Extracting Histogram of Gradients with OpenCV
Besides the feature descriptor generated by SIFT, SURF, and ORB, as in the previous post, the Histogram of Oriented Gradients (HOG) is another feature descriptor you can obtain using OpenCV. HOG is a...
View ArticleImage Datasets for Practicing Machine Learning in OpenCV
At the very start of your machine learning journey, making use of publicly available datasets alleviates the worry of having to create the datasets yourself, and rather lets you focus on learning to...
View ArticleHow to Train a Object Detection Engine with HOG in OpenCV
In the previous post, you saw that OpenCV can extract features from an image using a technique called the Histogram of Oriented Gradients (HOG). In short, this is to convert a “patch” of an image into...
View ArticleSupport Vector Machines in OpenCV
The Support Vector Machine algorithm is one of the most popular supervised machine learning techniques, and it comes implemented in the OpenCV library. This tutorial will introduce the necessary skills...
View ArticleHardware-Accelerated AI for Windows Apps Using ONNX RT
Sponsored Content By Rajan Mistry Sr. Applications Engineer with the Qualcomm Developer Network Today, you can’t help but read the media headlines about AI and the growing sophistication of...
View ArticleImage Vector Representation for Machine Learning Using OpenCV
One of the pre-processing steps that are often carried out on images before feeding them into a machine learning algorithm is to convert them into a feature vector. As we will see in this tutorial,...
View ArticleSupport Vector Machines for Image Classification and Detection Using OpenCV
In a previous tutorial, we have explored the use of the Support Vector Machine algorithm as one of the most popular supervised machine learning techniques that comes implemented in the OpenCV library....
View ArticleNormal Bayes Classifier for Image Segmentation Using OpenCV
The Naive Bayes algorithm is a simple but powerful technique for supervised machine learning. Its Gaussian variant is implemented in the OpenCV library. In this tutorial, you will learn how to apply...
View ArticleRandom Forest for Image Classification Using OpenCV
The Random Forest algorithm forms part of a family of ensemble machine learning algorithms and is a popular variation of bagged decision trees. It also comes implemented in the OpenCV library. In this...
View ArticleUsing Haar Cascade for Object Detection
Before the deep learning revolution redefined computer vision, Haar features and Haar cascades were the tools you must not ignore for object detection. Even today, they are very useful object detectors...
View ArticleTraining a Haar Cascade Object Detector in OpenCV
Using a Haar cascade classifier in OpenCV is simple. You just need to provide the trained model in an XML file to create the classifier. Training one from scratch, however, is not so straightforward....
View ArticleK-Means Clustering in OpenCV and Application for Color Quantization
The k-means clustering algorithm is an unsupervised machine learning technique that seeks to group similar data into distinct clusters to uncover patterns in the data that may not be apparent to the...
View ArticleRunning a Neural Network Model in OpenCV
Many machine learning models have been developed, each with strengths and weaknesses. This catalog is not complete without neural network models. In OpenCV, you can use a neural network model developed...
View ArticleLogistic Regression in OpenCV
Logistic regression is a simple but popular machine learning algorithm for binary classification that uses the logistic, or sigmoid, function at its core. It also comes implemented in the OpenCV...
View ArticleLogistic Regression for Image Classification Using OpenCV
In a previous tutorial, we explored logistic regression as a simple but popular machine learning algorithm for binary classification implemented in the OpenCV library. So far, we have seen how logistic...
View ArticleMachine Learning in OpenCV (7-Day Mini-Course)
Machine learning is an amazing tool for many tasks. OpenCV is a great library for manipulating images. It would be great if we can put them together. In this 7-part crash course, you will learn from...
View ArticleRevealing the Invisible: Visualizing Missing Values in Ames Housing
The digital age has ushered in an era where data-driven decision-making is pivotal in various domains, real estate being a prime example. Comprehensive datasets, like the one concerning properties in...
View ArticleDecoding Data: An Introduction to Descriptive Statistics with the Ames...
In this enlightening journey through the myriad lanes of Ames properties, we shine our spotlight on Descriptive Statistics, a cornerstone of Data Science. The study of the Ames properties dataset...
View ArticleFrom Data to Map: Visualizing Ames House Prices with Python
Geospatial visualization has become an essential tool for understanding and representing data in a geographical context. It plays a pivotal role in various real-world applications, from urban planning...
View ArticleExploring Dictionaries, Classifying Variables, and Imputing Data in the Ames...
The real estate market is a complex ecosystem driven by numerous variables such as location, property features, market trends, and economic indicators. One dataset that offers a deep dive into this...
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