#Gender Detection

Welcome to the Gender Detection Model project by @wingFire-29!
This project uses deep learning and OpenCV to detect human faces in real-time and predict their gender — Male or Female — with high confidence.

Features

• Real-time face detection
• Gender classification with probability score
• Support for both webcam and image inputs
• Testing framework to evaluate model accuracy

Requirements

• Python 3.6+
• OpenCV
• NumPy
• Pre-trained models (included in the repository)

Setup

1. Clone the repository:

   git clone https://github.com/yourusername/age-and-gender-detection.git
   cd age-and-gender-detection
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

Running Real-time Detection

To run gender detection on your webcam:

python detect.py

To run detection on a specific image:

python detect.py --image path/to/image.jpg

Press 'q' to exit the application.

Testing Model Accuracy

To evaluate the model accuracy on a dataset:

python testing1.py --dataset path/to/dataset

The dataset should have the following structure:

dataset/
  ├── Male/
  │   ├── image1.jpg
  │   ├── image2.jpg
  │   └── ...
  └── Female/
      ├── image1.jpg
      ├── image2.jpg
      └── ...

Pre-trained Models

The project uses pre-trained models for face detection and gender classification:

• Face Detection: OpenCV's DNN-based face detector
• Gender Classification: Caffe model for gender recognition

Dataset

For testing purposes, the project includes two datasets:

• dataset100: A small dataset with 100 images
• dataset1000: A larger dataset with 1000 images

Results

Testing results show an accuracy of XX% on gender classification.

License

[Add your license information here]