Python

💡 Problem Formulation: When working with image processing, a common task is to apply custom filters to enhance or extract features from images. Convolution is a mathematical operation used to apply these filters. Suppose we have an image and we want to highlight edges, blur, sharpen, or detect specific patterns using a custom designed filter. … Read more

💡 Problem Formulation: You have an image with a planar object, and you want to adjust its perspective to simulate a different viewpoint. For example, you’ve photographed a painting that wasn’t perfectly frontal and want to rectify it to appear as if viewed head-on. We plan to cover methods to apply perspective transformations using Python’s … Read more

💡 Problem Formulation: Converting a colored image to HLS (Hue, Lightness, Saturation) is often necessary for image processing tasks such as object tracking, computer vision, and image analysis. For example, given an input image in BGR (Blue, Green, Red) format, the task is to transform this image to HLS format using OpenCV in Python to … Read more

💡 Problem Formulation: You have an image and need to annotate it by drawing an arrowed line to highlight specific areas or to point to something. In OpenCV Python, this can be done through various methods. Imagine you have an image representing a map, and you want to draw an arrow from one city to … Read more

💡 Problem Formulation: In image processing, it’s often necessary to identify and encapsulate contours within bounding rectangles. OpenCV Python offers several methods to accomplish this. Given a binary or edge-detected image, we want to locate contours and create bounding boxes around them to extract or analyze these isolated regions. Method 1: Using cv2.boundingRect() OpenCV’s cv2.boundingRect() … Read more

💡 Problem Formulation: Affine transformation in image processing refers to altering an image to correct for distortions or to apply certain effects. When using OpenCV in Python, developers often need to apply affine transformations to shift, scale, rotate or skew images. This article walks through five methods to do this on an input image, aiming … Read more

💡 Problem Formulation: The task involves performing a bitwise XOR operation on two image matrices using OpenCV in Python. Given two images of identical dimensions, the desired output is a third image where each pixel is the result of a bitwise XOR operation between the corresponding pixels of the original images. This can be useful … Read more

💡 Problem Formulation: In the realm of image processing, performing a bitwise AND operation on two images is a fundamental technique. This process involves overlaying two images on top of one another and then performing the AND operation on every corresponding pair of pixels. The result is a new image in which only the pixels … Read more

💡 Problem Formulation: In text processing and parsing tasks, it’s common to need to identify and manipulate whitespace characters such as spaces, tabs, and newlines. For instance, in data cleaning, a programmer may want to find all the whitespace to replace or remove it from a string. Let’s say we have the input string “whitespace … Read more

💡 Problem Formulation: When working with Python’s regular expressions, it is often necessary not only to find if a pattern exists but also to locate the exact indices where each occurrence of the pattern is found within the string. For instance, given the input string “cat, bat, rat, sat” and the pattern “at”, the desired … Read more

💡 Problem Formulation: In Python programming, there are several scenarios where a developer needs to convert a number (be it an integer or a float) into a string data type. For instance, when concatenating a number with a string, or embedding numeric data into text output. This article will cover five methods to perform this … Read more

💡 Problem Formulation: In image processing, thresholding is a technique that converts an image into a binary image, where the pixels either become solid black or white, effectively segmenting the image into foreground and background. Adaptive thresholding, unlike simple thresholding, changes the threshold dynamically over the image to handle differing lighting conditions. This article demonstrates … Read more