{"id":13407627,"url":"https://github.com/SwiftBrain/awesome-CoreML-models","last_synced_at":"2025-03-14T12:31:18.649Z","repository":{"id":38206413,"uuid":"93711179","full_name":"SwiftBrain/awesome-CoreML-models","owner":"SwiftBrain","description":"Collection of models for Core ML ","archived":false,"fork":false,"pushed_at":"2019-12-07T02:09:02.000Z","size":17875,"stargazers_count":559,"open_issues_count":4,"forks_count":62,"subscribers_count":33,"default_branch":"master","last_synced_at":"2024-04-14T09:57:33.917Z","etag":null,"topics":["ai","awesome","awesome-list","coreml","coreml-framework","coreml-models","coremltools","deep-learning","ios","ios11","machine-learning","machine-learning-models","model","swift"],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/SwiftBrain.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-06-08T05:36:55.000Z","updated_at":"2024-03-18T10:29:56.000Z","dependencies_parsed_at":"2022-08-19T11:30:39.589Z","dependency_job_id":null,"html_url":"https://github.com/SwiftBrain/awesome-CoreML-models","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwiftBrain%2Fawesome-CoreML-models","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwiftBrain%2Fawesome-CoreML-models/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwiftBrain%2Fawesome-CoreML-models/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SwiftBrain%2Fawesome-CoreML-models/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SwiftBrain","download_url":"https://codeload.github.com/SwiftBrain/awesome-CoreML-models/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":221467851,"owners_count":16827234,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","awesome","awesome-list","coreml","coreml-framework","coreml-models","coremltools","deep-learning","ios","ios11","machine-learning","machine-learning-models","model","swift"],"created_at":"2024-07-30T20:00:45.651Z","updated_at":"2024-10-25T22:30:31.898Z","avatar_url":"https://github.com/SwiftBrain.png","language":null,"readme":"\u003cimg src=\"core-ml.png\" align=\"left\" width=\"64\"\u003e \n\n# Awesome Core ML models [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nThis repository has a collection of Open Source machine learning models which work with Apples **Core ML** standard.\n\nApple has published some of their own models. They can be downloaded [here](https://developer.apple.com/machine-learning/).\nThose published models are: **SqueezeNet, Places205-GoogLeNet, ResNet50, Inception v3, VGG16** and will not be republished in this repository.\n\n## Contributing\nIf 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**).\n\n```\n├── Convert\n    ├── coreml.py\n    ├── mobilenet_deploy.prototxt\n    └── synset_words.txt\n```\n\nThere 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.\n\n```\n├── MobileNetCoreML\n│   ├── *.swift\n├── MobileNetCoreML.xcodeproj\n│   ├── project.pbxproj\n│   └── project.xcworkspace\n│       └── contents.xcworkspacedata\n├── README.markdown\n```\n\nYou also have to have an Xcode project where the user can test the model (sample data included would be nice).