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Deep Learning with fastai Cookbook

You're reading from   Deep Learning with fastai Cookbook Leverage the easy-to-use fastai framework to unlock the power of deep learning

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781800208100
Length 340 pages
Edition 1st Edition
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Author (1):
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Mark Ryan Mark Ryan
Author Profile Icon Mark Ryan
Mark Ryan
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Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Getting Started with fastai 2. Chapter 2: Exploring and Cleaning Up Data with fastai FREE CHAPTER 3. Chapter 3: Training Models with Tabular Data 4. Chapter 4: Training Models with Text Data 5. Chapter 5: Training Recommender Systems 6. Chapter 6: Training Models with Visual Data 7. Chapter 7: Deployment and Model Maintenance 8. Chapter 8: Extended fastai and Deployment Features 9. Other Books You May Enjoy

Exploring a curated image location dataset

Back in Chapter 2, Exploring and Cleaning Up Data with fastai, we went through the process of ingesting and exploring a variety of datasets using fastai.

In this section, we are going to explore a special curated image dataset called COCO_TINY. This is an image location dataset. Unlike the CIFAR dataset that we used in the Training a classification model with a simple curated vision dataset recipe, which had a single labeled object in each image, the images in image location datasets are labeled with bounding boxes (which indicate where in the image a particular object occurs) as well as the name of the object. Furthermore, images in the COCO_TINY dataset can contain multiple labeled objects, as shown here:

Figure 6.17 – Labeled image from an image location dataset

In the recipe in this section, we'll ingest the dataset and apply its annotation information to create a dataloaders object for the dataset...

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