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.
Models that are recently added.
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| DocumentClassification Classify news articles into 1 of 5 categories. Download | Demo | Reference |
Models that takes image data as input and output useful information about the image.
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
Models that transform image to specific style.
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| 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 |
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| 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 |
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| 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 |
Models that takes text data as input and output useful information about the text.
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| 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 |
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| NamesDT Gender Classification using DecisionTreeClassifier Download | Demo | Reference |
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| Exermote Predicts the exercise, when iPhone is worn on right upper arm. Download | Demo | Reference |
GestureAI GestureAI Download | Demo | Reference |
List of model formats that could be converted to Core ML with examples
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.
- See the guide
- Distributed under the MIT license. See LICENSE for more information.