Dog Classifier iOS App

This iOS app uses CoreML and a neural network classifier built by James Requa, a graduate from Udacity's Deep Learning Nanodegree Foundation program, and it can detect a dog and determine its breed from an image or live video.

Note: You must use Xcode 9 (supports iOS 11) to build this app.

Structure

• iOS/
  • Contains Xcode project for iOS application
• ML/
  • images/
    • Test images to use for classification
  • models/
    • Keras and Core ML models
  • scripts/
    • Python scripts for creating and testing models

Requirements

• To run the iOS project, you must use Xcode 9
• To run any of the Python scripts, use the coreml-environment.yml file to create a Anaconda environment with the correct dependencies
• To run the Python script which generates a Core ML (.mlmodel) model, you must be running macOS 10.13 (High Sierra)

Note: Apple software can be downloaded from Apple's download page.

How it Works

The iOS app relies on two neural networks — Resnet50 and StudentDogModel (the dog classifier). When an image or video frame is processed by the app, it first goes through the Resnet50 model to determine if a dog is present. If a dog is present, then a second classification is done using the StudentDogModel to determine the dog's breed.