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Projects Repository

This repository contains multiple machine learning and computer vision projects implemented to solve real-world problems. Each project includes detailed explanations, dataset links, and source code.

Projects

1. Sign Language Detection Using ASL Dataset

  • Description: A system to detect American Sign Language (ASL) alphabets using computer vision and deep learning models.
  • Dataset: Synthetic ASL Alphabet Dataset
  • Features:
    • Utilizes a CNN model for classification.
    • Predicts alphabets from static hand gesture images.
  • Technologies: Python, TensorFlow/Keras, OpenCV
  • How to Run:
    • Follow the README file located in the project folder.

2. Drowsiness Detection Project

  • Description: A system to detect drowsiness in drivers or users using real-time facial features.
  • Dataset:
  • Features:
    • Detects eye closure and yawning using real-time video streams.
    • Triggers alerts like beep sounds and visual warnings.
  • Technologies: Python, TensorFlow/Keras, OpenCV, Dlib
  • How to Run:
    • Follow the README file located in the project folder.

3. Fall Detection System

  • Description: A system that detects falls using motion detection algorithms to monitor elderly individuals and trigger alerts.
  • Dataset: Fall Detection Dataset
  • Features:
    • Real-time fall detection based on video data.
    • Alerts triggered when a fall is detected.
  • Technologies: Python, OpenCV, TensorFlow
  • How to Run:
    • Follow the README file located in the project folder.

4. Smart CCTV Surveillance System

  • Description: A smart CCTV system that automatically detects and recognizes objects or people in real-time, with capabilities like motion and anomaly detection.
  • Dataset: Open Images Dataset
  • Features:
    • Detects people and objects in real-time using video feeds.
    • Capable of tracking movements and alerting when anomalies are detected.
  • Technologies: Python, OpenCV, TensorFlow, YOLO
  • How to Run:
    • Follow the README file located in the project folder.

5. Yoga Posture Recognition

  • Description: A system that uses computer vision and deep learning to recognize and provide feedback on yoga postures.
  • Dataset: Yoga Posture Dataset
  • Features:
    • Classifies yoga postures using images.
    • Provides feedback on posture correctness.
  • Technologies: Python, OpenCV, TensorFlow, Pose Estimation
  • How to Run:
    • Follow the README file located in the project folder.

Requirements

Each project includes its own dependencies in a requirements.txt file. To install dependencies for a specific project, run: pip install -r /requirements.txt

How to Contribute

If you'd like to contribute to any of these projects:
Fork the repository.
Clone the repository to your local machine.
Create a new branch for your feature or fix.
Submit a pull request with a clear description of your changes.

License

All projects in this repository are licensed under the MIT License. Feel free to use, modify, and distribute the code with proper attribution.

Contact

For any questions, suggestions, or collaborations, feel free to reach out:

Name: Nitesh Kumar Email: nk7003361@gmail.com

Thank you for visiting this repository! 🚀