Editing Images with scikit-image

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Editing Images with scikit-image

A picture is worth 1,000 words, and being able to work with images from your code can be worth billions (if you ask the engineers at Instagram). Work with image data is a skill that has become increasingly valuable as more of the world has access to a camera in their pocket. Images are data just like everything else that we have access to on our computers, and with `scikit-image`, we're able to manipulate and analyze this data from our Python code. In this Hands-On Lab, we'll go through the process of reading in an existing image and making modifications to it programmatically. _Warning:_ This is a lab designed as part of a professional level course and is difficult. The lab asks you to accomplish something using exact methods and functionality of the `scikit-image` library that might not have been covered in lessons. To feel comfortable completing this lab, you'll want to know how to do the following: - Use `scikit-image`. Watch the "Using SciKit-image" lessons from the [Using Python's Math, Science, and Engineering Libraries](https://linuxacademy.com/cp/modules/view/id/621) course. - Comfortability reading the [scikit-image documentation](https://scikit-image.org/docs/stable/) to find new functions and methods to use to accomplish your goal.

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Lab Info

Level

Intermediate

Last updated

Sep 07, 2025

Duration

45m

Challenge

Install scikit-image

Before we can edit images we'll need to install scikit-image.
Challenge

Load the `highrise.jpg` Image into Memory.

To test the image changes that we'd like to automate, we're going to work with a local image called highrise.jpg. This can be found at /home/cloud_user/highrise.jpg.
Challenge

Create a Black and White Version of `highrise.jpg`.

The first modification we'd like to automate is the conversion of an image from being a colored/RGB image to being a black and white or grayscale image. This is a common task, and we can leverage code from within the skimage.colors module to do nearly all of the work.
Challenge

Create a Copy of `highrise.jpg` with a Circular Mask.

Adding a mask to our image is a much more complicated task that requires us to index and slice the array that is backing our image's data. To create a copy of the highrise image, we can use the copy method on our existing image object. To do the actual masking, it is worth looking at the code from this example in the scikit-image documentation.

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