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https://github.com/SwiftBrain/awesome-CoreML-models

Collection of models for Core ML
https://github.com/SwiftBrain/awesome-CoreML-models

List: awesome-CoreML-models

ai awesome awesome-list coreml coreml-framework coreml-models coremltools deep-learning ios ios11 machine-learning machine-learning-models model swift

Last synced: 3 months ago
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Collection of models for Core ML

Awesome Lists containing this project

README 

        
 



# Awesome Core ML models [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



This repository has a collection of Open Source machine learning models which work with Apples **Core ML** standard.



Apple has published some of their own models. They can be downloaded [here](https://developer.apple.com/machine-learning/).

Those published models are: **SqueezeNet, Places205-GoogLeNet, ResNet50, Inception v3, VGG16** and will not be republished in this repository.



## Contributing

If you want your model added simply create a pull request with your repository and model added. In order to keep the quality of this repository you have to conform to this project structure (taken from **@hollance**).



```

├── Convert

    ├── coreml.py

    ├── mobilenet_deploy.prototxt

    └── synset_words.txt

```



There has to be a **Convert** directory with a Python script and additional data to reproduce this model on your own. If your model requires a huge amount of space please include a script which downloads those files.



```

├── MobileNetCoreML

│   ├── *.swift

├── MobileNetCoreML.xcodeproj

│   ├── project.pbxproj

│   └── project.xcworkspace

│       └── contents.xcworkspacedata

├── README.markdown

```



You also have to have an Xcode project where the user can test the model (sample data included would be nice).



This is a template for the README to copy:

```

### Name of your model

**Model:** [Model.mlmodel](link for downloading) 


**Description:** Short description 


**Author:** [Author](https://github.com/author) 


**Reference:** [Name of reference](URL to reference) 


**Example:** [Your example project](URL to example project) 


```

## Models



### MobileNet

**Model:** [MobileNet.mlmodel](https://github.com/hollance/MobileNet-CoreML/raw/master/MobileNet.mlmodel) 


**Description:** Object detection, finegrain classification, face attributes and large scale geo-localization 


**Author:** [Matthijs Hollemans](https://github.com/hollance) 


**Reference:** [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://arxiv.org/abs/1704.04861v1) 


**Example:** [MobileNet-CoreML](https://github.com/hollance/MobileNet-CoreML) 



### MNIST

**Model:** [MNIST.mlmodel](https://github.com/ph1ps/MNIST-CoreML/raw/master/MNISTPrediction/MNIST.mlmodel) 


**Description:** Handwritten digit classification 


**Author:** [Philipp Gabriel](https://github.com/ph1ps) 


**Reference:** [MNIST handwritten digit database](http://yann.lecun.com/exdb/mnist/) 


**Example:** [MNIST-CoreML](https://github.com/ph1ps/MNIST-CoreML) 



### Food101

**Model:** [Food101.mlmodel](https://drive.google.com/open?id=0B5TjkH3njRqnVjBPZGRZbkNITjA) 


**Description:** Food classification 


**Author:** [Philipp Gabriel](https://github.com/ph1ps) 


**Reference:** [UPMC Food-101](http://visiir.lip6.fr/explore) 


**Example:** [Food101-CoreML](https://github.com/ph1ps/Food101-CoreML) 



### SentimentPolarity

**Model:** [SentimentPolarity](https://github.com/cocoa-ai/SentimentCoreMLDemo/raw/master/SentimentPolarity/Resources/SentimentPolarity.mlmodel) 


**Description:** Sentiment Polarity Analysis 


**Author:** [Vadym Markov](https://github.com/vadymmarkov) 


**Reference:** [Epinions.com reviews dataset](http://boston.lti.cs.cmu.edu/classes/95-865-K/HW/HW3/) 


**Example:** [SentimentCoreMLDemo](https://github.com/cocoa-ai/SentimentCoreMLDemo) 



### VisualSentimentCNN

**Model:** [VisualSentimentCNN](https://drive.google.com/open?id=0B1ghKa_MYL6mZ0dITW5uZlgyNTg) 


**Description:** Visual Sentiment Prediction 


**Author:** [Image Processing Group - BarcelonaTECH - UPC](https://github.com/imatge-upc) 


**Reference:** [From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction](https://github.com/imatge-upc/sentiment-2017-imavis) 


