What is datasets.load_sample_image() in scikit-learn?

In a Python programming language, scikit-learn is a library for machine learning. This library contains different algorithms that include supervised learning and unsupervised learning techniques. For learning purposes, Sklean.dataset contains multiple build-in datasets like Toy datasets, Real-world datasets, etc.

The scikit-learn library contains a pair of sample images that are helpful to test different pipelines and algorithms on two-dimensional data.

• load_sample_image(image_name) is used to load an array containing a single image.
• The load_sample_images() method is used to load sample images to perform manipulations.

Syntax

sklearn.datasets.load_sample_image(image_name)

Parameters

image_name: It takes a string of an image name with format type jpg.

This string can either be china.jpg or flower.jpg because load_sample_images() has only a pair of images.

Return value

A Numpy 3D array with dimensions (height, width, and color) is returned.

Example

This code snippet demonstrates the use of the _load_sample_image()_ method which helps extract sample images from the sklearn.datasets module.

In lines 4 and 5, we extract china.jpg and flower.jpg images respectively and print their dimensions and datatype.