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You're reading from  Hands-On Image Processing with Python

Product typeBook
Published inNov 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781789343731
Edition1st Edition
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Author (1)
Sandipan Dey
Sandipan Dey
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Sandipan Dey

Sandipan Dey is a data scientist with a wide range of interests, covering topics such as machine learning, deep learning, image processing, and computer vision. He has worked in numerous data science fields, working with recommender systems, predictive models for the events industry, sensor localization models, sentiment analysis, and device prognostics. He earned his master's degree in computer science from the University of Maryland, Baltimore County, and has published in a few IEEE Data Mining conferences and journals. He has earned certifications from 100+ MOOCs on data science, machine learning, deep learning, image processing, and related courses. He is a regular blogger (sandipanweb) and is a machine learning education enthusiast.
Read more about Sandipan Dey

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Questions


  1. Use the scikit-image library's functions to read a collection of images and display them as a montage.
  2. Use the scipy ndimage and misc modules' functions to zoom, crop, resize, and apply Affine transformation to an image.
  3. Create a Python remake of the Gotham Instagram filter (https://github.com/lukexyz/CV-Instagram-Filters) (hint: manipulate an image with the PIL split(), merge(), and numpy interp() functions to create a channel interpolation (https://www.youtube.com/watch?v=otLGDpBglEA&feature=player_embedded)).
  4. Use scikit-image's warp() function to implement the swirl transform. Note that the swirl transform can also be expressed with the following equations:
  1. Implement the wave transform (hint: use scikit-image's warp()) given by the following:
  1. Use PIL to load an RGB .png file with a palette and convert into a grayscale image. This problem is taken from this post: https://stackoverflow.com/questions/51676447/python-use-pil-to-load-png-file-gives-strange-results/51678271#51678271. Convert the following RGB image (from the VOC2012 dataset) into a grayscale image by indexing the palette:
  1. Make a 3D plot for each of the color channels of the parrot image used in this chapter (hint: use the mpl_toolkits.mplot3d module's plot_surface() function and NumPy's meshgrid() function).
  1. Use scikit-image's transform module's ProjectiveTransform to estimate the homography matrix from a source to a destination image and use the inverse() function to embed the Lena image (or yours) in the blank canvas as shown in the following:

Input Image

Output Image

First try to solve the problems on your own. For your reference, the solutions can be found here: https://sandipanweb.wordpress.com/2018/07/30/some-image-processing-problems/.

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Author (1)

author image
Sandipan Dey

Sandipan Dey is a data scientist with a wide range of interests, covering topics such as machine learning, deep learning, image processing, and computer vision. He has worked in numerous data science fields, working with recommender systems, predictive models for the events industry, sensor localization models, sentiment analysis, and device prognostics. He earned his master's degree in computer science from the University of Maryland, Baltimore County, and has published in a few IEEE Data Mining conferences and journals. He has earned certifications from 100+ MOOCs on data science, machine learning, deep learning, image processing, and related courses. He is a regular blogger (sandipanweb) and is a machine learning education enthusiast.
Read more about Sandipan Dey