Data Science Series EP 10
Predict the Gender and Age Using OpenCV in Python
A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services, works by pinpointing and measuring facial features from a given image.
What is OpenCV?
OpenCV is short for Open Source Computer Vision. Intuitively by the name, it is an open-source Computer Vision and Machine Learning library. This library is capable of processing real-time images and videos while also boasting analytical capabilities. It supports the Deep Learning frameworks TensorFlow, Caffe, and PyTorch.
What is a CNN?
A Convolutional Neural Network is a deep neural network (DNN) widely used for the purposes of image recognition and processing and NLP. Also known as a ConvNet, a CNN has input and output layers, and multiple hidden layers, many of which are convolutional. In a way, CNN's are regularized multilayer perceptrons.
Application of Facial Recognition:
- Security companies are using facial recognition to secure their premises.
- Ride-sharing companies can use facial recognition to ensure the right passengers are picked up by the right drivers.
- Fleet management companies can use face recognition to secure their vehicles.
Implementation
1. Stage #1: Detect faces from the input image
2. Stage #2: Extract the face Region of Interest (ROI), and apply the age detector algorithm to predict the age of the person
For Stage #1, any face detector capable of producing bounding boxes for faces in an image can be used
The face detector produces the bounding box coordinates of the face in the image.
For Stage #2 — identifying the age of the person.
Code
Output
Conclusion:
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