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

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

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.

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.

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.

Converted CoreML Model Zoo.

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.

Collection of models for Core ML

ONNX to Core ML Converter

This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.

👀 iOS11 demo application for age and gender classification of facial images.

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.

Discover, download, compile & launch different image processing & style transfer CoreML models on iOS.

Style Art library process images using COREML with a set of pre trained machine learning models and convert them to Art style.

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）

A simple guide that explains the steps from training a simple PyTorch image classifier to converting the generated neural network into a CoreML model ready for production

Stable Diffusion implementation using CoreML, PyTorch and SwiftUI

Try CoreML models on multiple images and videos easily and quickly

A Swift library for creating and exporting CoreML Models in Swift

A Big Awesome List CoreML Models.

A CoreML model which classifies images of food

Stable Diffusion app for macOS based on CoreML models

Real-time on-device text-to-image and image-to-image Semantic Search with video stream camera capture using USearch & UForm AI Swift SDKs for Apple devices 🍏

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.

😃 iOS11 demo application for sentiment polarity analysis.

A CoreML models that detects nudity in a picture

NAFNet deblurring model inference using CoreML

This repository contains the code for converting tflite model of Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs and Blazeface to tensorflow and coreml.

Scripts for exporting YOLOv5 models to CoreML and benchmarking it.