\n\nThis is a template for the README to copy:\n```\n### Name of your model\n**Model:** [Model.mlmodel](link for downloading) \u003cbr /\u003e\n**Description:** Short description \u003cbr /\u003e\n**Author:** [Author](https://github.com/author) \u003cbr /\u003e\n**Reference:** [Name of reference](URL to reference) \u003cbr /\u003e\n**Example:** [Your example project](URL to example project) \u003cbr /\u003e\n```\n## Models\n\n### MobileNet\n**Model:** [MobileNet.mlmodel](https://github.com/hollance/MobileNet-CoreML/raw/master/MobileNet.mlmodel) \u003cbr /\u003e\n**Description:** Object detection, finegrain classification, face attributes and large scale geo-localization \u003cbr /\u003e\n**Author:** [Matthijs Hollemans](https://github.com/hollance) \u003cbr /\u003e\n**Reference:** [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://arxiv.org/abs/1704.04861v1) \u003cbr /\u003e\n**Example:** [MobileNet-CoreML](https://github.com/hollance/MobileNet-CoreML) \u003cbr /\u003e\n\n### MNIST\n**Model:** [MNIST.mlmodel](https://github.com/ph1ps/MNIST-CoreML/raw/master/MNISTPrediction/MNIST.mlmodel) \u003cbr /\u003e\n**Description:** Handwritten digit classification \u003cbr /\u003e\n**Author:** [Philipp Gabriel](https://github.com/ph1ps) \u003cbr /\u003e\n**Reference:** [MNIST handwritten digit database](http://yann.lecun.com/exdb/mnist/) \u003cbr /\u003e\n**Example:** [MNIST-CoreML](https://github.com/ph1ps/MNIST-CoreML) \u003cbr /\u003e\n\n### Food101\n**Model:** [Food101.mlmodel](https://drive.google.com/open?id=0B5TjkH3njRqnVjBPZGRZbkNITjA) \u003cbr /\u003e\n**Description:** Food classification \u003cbr /\u003e\n**Author:** [Philipp Gabriel](https://github.com/ph1ps) \u003cbr /\u003e\n**Reference:** [UPMC Food-101](http://visiir.lip6.fr/explore) \u003cbr /\u003e\n**Example:** [Food101-CoreML](https://github.com/ph1ps/Food101-CoreML) \u003cbr /\u003e\n\n### SentimentPolarity\n**Model:** [SentimentPolarity](https://github.com/cocoa-ai/SentimentCoreMLDemo/raw/master/SentimentPolarity/Resources/SentimentPolarity.mlmodel) \u003cbr /\u003e\n**Description:** Sentiment Polarity Analysis \u003cbr /\u003e\n**Author:** [Vadym Markov](https://github.com/vadymmarkov) \u003cbr /\u003e\n**Reference:** [Epinions.com reviews dataset](http://boston.lti.cs.cmu.edu/classes/95-865-K/HW/HW3/) \u003cbr /\u003e\n**Example:** [SentimentCoreMLDemo](https://github.com/cocoa-ai/SentimentCoreMLDemo) \u003cbr /\u003e\n\n### VisualSentimentCNN\n**Model:** [VisualSentimentCNN](https://drive.google.com/open?id=0B1ghKa_MYL6mZ0dITW5uZlgyNTg) \u003cbr /\u003e\n**Description:** Visual Sentiment Prediction \u003cbr /\u003e\n**Author:** [Image Processing Group - BarcelonaTECH - UPC](https://github.com/imatge-upc) \u003cbr /\u003e\n**Reference:** [From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction](https://github.com/imatge-upc/sentiment-2017-imavis) \u003cbr /\u003e\n**Example:** [SentimentVisionDemo](https://github.com/cocoa-ai/SentimentVisionDemo) \u003cbr /\u003e\n\n### AgeNet\n**Model:** [AgeNet](https://drive.google.com/file/d/0B1ghKa_MYL6mT1J3T1BEeWx4TWc/view?usp=sharing) \u003cbr /\u003e\n**Description:** Age Classification \u003cbr /\u003e\n**Author:** [Gil Levi and Tal Hassner](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/) \u003cbr /\u003e\n**Reference:** [Age and Gender Classification using Convolutional Neural Networks](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/CNN_AgeGenderEstimation.pdf) \u003cbr /\u003e\n**Example:** [FacesVisionDemo](https://github.com/cocoa-ai/FacesVisionDemo) \u003cbr /\u003e\n\n### GenderNet\n**Model:** [GenderNet](https://drive.google.com/file/d/0B1ghKa_MYL6mYkNsZHlyc2ZuaFk/view?usp=sharing) \u003cbr /\u003e\n**Description:** Gender Classification \u003cbr /\u003e\n**Author:** [Gil Levi and Tal Hassner](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/) \u003cbr /\u003e\n**Reference:** [Age and Gender