YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Visualizer for neural network, deep learning and machine learning models

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.

Run Stable Diffusion on Mac natively

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

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.

Native Mac APIs for Go. Previously known as MacDriver

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

👨🏻‍💻 Examples of new iOS 11 APIs

📚 Curated list of articles, tutorials and repos that may help you dig a little bit deeper into iOS [and Apple Platforms].

Everything we actually know about the Apple Neural Engine (ANE)

Use AnimeGANv3 to make your own animation works, including turning photos or videos into anime.

Apple Silicon Guide. Learn all about the A17 Pro, A16 Bionic, R1, M1-series, M2-series, and M3-series chips. Along with all the Devices, Operating Systems, Tools, Gaming, and Software that Apple Silicon powers.

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.

Converted CoreML Model Zoo.

A NSFW (aka porn) detector with CoreML

Frontier CoreML audio models in your apps — text-to-speech, speech-to-text, voice activity detection, and speaker diarization. In Swift, powered by SOTA open source.

Code examples for ARKit.

Types and functions that make it a little easier to work with Core ML in Swift.

The challenge projects for Inferencing machine learning models on iOS

Visual programming language written in Swift that assembles to executable Swift code.

Official PyTorch implementation of "EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM"

Samples and Tools for Windows ML.

[Deprecated] 🇨🇳中国二代身份证光学识别

Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.

A curated collection of iOS, ML, AR resources sprinkled with some UI additions

A camera designed in Swift for easily integrating CoreML models - as well as image streaming, QR/Barcode detection, and many other features

Detects faces using the Vision-API and runs the extracted face through a CoreML-model to identiy the specific persons.