160 Open Source Coreml Software Projects
Free and open source coreml code projects including engines, APIs, generators, and tools.
Catboost 5446 ⭐
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Mmdnn 4989 ⭐
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Coreml In Arkit 1451 ⭐
Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit project to use CoreML.
IOS Learning Materials 1244 ⭐
📚Curated list of articles, web-resources, tutorials and code repositories that may help you dig a little bit deeper into iOS [and Apple Platforms].
Visualprogramminglanguage 1132 ⭐
Visual programming language written in Swift that assembles to executable Swift code. WWDC '18 scholarship submission.
Lumina 772 ⭐
A camera designed in Swift for easily integrating CoreML models - as well as image streaming, QR/Barcode detection, and many other features
Facerecognition In Arkit 758 ⭐
Detects faces using the Vision-API and runs the extracted face through a CoreML-model to identiy the specific persons.
Hollance Coremlhelpers 739 ⭐
Types and functions that make it a little easier to work with Core ML in Swift.
Awesome Ml Demos With IOS 657 ⭐
The challenge projects for Inferencing machine learning models on iOS
Keras Openface 508 ⭐
Keras-OpenFace is a project converting OpenFace from Torch implementation to a Keras version
Kingreza Seefood 443 ⭐
Inspired by HBO's Silicon Valley: SeeFood is an iOS app that uses CoreML to detect various dishes
Gesture Recognition 101 Coreml Arkit 260 ⭐
Simple project to recognize hands in realtime. 👋 Serves as an Example for building your own object recognizer.
Pinto_model_zoo 282 ⭐
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin]
Styleart 204 ⭐
Style Art library process images using COREML with a set of pre trained machine learning models and convert them to Art style.
Vocalization Sign Language IOS 181 ⭐
Vocalization sign language iOS App with deep learning using CoreML.
Programming Language Classifier 173 ⭐
An example of how to use CreateML in Xcode 10 to create a Core ML model for classifying text
Facenet_mtcnn_to_mobile 161 ⭐
convert facenet and mtcnn models from tensorflow to tensorflow lite and coreml （使用 TFLite 将 FaceNet 和 MTCNN 移植到移动端）
Mnist_draw 138 ⭐
This is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.
Ssdmobilenet_coreml 136 ⭐
Real-time object-detection using SSD on Mobilenet on iOS using CoreML, exported using tf-coreml
Awesome Ml 130 ⭐
Discover, download, compile & launch different image processing & style transfer CoreML models on iOS.
Unityvision IOS 77 ⭐
This native plugin enables Unity to take advantage of specific features of Core-ML and Vision Framework on the iOS platform.
Testcoreml 60 ⭐
A camera object recognition demo using the CoreML & AVCam framework. Required XCode 9 & iOS 11.
Createml Playgrounds 60 ⭐
Create ML playgrounds for building machine learning models. For developers and data scientists.
Nlpswift 49 ⭐
NSLinguisticTagger provides a uniform interface to a variety of natural language processing functionality with support for many different languages and scripts. One can use this class to segment natural language text into paragraphs , sentences, or words and tag information about those segments such as parts of speech, lexical class, lemma!
Mobilenetv3_centernet 46 ⭐
A tensorflow implement mobilenetv3 centernet, which can be easily deployeed on android(MNN) and ios(CoreML).
Mnist Coreml 40 ⭐
Simple convolutional neural network to predict handwritten digits using Keras + CoreML for WWDC '18 scholarship [Accepted]
Facialcontour 40 ⭐
The facial detection API allows us to not only detect faces & facial features but also check those faces for particular properties such as if a smile is present or eyes are open etc. This is a simple app that recognizes a face in a photo and highlights it with a box. Also, it captures facial features like eyes, nose, lips, ears etc. All written i Swift4.
Visual Recognition With Coreml 37 ⭐
🕶 Classify images offline using Watson Visual Recognition and Core ML.
Coreml Samples 33 ⭐
Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.
Bootfinder 33 ⭐
Boot Finder demonstrates the power of using on-device machine learning models to delight users in new and innovative ways. It's private too! Because this model runs on-device, customer photos never leave the phone!
IOS Ml Dog Classifier 31 ⭐
An iOS app that can detect a dog and determine its breed from an image or video feed.
Route Direction In Ar 30 ⭐
Adding the Feature "Real World Path Direction" by tapping on Map. GoogleMap will give us the direction to that location from user location then click on "ARView" & you will get the real-world path direction. Also added "Reachability" for finding path in Google map. -- Also added .mlmodel for car-detection. Initially trained the model using Convolutional Neural Network in TensorFlow, then convert the .h5 output into .mlmodel. Use it in the application. please check : https://github.com/ashislaha/CarDetection-Keras & https://github.com/ashislaha/CarDetection-iOS for more details how to train a model. -- In ARFrame generates capturedImage which is the input to .mlmodel for detecting that car is present in the image or not. -- This project combines both ARKit & CoreML.
Vksentimentanalysis 28 ⭐
This project is a demo on using CoreML framework for sentiment analysis of text. .mlmodel was developed from Scikit-learn Pipeline using coremltools python package. More details here : https://developer.apple.com/documentation/coreml/converting_trained_models_to_core_ml