Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentationWe'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.If you've converted a Core ML model, feel free to submit a pull request.Recently, we've included visualization tools. And here's one Netron.

ModelsImage - Metadata/TextModels that take image data as input and output useful information about the image. * TextDetection - Detecting text using Vision built-in model in real-time. Download | Demo | Reference * PhotoAssessment - Photo Assessment using Core ML and Metal. Download | Demo | Reference * PoseEstimation - Estimating human pose from a picture for mobile. Download | Demo | Reference * MobileNet - Detects the dominant objects present in an image. Download | Demo | Reference * Places CNN - Detects the scene of an image from 205 categories such as bedroom, forest, coast etc. Download | Demo | Reference * Inception v3 - Detects the dominant objects present in an image. Download | Demo | Reference * ResNet50 - Detects the dominant objects present in an image. Download | Demo | Reference * VGG16 - Detects the dominant objects present in an image. Download | Demo | Reference * Car Recognition - Predict the brand & model of a car. Download | Demo | Reference * YOLO - Recognize what the objects are inside a given image and where they are in the image. Download | Demo | Reference * AgeNet - Predict a person's age from one's portrait. Download | Demo | Reference * GenderNet - Predict a person's gender from one's portrait. Download | Demo | Reference * MNIST - Predict handwritten (drawn) digits from images. Download | Demo | Reference * EmotionNet - Predict a person's emotion from one's portrait. Download | Demo | Reference

Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation

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.

If you've converted a Core ML model, feel free to submit a pull request.

Recently, we've included visualization tools. And here's one Netron.

Models

Image - Metadata/Text

Models that take image data as input and output useful information about the image. * TextDetection - Detecting text using Vision built-in model in real-time. Download | Demo | Reference * PhotoAssessment - Photo Assessment using Core ML and Metal. Download | Demo | Reference * PoseEstimation - Estimating human pose from a picture for mobile. Download | Demo | Reference * MobileNet - Detects the dominant objects present in an image. Download | Demo | Reference * Places CNN - Detects the scene of an image from 205 categories such as bedroom, forest, coast etc. Download | Demo | Reference * Inception v3 - Detects the dominant objects present in an image. Download | Demo | Reference * ResNet50 - Detects the dominant objects present in an image. Download | Demo | Reference * VGG16 - Detects the dominant objects present in an image. Download | Demo | Reference * Car Recognition - Predict the brand & model of a car. Download | Demo | Reference * YOLO - Recognize what the objects are inside a given image and where they are in the image. Download | Demo | Reference * AgeNet - Predict a person's age from one's portrait. Download | Demo | Reference * GenderNet - Predict a person's gender from one's portrait. Download | Demo | Reference * MNIST - Predict handwritten (drawn) digits from images. Download | Demo | Reference * EmotionNet - Predict a person's emotion from one's portrait. Download | Demo | Reference