**Example:** [SentimentVisionDemo](https://github.com/cocoa-ai/SentimentVisionDemo) 



### AgeNet

**Model:** [AgeNet](https://drive.google.com/file/d/0B1ghKa_MYL6mT1J3T1BEeWx4TWc/view?usp=sharing) 


**Description:** Age Classification 


**Author:** [Gil Levi and Tal Hassner](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/) 


**Reference:** [Age and Gender Classification using Convolutional Neural Networks](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/CNN_AgeGenderEstimation.pdf) 


**Example:** [FacesVisionDemo](https://github.com/cocoa-ai/FacesVisionDemo) 



### GenderNet

**Model:** [GenderNet](https://drive.google.com/file/d/0B1ghKa_MYL6mYkNsZHlyc2ZuaFk/view?usp=sharing) 


**Description:** Gender Classification 


**Author:** [Gil Levi and Tal Hassner](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/) 


**Reference:** [Age and Gender Classification using Convolutional Neural Networks](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/CNN_AgeGenderEstimation.pdf) 


**Example:** [FacesVisionDemo](https://github.com/cocoa-ai/FacesVisionDemo) 



### CNNEmotions

**Model:** [CNNEmotions](https://drive.google.com/file/d/0B1ghKa_MYL6mTlYtRGdXNFlpWDQ/view?usp=sharing) 


**Description:** Emotion Recognition 


**Author:** [Gil Levi and Tal Hassner](http://www.openu.ac.il/home/hassner/projects/cnn_emotions/) 


**Reference:** [Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns](http://www.openu.ac.il/home/hassner/projects/cnn_emotions/LeviHassnerICMI15.pdf) 


**Example:** [FacesVisionDemo](https://github.com/cocoa-ai/FacesVisionDemo) 



### NamesDT

**Model:** [NamesDT](https://github.com/cocoa-ai/NamesCoreMLDemo/raw/master/Names/Resources/NamesDT.mlmodel) 


**Description:** Gender Classification from first names 


**Author:** [http://nlpforhackers.io](http://nlpforhackers.io) 


**Reference:** [Is it a boy or a girl? An introduction to Machine Learning](http://nlpforhackers.io/introduction-machine-learning/) 


**Example:** [NamesCoreMLDemo](https://github.com/cocoa-ai/NamesCoreMLDemo) 



### Oxford102

**Model:** [Oxford102](https://drive.google.com/file/d/0B1ghKa_MYL6meDBHT2NaZGxkNzQ/view?usp=sharing) 


**Description:** Flower Classification 


**Author:** [Jimmie Goode](https://github.com/jimgoo) 


**Reference:** [Classifying images in the Oxford 102 flower dataset with CNNs](http://jimgoo.com/flower-power/) 


**Example:** [FlowersVisionDemo](https://github.com/cocoa-ai/FlowersVisionDemo) 



### FlickrStyle

**Model:** [FlickrStyle](https://drive.google.com/file/d/0B1ghKa_MYL6maFFWR3drLUFNQ1E/view?usp=sharing) 


**Description:** Image Style Classification 


**Author:** [Sergey Karayev](https://gist.github.com/sergeyk) 


**Reference:** [Recognizing Image Style](http://sergeykarayev.com/files/1311.3715v3.pdf) 


**Example:** [StylesVisionDemo](https://github.com/cocoa-ai/StylesVisionDemo) 



## Model Demonstration App





    





    




**Description:** Discover, download, on-device-compile & launch different image processing CoreML models on iOS. 


**Author:** [Eugene Bokhan](https://github.com/eugenebokhan) 


**Source:** [Awesome ML](https://github.com/eugenebokhan/Awesome-ML) 


**Lincese:** [BSD 3-Clause](https://github.com/eugenebokhan/Awesome-ML/blob/master/LICENSE.md)