#Keras data augmentation rotation how to
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Training a machine learning model on this data may result in us modeling the distribution exactly - however, in real-world applications, data rarely follows such a nice, neat distribution. LetвЂ™s consider Figure 2 ( left) of a normal distribution with zero mean and unit variance. This type of data augmentation increases the generalizability of our networks. Right: Adding a small amount of random вЂњjitterвЂќ to the distribution. A simple data augmentation example Figure 2: Left: A sample of 250 data points that follow a normal distribution exactly. Given that our network is constantly seeing new, slightly modified versions of the input data, the network is able to learn more robust features.ДЄt testing time we do not apply data augmentation and simply evaluate our trained network on the unmodified testing data - in most cases, youвЂ™ll see an increase in testing accuracy, perhaps at the expense of a slight dip in training accuracy. Our goal when applying data augmentation is to increase the generalizability of the model. What is data augmentation?Дata augmentation encompasses a wide range of techniques used to generate вЂњnewвЂќ training samples from the original ones by applying random jitters and perturbations (but at the same time ensuring that the class labels of the data are not changed).

#Keras data augmentation rotation how to

Combining dataset generation and in-place augmentationДЇrom there IвЂ™ll teach you how to apply data augmentation to your own datasets (using all three methods) using KerasвЂ™ ImageDataGenerator class.In-place/on-the-fly data augmentation (most common).Dataset generation and data expansion via data augmentation (less common).IвЂ™ll then cover the three types of data augmentation youвЂ™ll see when training deep neural networks: WeвЂ™ll start this tutorial with a discussion of data augmentation and why we use it. Update: This blog post is now TensorFlow 2+ compatible!

#Keras data augmentation rotation code

Looking for the source code to this post? Jump Right To The Downloads Section Keras ImageDataGenerator and Data Augmentation To learn more about data augmentation, including using KerasвЂ™ ImageDataGenerator class, just keep reading!

Learn how to apply data augmentation with Keras and the ImageDataGenerator class.

Dispel any confusion you have surrounding data augmentation.

Learn about three types of data augmentation.

Inside the rest of todayвЂ™s tutorial you will: IвЂ™ll help you clear up some of the confusion regarding data augmentation (and give you the context you need to successfully apply it). Technically, all the answers are correct - but the only way you know if a given definition of data augmentation is correct is via the context of its application. Instead, the ImageDataGenerator accepts the original data, randomly transforms it, and returns only the new, transformed data.Д«ut remember how I said this was a trick question?

ItвЂ™s not taking the original data, randomly transforming it, and then returning both the original data and transformed data. ThatвЂ™s right - the Keras ImageDataGenerator class is not an вЂњadditiveвЂќ operation.

Training the CNN on this randomly transformed batch (i.e., the original data itself is not used for training).

Replacing the original batch with the new, randomly transformed batch.

#Keras data augmentation rotation series

Taking this batch and applying a series of random transformations to each image in the batch (including random rotation, resizing, shearing, etc.).Accepting a batch of images used for training.While the word вЂњaugmentвЂќ means to make something вЂњgreaterвЂќ or вЂњincreaseвЂќ something (in this case, data), the Keras ImageDataGenerator class actually works by: Only 5% of respondents answered this trick question вЂњcorrectlyвЂќ (at least if youвЂ™re using KerasвЂ™ ImageDataGenerator class).ДЄgain, itвЂ™s a trick question so thatвЂ™s not exactly a fair assessment, but hereвЂ™s the deal: Here are the results: Figure 1: My twitter poll on the concept of Data Augmentation. The question was simple - data augmentation does which of the following?

Knowing that I was going to write a tutorial on data augmentation, two weekends ago I decided to have some fun and purposely post a semi-trick question on my Twitter feed. IвЂ™ll also dispel common confusions surrounding what data augmentation is, why we use data augmentation, and what it does/does not do. In todayвЂ™s tutorial, you will learn how to use KerasвЂ™ ImageDataGenerator class to perform data augmentation.

#Keras data augmentation rotation download

Click here to download the source code to this post