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.
Screenshots
Detect Emotion, Age, Gender in Any Image!
Detect Emotion, Age, Gender in Any Video!
Detect Emotion, Age, Gender in Webcam!
Technical Concepts
VGG The VGG network architecture was introduced by Simonyan and Zisserman in their 2014 paper, Very Deep Convolutional Networks for Large Scale Image Recognition.
This network is characterized by its simplicity, using only 3×3 convolutional layers stacked on top of each other in increasing depth. Reducing volume size is handled by max pooling. Two fully-connected layers, each with 4,096 nodes are then followed by a softmax classifier
More information can be found here
Resnet Unlike traditional sequential network architectures such as AlexNet, OverFeat, and VGG, ResNet is instead a form of “exotic architecture” that relies on micro-architecture modules (also called “network-in-network architectures”).
The term micro-architecture refers to the set of “building blocks” used to construct the network. A collection of micro-architecture building blocks (along with your standard CONV, POOL, etc. layers) leads to the macro-architecture
More information can be found here
Technologies used
How to Install and Use
- Install Python. Download my repo and change to directory of repo.
- On command prompt, run pip install -r requirements.txt
- On commmand prompt, run jupter notebook
- Open and run my jupyter notebook