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Python Image Processing Cookbook

You're reading from   Python Image Processing Cookbook Over 60 recipes to help you perform complex image processing and computer vision tasks with ease

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789537147
Length 438 pages
Edition 1st Edition
Languages
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Author (1):
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Sandipan Dey Sandipan Dey
Author Profile Icon Sandipan Dey
Sandipan Dey
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Toc

Table of Contents (11) Chapters Close

Preface 1. Image Manipulation and Transformation 2. Image Enhancement FREE CHAPTER 3. Image Restoration 4. Binary Image Processing 5. Image Registration 6. Image Segmentation 7. Image Classification 8. Object Detection in Images 9. Face Recognition, Image Captioning, and More 10. Other Books You May Enjoy

Deep instance segmentation

Similar to deep semantic segmentation, deep instance segmentation also assigns a label to each pixel in an image. The labels collectively produce pixel-based masks for each object in an input image. The difference between these two techniques is that even if multiple objects have the same class label (for example, two cats and a dog in the input image shown in the following figure), the instance segmentation should report each object instance as a unique one (for example, a total of three unique objects: two cats and a dog), as opposed to the semantic segmentation that reports the total number of unique class labels found (for example, two unique classes, namely a cat and dog), as shown in the following screenshot:

In this recipe, you will learn how to use a pretrained mask R-CNN deep learning model to perform instance segmentation.

The region-based...

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