Computer Vision: Face Recognition Quick Starter in Python

In this module, we will introduce the course, providing an overview of the topics to be covered, and discuss the significance of face recognition in various applications.

In this module, we will set up the development environment by installing the Anaconda package. This will prepare our computer for Python coding.

In this module, we will cover essential Python programming basics, including assignments, flow control, data structures, and functions.

In this module, we will install the necessary dependencies and libraries required for face recognition.

In this module, we will introduce face detectors, discussing their importance and the different techniques used for detecting faces.

In this module, we will implement face detection in code using the face_recognition and OpenCV libraries.

In this module, we will address the common issue of the cv2.imshow() function not responding while displaying images.

In this module, we will detect and locate faces from a real-time webcam video feed.

In this module, we will detect and locate faces in pre-recorded video files.

In this module, we will blur detected faces in real-time video to ensure privacy.

In this module, we will install the libraries required for real-time facial expression detection.

In this module, we will detect facial expressions from a real-time webcam video feed.

In this module, we will delve into the techniques for detecting facial expressions in video footage.

In this module, we will detect facial expressions in static images.

In this module, we will introduce age and gender detection, discussing their significance and applications.

In this module, we will perform real-time age and gender classification on webcam video feed.

In this module, we will classify the age and gender of faces in static images.

In this module, we will introduce face recognition, discussing its applications and underlying principles.

In this module, we will implement face recognition algorithms to detect and recognize faces in images.

In this module, we will detect and recognize faces from a real-time webcam video feed.

In this module, we will detect and recognize faces in pre-recorded video files.

In this module, we will calculate the distance between faces for advanced analysis.

In this module, we will learn how to visualize and customize face landmarks in images.

In this module, we will visualize and customize face landmarks for multiple faces in both real-time and pre-saved videos.

In this module, we will demonstrate how to customize face landmarks to apply simple makeup.

In this module, we will demonstrate face makeup in a real-time video using face landmarks.