/Deep-Surveillance-Monitor-Facial-Emotion-Age-Gender-Recognition-System

Computer Vision module for detecting emotion, age and gender of a person in any given image, video or real time webcam. A custom VGG16 model was developed and trained on open source facial datasets downloaded from Kaggle and IMDB. OpenCV,dlib & keras were used to aid facial detection and video processing. The final system can detect the emotion, age and gender of people in any given image, video or real time webcam

Primary LanguageJupyter NotebookMIT LicenseMIT

DOI License Code Coverage GitHub contributors Documentation Status GitHub release (latest by date) GitHub issues GitHub closed issues GitHub Repo Size GitHub last commit GitHub language count Commit Acitivity Code Size GitHub forks GitHub stars GitHub watchers

Deep-Surveillance-Monitor-Facial-Emotion-Age-Gender-Recognition-System

Computer Vision module for detecting emotion, age and gender of a person in any given image, video or real time webcam. A custom VGG16 model was developed and trained on open source facial datasets downloaded from Kaggle and IMDB. OpenCV,dlib & keras were used to aid facial detection and video processing. The final system can detect the emotion, age and gender of people in any given image, video or real time webcam.

Table of Contents
  1. System Description and Functions
  2. Built With
  3. Installation
  4. Authors
  5. Links

System Description and Functions

Computer Vision module for detecting emotion, age and gender of a person in any given image, video or real time webcam. A custom VGG16 model was developed and trained on open source facial datasets downloaded from Kaggle and IMDB. OpenCV,dlib & keras were used to aid facial detection and video processing. It can detect the emotion, age and gender of people in any given image, video or real time webcam.

Detect Emotion, Age, Gender in Any Image!

Detect Emotion, Age, Gender in Any Video!

Detect Emotion, Age, Gender in Webcam!

Built With

Python Jupyter OpenCV Keras Numpy Dlib

Installation

  1. Install Python and Jupyter studio
  2. Clone repo, cd into it and open the Age, Gender with Emotion.ipynb notebook in Jupyter.

Authors

Kaushik Jadhav

Links