A series of articles dedicated to computer vision. All codes and exercises of this section are hosted on GitHub in a dedicated repository :
Introduction to Computer Vision : What is Computer Vision ? What are the main concepts ? When should it be used ?
Image Formation and Filtering : How are images formed ? Filters can be applied on the image to extract information. What filters can we use ?
Advanced Filtering and Transformations : In this article, we’ll cover advanced filtering and image transformation techniques.
Local features, Detection, Description and Matching : Local features are used for object tracking for example. We’ll see how to implement them, and cover othe topics.
Images Alignment : When you take a panorama, the image needs to be aligned. How is it done ?
Convolutional Neural Networks (CNN) : CNNs changed the field of Computer Vision. How do CNNs work ? What can they be used for ?
A full guide to face detection : Face Detection using Cascade Classifier, Histogram of Oriented Gradients and Convolutional Neural Networks.
Implementing YoloV3 for Object DDetection : Learn how to implement YoloV3 and detect objects on your images and videos.
How to use OpenPose on macOS ? : OpenPose is a C++ / Python library for Pose Estimation. Let’s see how to use it in macOS !
Facial Emotion Analysis WebApp : We built a Web App using Flask to analyze job seeking candidates emotions.
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