Exploit the power of TensorFlow to create powerful image processing applications
About This Video
Learn how to build a fully-fledged image-processing application using free tools and libraries
Perform basic to advanced image (as well as video) stream processing with Python's APIs
Understand and optimize various features of TensorFlow with the help of easy-to-grasp examples.
TensorFlow has been gaining immense popularity over the past few months, owing to its power and ease of use. This video aims to help you leverage the power of TensorFlow to perform image processing. Beginning with an introduction to image processing, the video will take you through TensorFlow's API-like graph tensor, which can be used for image classification.
Starting off with basic 2D images, the video will gradually take you through recognizing more complex images, colors, shapes, and so on. Making use of the Python API, you will move on to classifying and training your model to identify more complex images such as face and expression detection, while you will also perform classification using regression.
Then you will delve into more advanced stuff such as semantic segmentation, Neural Image Caption Generation, and so on, taking advantage of TensorFlow's Deep Neural Networks. Then the video will up the ante and cover advanced topics such as Object Tracking, Video stream processing, and, finally, accelerating image processing with a GPU.
Table of contents
- Chapter 1 : TensorFlow-Keras Introduction
- Chapter 2 : CNNs with TensorFlow-Keras
- Chapter 3 : Image Classification with VGG
- Title: Learning Computer Vision with TensorFlow
- Release date: July 2017
- Publisher(s): Packt Publishing
- ISBN: 9781788292573
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