With rapid advancements in technology, mobile apps are now utilizing all these technologies. A large number of technologies have been introduced in recent years. However, one of the biggest innovation tech industries ever came across is Deep Learning technology. It is the subset of Machine Learning inside Artificial Intelligence and contains the characteristics of both. Due to the combination of two popular technologies, you will find Deep Learning as the most popular technology now. It has the ability to learn from unstructured data without any supervision. You can create a deep neural network to make it function within your app that benefits you in multiple ways.
Using Deep Learning technology within the iOS app is more difficult than that of Android. You are short on time but want to create a Deep Learning iOS app, then this article is for you. Have a look at how to create an iOS app with this amazing technology in just five minutes.
Training/Preparing Your Model
To start developing an iOS app with deep learning capability, you need to have Python3, MacBook and latest XCode installed on your computer. You can buy a Mac and get the XCode with it and install all the necessary libraries required for running Python3. If you know about Keras API used for deep learning, then you must have an idea that it loads the CIFAR dataset and trains CNN on it. For a working iOS app, make a few adjustments according to your iOS app with the help of Keras API integration documentation. First, change the number of epochs to only 1 which will accelerate the training process. Then, you need to change the data-augmentation parameter from true to false. It will train the data exactly as provided without adjusting the training images. Within the page, you’ll find the ‘Convert Your Model’ section, paste that code on your script. While converting your model, avoiding violating the guidelines from Apple.
Start Building iOS App
Now comes the most important step where you begin the creation of your iOS app using Keras. You need to make the script run with Keras model and for that small changes are required. Update the elements like input_names, image_input_names and class_labels. It will make the script work according to your model. Build your iOS by starting the classification of images while the model is being simmered. Download the iOS XCode project that is used for image classification in a model. Use the Apple XCode project for your model and you are done to go with the build.
Fix The Broken Stuff
There are certain things you need to take care of as it doesn’t go well with the app. You must add the trained model to the XCode project. You also need to update the code so that you can use the model. Within CIFAR, the picture size is slightly different than what you had taken from your iPhone. For this reason, you need to scale the images. The newly trained model should be copied to the app project folder. It should be placed under Vision+ML/Example/Model/CIFAR.mlmodel, the next step is to link it using the build phases of XCode. After putting your trained model within the project, update the code found in ImageClassificationViewController.swift. It helps in recognizing the new model after it you are all set to manage the image sizing.
Fix Sizing Issues
The model was made using Keras, the expected image size is 64 x 64 x 3. You need to adjust your code according to the prescribed image size. However, the default image size is 224 x 224 x 3. You can view this size by clicking on the model file MobileNer.mlmodel in XCode. You will get you to see the expected size of the image under the prediction option. You are confused about how to resize the image using code, search about it and you will find multiple codes available in Swift3. You just need to copy that Swift3 code for your project and call the new function made by the iOS application development Company. Afterward, change the starting lines of update classifications and you are done to run your model. Just click the Play button and enjoy your newly trained model application.
Conclusion
Deep Learning is among the most powerful and useful technologies that made the machine learning process even easier. Apple contains multiple restrictions from mobile apps. Thus you must create a Deep Learning app that fulfills all specifications and doesn’t violate any of the guidelines. This article provides you with every detail on creating an iOS app with Deep Learning functionality. Using the steps mentioned in this article, you can create an amazing deep learning iOS app within just five minutes. It doesn’t only save your time but also provides you with a guideline to create an iOS app with this technology in the smartest way.
Using Deep Learning technology within the iOS app is more difficult than that of Android. You are short on time but want to create a Deep Learning iOS app, then this article is for you. Have a look at how to create an iOS app with this amazing technology in just five minutes.
Training/Preparing Your Model
To start developing an iOS app with deep learning capability, you need to have Python3, MacBook and latest XCode installed on your computer. You can buy a Mac and get the XCode with it and install all the necessary libraries required for running Python3. If you know about Keras API used for deep learning, then you must have an idea that it loads the CIFAR dataset and trains CNN on it. For a working iOS app, make a few adjustments according to your iOS app with the help of Keras API integration documentation. First, change the number of epochs to only 1 which will accelerate the training process. Then, you need to change the data-augmentation parameter from true to false. It will train the data exactly as provided without adjusting the training images. Within the page, you’ll find the ‘Convert Your Model’ section, paste that code on your script. While converting your model, avoiding violating the guidelines from Apple.
Start Building iOS App
Now comes the most important step where you begin the creation of your iOS app using Keras. You need to make the script run with Keras model and for that small changes are required. Update the elements like input_names, image_input_names and class_labels. It will make the script work according to your model. Build your iOS by starting the classification of images while the model is being simmered. Download the iOS XCode project that is used for image classification in a model. Use the Apple XCode project for your model and you are done to go with the build.
Fix The Broken Stuff
There are certain things you need to take care of as it doesn’t go well with the app. You must add the trained model to the XCode project. You also need to update the code so that you can use the model. Within CIFAR, the picture size is slightly different than what you had taken from your iPhone. For this reason, you need to scale the images. The newly trained model should be copied to the app project folder. It should be placed under Vision+ML/Example/Model/CIFAR.mlmodel, the next step is to link it using the build phases of XCode. After putting your trained model within the project, update the code found in ImageClassificationViewController.swift. It helps in recognizing the new model after it you are all set to manage the image sizing.
Fix Sizing Issues
The model was made using Keras, the expected image size is 64 x 64 x 3. You need to adjust your code according to the prescribed image size. However, the default image size is 224 x 224 x 3. You can view this size by clicking on the model file MobileNer.mlmodel in XCode. You will get you to see the expected size of the image under the prediction option. You are confused about how to resize the image using code, search about it and you will find multiple codes available in Swift3. You just need to copy that Swift3 code for your project and call the new function made by the iOS application development Company. Afterward, change the starting lines of update classifications and you are done to run your model. Just click the Play button and enjoy your newly trained model application.
Conclusion
Deep Learning is among the most powerful and useful technologies that made the machine learning process even easier. Apple contains multiple restrictions from mobile apps. Thus you must create a Deep Learning app that fulfills all specifications and doesn’t violate any of the guidelines. This article provides you with every detail on creating an iOS app with Deep Learning functionality. Using the steps mentioned in this article, you can create an amazing deep learning iOS app within just five minutes. It doesn’t only save your time but also provides you with a guideline to create an iOS app with this technology in the smartest way.
Also Read: The Useful Mobile App Development Tools List
