NumPy is a powerful library for numerical computing in Python. It is useful for image processing and manipulation. With NumPy, we can easily perform operations on large arrays of numerical data and manipulate images in a variety of ways. For example, we can create or modify images in a variety of ways, including changing the brightness, contrast, or color balance, or adding filters and effects.
NumPy can also be used to perform more complex tasks, such as feature extraction, image segmentation, and image classification. In addition, NumPy can be used to create 3D models, animations and more.
Images to talk about can be considered as made up of arrays and we can use NumPy to perform different image processing tasks from scratch. In this article, we will learn about image processing that can easily be done using NumPy. So, if you are a beginner and want to understand image processing from the very basics, this stepwise tutorial is going to be quite useful.
Image processing Video
Coding Steps for Images Processing with NumPy
(I) Loading Image
Step 1. Import NumPy library with as a name “np” and import pyplot function from matplot library as “plt” name.
Step 2. Create a NumPy array for sample data.
A. One Dimensional Array
B. Two Dimension Array
C. Three Dimension Array
Step 3. Now, reshape the dimensions of the array with the np.reshape function.
Output:-
Step 4. Now, do the mathematical operations with numpy arrays.
A. Multiplication:
B. Addition
Step 5. Convert any data type into an array.
Step 6. Do basic indexing and slicing.
Conclusion:
In conclusion, Numpy is an incredibly powerful tool for performing mathematical calculations. It allows you to work with large datasets and perform advanced calculations with ease. It is also used to construct powerful machine-learning models and is an essential tool for data scientists. With its versatile and powerful features, Numpy is a must for any data scientist looking to perform complex mathematics with ease.
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