Next, we’ll create a Swift project in Xcode. Today’s blog post is broken down into four parts.įirst, I’ll give some background on CoreML, including what it is and why we should use it when creating iPhone and iOS apps that utilize deep learning.įrom there, we’ll write a script to convert our trained Keras model from a HDF5 file to a serialized CoreML model - it’s an extremely easy process. Looking for the source code to this post? Jump Right To The Downloads Section Running Keras models on iOS with CoreML To learn how you can deploy a trained Keras model to iOS and build a deep learning iPhone app, just keep reading. You can see an example of a Pokedex in action at the top of this blog post, but again, feel free to swap out my Keras model for your own - the process is quite simple and straightforward as you’ll see later in this guide. Using a Pokedex you can take a picture of a Pokemon (animal-like creatures that exist in the world of Pokemon) and the Pokedex will automatically identify the creature for for you, providing useful information and statistics, such as the Pokemon’s height, weight, and any special abilities it may have. A Pokedex is a device that exists in the world of Pokemon, a popular TV show, video game, and trading card series (I was/still am a huge Pokemon nerd). To be clear, I’m not a mobile developer by any stretch of the imagination, and if I can do it, I’m confident you can do it as well.įeel free to use the code in today’s post as a starting point for your own application.īut personally, I’m going to continue the theme of this series and build a Pokedex. My goal today is to show you how simple it is to deploy your Keras model to your iPhone and iOS using CoreML.
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