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Hands-On Computer Vision with TensorFlow 2

You're reading from   Hands-On Computer Vision with TensorFlow 2 Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781788830645
Length 372 pages
Edition 1st Edition
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Authors (2):
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Eliot Andres Eliot Andres
Author Profile Icon Eliot Andres
Eliot Andres
Benjamin Planche Benjamin Planche
Author Profile Icon Benjamin Planche
Benjamin Planche
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Table of Contents (16) Chapters Close

Preface 1. Section 1: TensorFlow 2 and Deep Learning Applied to Computer Vision FREE CHAPTER
2. Computer Vision and Neural Networks 3. TensorFlow Basics and Training a Model 4. Modern Neural Networks 5. Section 2: State-of-the-Art Solutions for Classic Recognition Problems
6. Influential Classification Tools 7. Object Detection Models 8. Enhancing and Segmenting Images 9. Section 3: Advanced Concepts and New Frontiers of Computer Vision
10. Training on Complex and Scarce Datasets 11. Video and Recurrent Neural Networks 12. Optimizing Models and Deploying on Mobile Devices 13. Migrating from TensorFlow 1 to TensorFlow 2 14. Assessments 15. Other Books You May Enjoy

On a local machine

Coding your model on your computer is often the fastest way to get started. As you have access to a familiar environment, you can easily change your code as often as needed. However, personal computers, especially laptops, lack the computing power to train a computer vision model. Training on a GPU may be between 10 and 100 times faster than using a CPU. This is why it is recommended to use a GPU.

Even if your computer has a GPU, only very specific models can run TensorFlow. Your GPU must be compatible with CUDA, NVIDIA's computing library. At the time of writing, the latest version of TensorFlow requires a CUDA compute capability of 3.5 or higher.

Some laptops are compatible with external GPU enclosures, but this defeats the purpose of a portable computer. Instead, a practical way is to run your model on a remote computer that has a GPU.

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