Howto

💡 Problem Formulation: Linear classification algorithms help in distinguishing data into pre-defined categories based on input features. For example, if you’re tasked to classify emails into ‘spam’ or ‘not spam’, your input could be the text of the email, and the desired output is a label indicating ‘spam’ or ‘not spam’. Method 1: Logistic Regression … Read more

💡 Problem Formulation: Calculating the logarithm of the gamma function, often denoted as log(Γ(x)), is a common task in statistics and various fields of science. The gamma function is a generalization of factorial, valid for complex numbers. Meant for readers who have a number x, the goal is to compute the natural logarithm of its … Read more

💡 Problem Formulation: The Iris dataset from scikit-learn is a popular multivariate dataset with four features. However, you might face situations where a 2-feature dataset is required, for example, for visualization purposes or simplistic modeling. This article showcases how to transform the original four-feature Iris dataset into a dataset with just two features while retaining … Read more

💡 Problem Formulation: When working with images, determining the aspect ratio of an object within it can be essential for various tasks such as object recognition, resizing, or altering objects proportionally. The aspect ratio is the ratio of the width to the height of an object. This article focuses on extracting this ratio using OpenCV … Read more

💡 Problem Formulation: Applying a bilateral filter to an image involves reducing unwanted noise while keeping edges sharp. In OpenCV, we aim to efficiently perform this task using Python. An example input would be a noisy image, and the desired output is a clear, denoised image with well-preserved edges. Method 1: Standard Bilateral Filtering This … Read more

💡 Problem Formulation: Many computer vision tasks involve identifying and tracking objects within images. Sometimes, these objects are best represented geometrically—a common case being elliptical shapes for objects such as eyes, wheels, or planets. For example, given an image of a car, we may wish to fit an ellipse around one of the wheels to … Read more

💡 Problem Formulation: In the realm of computer vision and image processing, there are situations where combining two images becomes necessary. Specifically, the bitwise OR operation allows for the merging of two images, pixel by pixel, such that each bit is set to 1 if either pixel’s corresponding bit is 1. For instance, when overlaying … Read more

💡 Problem Formulation: Watermarking images can be essential for copyright protection or branding purposes. This article will walk through how to add a watermark to an image using Python’s OpenCV library, starting with a base image (e.g., a landscape photo) and rendering a transparent text or logo overlay as the desired output. Method 1: Overlaying … Read more

💡 Problem Formulation: In data science tasks, often there is a need to convert datasets into dictionary-like objects for further processing or feature extraction. This article explains how to use Python’s Scikit-Learn library to accomplish this, specifically demonstrating how to convert datasets into a format that resembles Python dictionaries, where keys correspond to feature names … Read more

💡 Problem Formulation: In image processing, finding the minimum enclosing circle for an object is a common task that involves identifying the smallest circle that can completely enclose the target object. This problem is relevant in scenarios such as object tracking, shape analysis, and computer vision applications. The input is an image with an object, … Read more

💡 Problem Formulation: Transforming continuous or categorical data into a binary format is often a necessary preprocessing step in machine learning. Binarization turns your feature values into zeros and ones based on a threshold. For example, given an input array [1, 2, 3, 4], you might want to consider values greater than or equal to … Read more

💡 Problem Formulation: In image processing and computer vision tasks, it’s often necessary to identify the convex hull of contours in an image — the smallest convex shape that fully encloses the contour. This article will guide you through five distinct methods using OpenCV in Python to locate and illustrate convex hulls, from finding contours … Read more