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 resolve RuntimeError: The current Numpy installation fails to pass a sanity check in Numpy?
If you are a Python developer, you may have encountered the following error message when importing numpy: RuntimeError: The current Numpy installation fails to pass a sanity check due to a bug in the windows runtime. See this issue for more information.
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. Numpy logspace is a function that returns an array of numbers that are evenly spaced on a log scale. The syntax of the function is:
How to resolve TypeError: Cannot cast scalar from dtype(‘float64’) to dtype(‘int64’) according to the rule ‘safe’
If you are working with NumPy arrays, you may encounter a TypeError when you try to convert a float array to an integer array using the astype() method. For example, if you have an array like this:
Difference between the sep and end parameters in Python print statement
I will explain the difference between the sep and end parameters in Python print statement. These parameters are useful for formatting the output of your print statements and making them more readable and customizable. The sep parameter specifies the separator between the values that are printed. By default, it is a single space character. For Continue reading
How to permute along axis in Numpy
I will show you how to use numpy to permute the elements of an array along a given axis. Permuting means rearranging the order of the elements in a way that preserves their shape and size. For example, if we have an array of shape (2, 3, 4), we can permute the elements along the Continue reading
How to use random seed in Numpy
I will explain how to use random seed in Numpy, a popular Python library for scientific computing. Random seed is a way of controlling the randomness of Numpy’s random number generators, which are used for various purposes such as generating random data, shuffling arrays, sampling from distributions, and more.
TypeError: ufunc ‘add’ did not contain a loop with signature matching types
If you are working with pandas and numpy, you might encounter a TypeError like this: TypeError: ufunc ‘add’ did not contain a loop with signature matching types dtype (‘S21’) dtype (‘S21’) dtype (‘S21’) This error means that you are trying to add two arrays with incompatible data types. For example, you might have an array Continue reading
How to resolve AttributeError: ‘numpy.ndarray’ object has no attribute ‘function_name
If you are working with Python and numpy, you may encounter an error like this: AttributeError: ‘numpy.ndarray’ object has no attribute ‘function_name’ This error means that you are trying to call a function that does not exist for numpy arrays. Numpy arrays are objects that store multiple values of the same data type in a Continue reading
How to resolve TypeError: Cannot perform reduce with flexible type
I will explain how to resolve the error TypeError: Cannot perform reduce with flexible type that may occur when using NumPy functions on arrays with different data types. NumPy is a popular Python library for scientific computing that provides fast and efficient operations on multidimensional arrays. One of the features of NumPy is that it Continue reading
How to Use scipy.optimize.least_squares
In this blog post, I will show you how to use scipy.optimize.least_squares to solve nonlinear least squares problems in Python. Nonlinear least squares problems are optimization problems where the objective function is a sum of squared residuals, and the residuals depend on some nonlinear function of the parameters. For example, suppose we have some data Continue reading
Using scipy curve_fit to fit a function with multiple independent variables
In this blog post, I will show you how to use scipy curve_fit to fit a function with multiple independent variables. Curve fitting is a technique to find the best parameters for a model function that describes the relationship between a dependent variable and one or more independent variables. Scipy curve_fit is a function in Continue reading
How to resolve ValueError: operands could not be broadcast together with shapes
If you have ever worked with NumPy arrays, you might have encountered the ValueError: operands could not be broadcast together with shapes. This error occurs when you try to perform an operation on two arrays that have incompatible shapes. We will explain what broadcasting is, how NumPy determines the shapes of the operands, and how Continue reading