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Women Safety Analytics

Overview

This project is designed to enhance women's safety through real-time video analysis. It uses machine learning and computer vision techniques to detect faces, classify gender, identify gestures, and generate alerts based on suspicious behavior. Key functionalities include:

  • Face detection
  • Gender classification
  • Gesture recognition
  • Real-time alert system for lone women and suspicious gestures

Features

  • Face Detection: Uses OpenCV's pre-trained model for detecting faces in video frames.
  • Gender Classification: Classifies detected faces into male or female using a deep learning model.
  • Gesture Recognition: Placeholder for gesture detection model (needs implementation).
  • Alert System: Sends email alerts and displays on-screen notifications for detected anomalies, lone women, or suspicious gestures.

Setup

Prerequisites

  • Python 3.x
  • OpenCV
  • TensorFlow (for gesture recognition, if applicable)
  • NumPy
  • smtplib (for sending email alerts)

Installation

  1. Clone the Repository

    git clone(https://github.com/Asmi-va/women_safety_analysis/new/main?readme=1)
cd repository

  2. Install Dependencies

    pip install opencv-python numpy

  3. Download Pre-trained Models

  4. Configure Email Alerts

    • Update the EMAIL_HOST, EMAIL_PORT, EMAIL_HOST_USER, EMAIL_HOST_PASSWORD, and ALERT_RECEIVER variables in the code with your SMTP server details and email addresses.

Running the Application

  1. Start the Script

    python women_safety_analysis.py

  2. Terminate the Script

    • Press q in the OpenCV window to stop the video capture.

Project Structure

women_safety_analysis/
├── women_safety_analysis.py
├── opencv_face_detector.pbtxt
├── opencv_face_detector_uint8.pb
├── age_deploy.prototxt
├── age_net.caffemodel
├── gender_deploy.prototxt
├── gender_net.caffemodel
├── gesture_recognition_model.h5
├── women_safety.log
└── README.md

Known Issues

  • Gesture recognition model is currently a placeholder and needs to be implemented.
  • Ensure all models are correctly downloaded and paths are updated in the script.

Contributing

Feel free to contribute to this project by opening issues or submitting pull requests. For detailed contribution guidelines, please refer to CONTRIBUTING.md.

License

This project is licensed under the MIT License - see the LICENSE file for details.