.h5.

4. Run real-time detection

python recognize.py

Press ESC to exit the webcam window.

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📊 Model Architecture

• Conv2D + MaxPooling → Feature extraction
• Flatten → Convert to 1D vector
• Dropout → Prevent overfitting
• Dense layers → Classification
• Softmax output → Mask / No Mask

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👨‍🎓 Author

Owner: Alauddinbukhari

• Full‑stack developer (Python, Java, React, Cloud)
• Passionate about building scalable and secure applications
• Open to freelance and contract opportunities