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What is Face Recognition? It is an ability to recognize a face of a person in an image. In early days operator has to manually tag the location of each facial features. The new complex statistical model was built and used to increase the accuracy of recognition. The advent of deep learning led to huge advances in face recognition. Researchers openly shared their solution for building face recognition. Uses of Face Recognition? Identify verification. Automatically organizing raw photo libraries by the person. Tracking a specific person. Counting unique people. Finding people with similar appearances. Tools for Face Recognition: Commercial face recognition services Amazon Rekognition API:  used for FACE RECOGNITION, EMOTION DETECTION, MOTION DETECTION Microsoft Azure Face API : used for FACE RECOGNITION, AGE AND GENDER DETECTION, AND FACE SIMILARITY MATCHING. Open source face recognition: OpenFace: Brandon Amos and Carnegie Mellon university dlib: Davis Ki

Before reading this, please read  deep-learning-face-recognition-part-1.html  for better understanding What is Face Detection? ( locate and extract faces from each image.) The ability to detect and locate human faces in a photograph. Face detection is used for various purposes but here we use it for the only extraction of faces and pass it to the next level of face recognition. (face detection is one of the steps in our pipeline) Easiest Way to detect face is applying Sliding Window Classifier, It is done in two steps: Build a face detection model using a machine learning model which can tell whether a given image is a face or not. Slide the face detector across the large image for faces. If faces are detected it will note the location of it. Popular face detection algorithms:(Accuracy of detection increase from 1 to 3) viola jones Invented by Paul Viola and Michael Jones in the early 2000s. Uses decision trees to detect faces based on light and dark areas. Very fast

As i am working on windows and familiar with it, i will explain how to install keras with TensorFlow cpu. Install anaconda by downloading(just clicking next, next...install). Open anaconda prompt and type following command to create an environment and activate it.(keras is the environment name of mine) >>conda create --name keras It will prompt for yes or no : type yes. For activating the Environment,Type following: >>conda activate keras Follow the link in-case you got struck somewhere:  https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment If you reopen the anaconda prompt after closing, it will open with it's default base environment. So to change the environment use activate command as above If needed check these: (keras) C:\Users\saicharan>conda info active environment : keras active env location : E:\anaconda3\envs\keras shell level : 2 user config file