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This project focuses on real-time gender and gesture recognition using machine learning techniques. The system detects and classifies gender based on facial features and identifies gestures through image or video input. The model leverages TensorFlow and Keras for training and inference, ensuring accurate and efficient recognition.

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AmitPrasad212003/Gender-Gesture-Recognition

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Gender and Gesture Recognition

This project implements a Gender and Gesture Recognition system using deep learning techniques with TensorFlow and Keras. The model is designed to classify genders and recognize gestures from input images or videos, aiming to enhance safety and interaction in various real-world scenarios.

Features

  • Gender Recognition: Classifies gender based on facial features.
  • Gesture Recognition: Detects and classifies hand gestures.
  • Real-time Processing: Supports real-time gender and gesture recognition via webcam or video input.
  • Deep Learning Models: Built with TensorFlow and Keras.

Requirements

To run this project, you need the following dependencies:

  • Python 3.x
  • TensorFlow
  • Keras
  • OpenCV
  • NumPy
  • Matplotlib

You can install the required packages using:

pip install tensorflow keras opencv-python numpy matplotlib

About

This project focuses on real-time gender and gesture recognition using machine learning techniques. The system detects and classifies gender based on facial features and identifies gestures through image or video input. The model leverages TensorFlow and Keras for training and inference, ensuring accurate and efficient recognition.

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