Tutorials

In last week’s blog post we got our feet wet by implementing a simple object tracking algorithm called “centroid tracking”. Today, we are going to take the next step and look at eight separate object tracking algorithms built right into…

Last updated on Mar 15th, 2023. Today’s tutorial kicks off a new series of blog posts on object tracking, arguably one of the most requested topics here on PyImageSearch. Object tracking is the process of: Taking an initial set of…

Whether you’re interested in learning how to apply facial recognition to video streams, building a complete deep learning pipeline for image classification, or simply want to tinker with your Raspberry Pi and add image recognition to a hobby project, you’ll…

Today’s tutorial is on saliency detection, the process of applying image processing and computer vision algorithms to automatically locate the most “salient” regions of an image. In essence, saliency is what “stands out” in a photo or scene, enabling your…

Today’s blog post is inspired by a question from PyImageSearch reader, Leonard Bogdonoff. After I published my previous post on Face recognition with OpenCV and deep learning, Leonard wrote in and asked: Hey Adrian, can you go into identity clustering?…

In last week’s blog post you learned how to perform Face recognition with Python, OpenCV, and deep learning. But as I hinted at in the post, in order to perform face recognition on the Raspberry Pi you first need to…

Last updated on December 30, 2022 with content updates. In today’s blog post you are going to learn how to perform face recognition in both images and video streams using: OpenCV Python Deep learning As we’ll see, the deep learning-based…

In the next couple of blog posts we are going to train a computer vision + deep learning model to perform facial recognition… …but before we can train our model to recognize faces in images and video streams we first…

A couple weeks ago, we discussed how to perform multi-label classification using Keras and deep learning. Today, we are going to discuss a more advanced technique called multi-output classification. So, what’s the difference between the two? And how are you…