Displaying 1 to 7 from 7 results

Awesome-CoreML-Models - Largest list of models for Core ML (for iOS 11+)

  •    HTML

We've put up the largest collection of machine learning models in Core ML format, to help iOS, macOS, tvOS, and watchOS developers experiment with machine learning techniques. We've created a site with better visualization of the models CoreML.Store, and are working on more advance features. If you've converted a Core ML model, feel free to submit an issue.

ios-learning-materials - 📚Curated list of articles, web-resources, tutorials and code repositories that may help you dig a little bit deeper into iOS

  •    Swift

Last Update: 10/October/2018. Curated list of articles, web-resources, tutorials, Stack Overflow and Quora Q&A, GitHubcode repositories and useful resources that may help you dig a little bit deeper into iOS. All the resources are split into sub-categories which simlifies navigation and management. Feel free to use and suggest something to learn (iOS related of course 😜).

Food101-CoreML - A CoreML model which classifies images of food

  •    Swift

This is the Food101 dataset implemented in Apple's new framework called CoreML. The Food101 dataset can predict foods from images. The model was built with Keras 1.2.2 and is a fine-tuned InceptionV3 model. To test this model you can open the Food101Prediction.xcodeproj and run it on your device (iOS 11 and Xcode 9 is required). To test further images just add them to the project and replace my testing with yours.




MNIST-CoreML - Predict handwritten digits with CoreML

  •    Python

This is the MNIST dataset implemented in Apple's new framework CoreML. The MNIST dataset can predict handwritten (drawn) digits from an image and outputs a prediction from 0-9. The model was built with Keras 1.2.2. To test this model you can open the MNISTPrediction.xcodeproj and run it on your device (iOS 11 and Xcode 9 is required). To test further images just add them to the project and replace my testing with yours.

CoreML-samples - Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools

  •    Jupyter

This is the sample code for Core ML using ResNet50 provided by Apple. ResNet50 can categorize the input image to 1000 pre-trained categories. What's more, this includes a sample code for coremltools converting keras model to mlmodel.