codeinpeace / awesome-coreml-models

Largest list of models for Core ML (for iOS 11+)

Awesome Core ML Models

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. 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.

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

Models

New Models

Models that are recently added.

DocumentClassification Classify news articles into 1 of 5 categories. Download | Demo | Reference

Image Processing

Models that takes image data as input and output useful information about the image.

MobileNet The network from the paper 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications', trained on the ImageNet dataset. Download | Demo | Reference	GoogLeNetPlaces Detects the scene of an image from 205 categories such as airport, bedroom, forest, coast etc. Download | Demo | Reference	Inceptionv3 Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, person etc. The top-5 error from the original publication is 5.6%. Download | Demo | Reference
Resnet50 Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, person etc. The top-5 error from the original publication is 7.8%. Download | Demo | Reference	VGG16 Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, person etc. The top-5 error from the original publication is 7.4%. Download | Demo | Reference	CarRecognition Predict the brand & model of a car. Download | Demo | Reference
TinyYOLO The Tiny YOLO network from the paper 'YOLO9000: Better, Faster, Stronger' (2016), arXiv:1612.08242 Download | Demo | Reference	AgeNet Age Classification using Convolutional Neural Networks Download | Demo | Reference	GenderNet Gender Classification using Convolutional Neural Networks Download | Demo | Reference
MNIST Predicts a handwritten digit. Download | Demo | Reference	CNNEmotions Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns Download | Demo | Reference	VisualSentimentCNN Fine-tuning CNNs for Visual Sentiment Prediction Download | Demo | Reference
Food101 This model takes a picture of a food and predicts its name Download | Demo | Reference	Oxford102 Classifying images in the Oxford 102 flower dataset with CNNs Download | Demo | Reference	FlickrStyle Finetuning CaffeNet on Flickr Style Download | Demo | Reference
RN1015k500 Predict the location where a picture was taken. Download | Demo | Reference	Nudity Classifies an image either as NSFW (nude) or SFW (not nude) Download | Demo | Reference

Style Transfer

Models that transform image to specific style.

HED_so Holistically-Nested Edge Detection. Side outputs Download | Demo | Reference	FNS-Candy Feedforward style transfer https://github.com/jcjohnson/fast-neural-style Download | Demo | Reference	FNS-Feathers Feedforward style transfer https://github.com/jcjohnson/fast-neural-style Download | Demo | Reference
FNS-La-Muse Feedforward style transfer https://github.com/jcjohnson/fast-neural-style Download | Demo | Reference	FNS-The-Scream Feedforward style transfer https://github.com/jcjohnson/fast-neural-style Download | Demo | Reference	FNS-Udnie Feedforward style transfer https://github.com/jcjohnson/fast-neural-style Download | Demo | Reference
FNS-Mosaic Feedforward style transfer https://github.com/jcjohnson/fast-neural-style Download | Demo | Reference	AnimeScale2x Process a bicubic-scaled anime-style artwork Download | Demo | Reference

Text Analysis

Models that takes text data as input and output useful information about the text.

SentimentPolarity Sentiment polarity LinearSVC. Download | Demo | Reference	DocumentClassification Classify news articles into 1 of 5 categories. Download | Demo | Reference	MessageClassifier Detect whether a message is spam. Download | Demo | Reference
NamesDT Gender Classification using DecisionTreeClassifier Download | Demo | Reference

Others

Exermote Predicts the exercise, when iPhone is worn on right upper arm. Download | Demo | Reference	GestureAI GestureAI Download | Demo | Reference

Visualization Tools

Tools that helps visualize CoreML Models

• Netron

Supported formats

List of model formats that could be converted to Core ML with examples

• Caffe
• Keras
• XGBoost
• Scikit-learn
• MXNet
• LibSVM
• Torch7

The Gold

Collections of machine learning models that could be converted to Core ML

• Caffe Model Zoo - Big list of models in Caffe format.
• TensorFlow Models - Models for TensorFlow.
• TensorFlow Slim Models - Another collection of TensorFlow Models.
• MXNet Model Zoo - Collection of MXNet models.

Individual machine learning models that could be converted to Core ML. We'll keep adjusting the list as they become converted.

• LaMem Score the memorability of pictures.
• ILGnet The aesthetic evaluation of images.
• Colorization Automatic colorization using deep neural networks.
• Illustration2Vec Estimating a set of tags and extracting semantic feature vectors from given illustrations.
• CTPN Detecting text in natural image.
• Image Analogy Find semantically-meaningful dense correspondences between two input images.
• iLID Automatic spoken language identification.
• Fashion Detection Cloth detection from images.
• Saliency The prediction of salient areas in images has been traditionally addressed with hand-crafted features.
• Face Detection Detect face from image.
• mtcnn Joint Face Detection and Alignment.
• deephorizon Single image horizon line estimation.

Contributing and License

• See the guide
• Distributed under the MIT license. See LICENSE for more information.