Self-Portraits Taken Automatically by Detecting Smiles (Information Horizons: American Journal of Library and Information Science Innovation (2993-2777), 2024)
Get beautiful selfies automatically captured when you smile – Python Project to automatically detect and capture selfies. Everyone loves a smiling picture, so we will develop a project to capture images every time you smile. For this machine learning project, we will use the OpenCV library. OpenCV is an open-source library for computer vision, focusing on real-time applications. It focuses mainly on video capture/processing, image processing, and analysis (like face and object detection). It has many built-in functions and pre-trained models, so we don’t have to worry about training and testing algorithms. For this project, we need haarcascade_frontalface_default.xml and haarcascade_smile.xml files. Please download these files using the link and the project code mentioned in the previous step. Haar Cascade is an ML object detection algorithm that identifies objects in an image or video. In this algorithm, a cascade function is trained from many positive and negative images, which is then used to detect objects in other images. It can be trained to identify almost any object. In this project, we will be using these pre-trained files.