We’ll explore how to use OpenCV’s addWeighted function to blend images with different weights. Understanding Image Blending Image blending, also known as image compositing, involves combining two or more images by assigning different weights to each pixel. This technique is useful for various applications, including: Image Merging: Combining two or more images into a single Continue reading
Multiple Regression with NumPy
NumPy provides powerful tools for performing multiple linear regression, a statistical method used to model the relationship between a dependent variable and two or more independent variables. This guide will explain the key concepts of multiple regression and demonstrate how to implement it efficiently using NumPy.
Exponential Regression with NumPy
Master exponential regression from theory to implementation. Learn how to use NumPy to build predictive models for growth patterns, population dynamics, and financial forecasting. đź’ˇ Quick Insight: NumPy’s vectorized operations can execute exponential regression calculations 20-100x faster than traditional Python loops, making it essential for large-scale data analysis.
Create a Bubble Plot with Seaborn
You will learn how to create a bubble chart in Seaborn.
Fixing the Dreaded RecursionError: maximum recursion depth exceeded in Python
The RecursionError occurs in Python when a recursive function exceeds the maximum recursion depth, a limit set to prevent a stack overflow. I provide you insights into understanding and resolving this common error in recursive function implementations.
Using Python Tracebacks to Understand Error Flows
Tracebacks in Python provide a detailed snapshot of the call stack at the point where an exception occurs, making them an invaluable resource for debugging. I show you how to interpret tracebacks and leverage them to diagnose and resolve errors in your Python code.
Advanced Python Debugging with PDB
Transform from squinting at error messages to systematically hunting down bugs. Learn how Python’s built-in debugger (PDB) can reduce your debugging time by 60-80% and help you write more reliable code.
How to use matplotlib cmap?
A colormap, or cmap, is a mapping from a range of values to a range of colors. In Matplotlib, cmaps are used to colorize data in plots. There are many built-in cmaps in Matplotlib, and you can also create your own. To use a cmap in Matplotlib, you can use the plt.cm.get_cmap() function. This function Continue reading
How to Change the Title Font Size in Plotly
Plotly offers extensive customization options for your plots, including adjusting the title font size. This guide demonstrates two methods to achieve this: using the layout argument and the update_layout method.
How to create a title with multiple lines in Plotly
One of the features of Plotly is that it allows you to customize the appearance of your charts, including the title. We will show you how to create a title with multiple lines in Plotly, using different methods and options.
Aruco Marker Detection with OpenCV
OpenCV (Open Source Computer Vision Library) is a powerful open-source tool for computer vision and image processing tasks. Aruco markers are a type of augmented reality marker used for detecting and tracking objects in computer vision applications. We’ll explore how to use OpenCV to detect and work with Aruco markers in your projects.
How to resolve MemoryError: Unable to allocate array in Numpy?
If you are working with big data and performance-related scalable systems in Python, you might have encountered the dreaded MemoryError: Unable to allocate array in Numpy. This error occurs when Numpy tries to create an array that is larger than the available memory on your machine. I will explain why this error happens, how to Continue reading
How to Fix NumPy RuntimeError: Sanity Check Failure (Complete Guide)
Master the complete troubleshooting process for NumPy’s “fails to pass a sanity check” error. Learn the root causes, platform-specific fixes, and prevention strategies. ⚠️ Critical Error: This error means NumPy detected a problem with its installation that prevents safe operation. Do NOT ignore it—your code will fail or produce incorrect results.
How to use numpy mgrid
I will explain how to use numpy mgrid, a powerful tool for creating multidimensional grids. Numpy mgrid is a function that returns a dense multi-dimensional “meshgrid”. A meshgrid is an array that contains the coordinates of a rectangular grid.
How to use numpy logspace
I will explain how to use numpy logspace, a handy function for creating logarithmically spaced arrays. Such arrays are particularly useful in various scientific and engineering applications where data or phenomena span several orders of magnitude. For example, in frequency analysis, signal processing, or when dealing with exponential scales, logarithmic spacing is often more appropriate Continue reading