Classification using Convolutional Neural Networks](http://www.openu.ac.il/home/hassner/projects/cnn_agegender/CNN_AgeGenderEstimation.pdf) \u003cbr /\u003e\n**Example:** [FacesVisionDemo](https://github.com/cocoa-ai/FacesVisionDemo) \u003cbr /\u003e\n\n### CNNEmotions\n**Model:** [CNNEmotions](https://drive.google.com/file/d/0B1ghKa_MYL6mTlYtRGdXNFlpWDQ/view?usp=sharing) \u003cbr /\u003e\n**Description:** Emotion Recognition \u003cbr /\u003e\n**Author:** [Gil Levi and Tal Hassner](http://www.openu.ac.il/home/hassner/projects/cnn_emotions/) \u003cbr /\u003e\n**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) \u003cbr /\u003e\n**Example:** [FacesVisionDemo](https://github.com/cocoa-ai/FacesVisionDemo) \u003cbr /\u003e\n\n### NamesDT\n**Model:** [NamesDT](https://github.com/cocoa-ai/NamesCoreMLDemo/raw/master/Names/Resources/NamesDT.mlmodel) \u003cbr /\u003e\n**Description:** Gender Classification from first names \u003cbr /\u003e\n**Author:** [http://nlpforhackers.io](http://nlpforhackers.io) \u003cbr /\u003e\n**Reference:** [Is it a boy or a girl? An introduction to Machine Learning](http://nlpforhackers.io/introduction-machine-learning/) \u003cbr /\u003e\n**Example:** [NamesCoreMLDemo](https://github.com/cocoa-ai/NamesCoreMLDemo) \u003cbr /\u003e\n\n### Oxford102\n**Model:** [Oxford102](https://drive.google.com/file/d/0B1ghKa_MYL6meDBHT2NaZGxkNzQ/view?usp=sharing) \u003cbr /\u003e\n**Description:** Flower Classification \u003cbr /\u003e\n**Author:** [Jimmie Goode](https://github.com/jimgoo) \u003cbr /\u003e\n**Reference:** [Classifying images in the Oxford 102 flower dataset with CNNs](http://jimgoo.com/flower-power/) \u003cbr /\u003e\n**Example:** [FlowersVisionDemo](https://github.com/cocoa-ai/FlowersVisionDemo) \u003cbr /\u003e\n\n### FlickrStyle\n**Model:** [FlickrStyle](https://drive.google.com/file/d/0B1ghKa_MYL6maFFWR3drLUFNQ1E/view?usp=sharing) \u003cbr /\u003e\n**Description:** Image Style Classification \u003cbr /\u003e\n**Author:** [Sergey Karayev](https://gist.github.com/sergeyk) \u003cbr /\u003e\n**Reference:** [Recognizing Image Style](http://sergeykarayev.com/files/1311.3715v3.pdf) \u003cbr /\u003e\n**Example:** [StylesVisionDemo](https://github.com/cocoa-ai/StylesVisionDemo) \u003cbr /\u003e\n\n## Model Demonstration App\n\n\u003cp align=\"left\"\u003e\n    \u003cimg src=\"https://github.com/eugenebokhan/Awesome-ML/raw/master/Media/header.png\", width=\"640\"\u003e\n\u003c/p\u003e\n\u003cp align=\"left\"\u003e\n    \u003cimg src=\"https://github.com/eugenebokhan/Awesome-ML/raw/master/Media/Cards_Scroll_Demonstration_640.gif\", width=\"640\"\u003e\n\u003c/p\u003e\n\n**Description:** Discover, download, on-device-compile \u0026 launch different image processing CoreML models on iOS. \u003cbr /\u003e\n**Author:** [Eugene Bokhan](https://github.com/eugenebokhan) \u003cbr /\u003e\n**Source:** [Awesome ML](https://github.com/eugenebokhan/Awesome-ML) \u003cbr /\u003e\n**Lincese:** [BSD 3-Clause](https://github.com/eugenebokhan/Awesome-ML/blob/master/LICENSE.md) \u003cbr /\u003e\n","funding_links":[],"categories":["Collections","Swift","Other Lists","🌐 **Edge Deployment Frameworks**"],"sub_categories":["General-Purpose Machine Learning","TeX Lists","🍎 **CoreML** - Apple"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSwiftBrain%2Fawesome-CoreML-models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FSwiftBrain%2Fawesome-CoreML-models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSwiftBrain%2Fawesome-CoreML-models/lists"}