Jason Brownlee has a fantastic tutorial showing how you can use computer vision to recognize faces.
This is much more difficult than face detection, since you need to detect a face and recognize it for this task.
Recently, deep learning convolutional neural networks have surpassed classical methods and are achieving state-of-the-art results on standard face recognition datasets. One example of a state-of-the-art model is the VGGFace and VGGFace2 model developed by researchers at the Visual Geometry Group at Oxford.https://machinelearningmastery.com/how-to-perform-face-recognition-with-vggface2-convolutional-neural-network-in-keras/
Dr Brownlee is a world recognized author on all things AI and ML.
His tutorial is composed of six steps:
VGGFace and VGGFace2 Models
How to Install the keras-vggface Library
How to Detect Faces for Face Recognition
How to Perform Face Identification With VGGFace2
How to Perform Face Verification With VGGFace2
In order to follow this tutorial, you’ll need to have python installed (3.7 or higher), and install a few packages:
pip install git+https://github.com/rcmalli/keras-vggface.git pip show keras-vggface pip install mtcnn
To follow the tutorial, navigate to Jason’s walkthrough.
Leave a comment if you’d like any more specialized content.