Gender-Recognition-Using-Deep-Learning

Objective:

Implementation of a deep learning model to recognize the gender of people in images.

Overview:

• This project implements a simple Convolutional Neural Network which is trained on a dataset of images labelled by gender.

• A web cam application is also implemented to capture faces off the video stream and classify them as either man or woman.

• The classifier attained a training accuracy of 98.4% and a validation accuracy of 95.6%.

Code and Dependancies

• Python Version: 3.7

• Packages: numpy, pandas, matplotlib, glob, scikit-learn, tensorflow, OpenCV, cvlib