coreml-models
There are 16 repositories under coreml-models topic.
likedan / Awesome-CoreML-Models
Largest list of models for Core ML (for iOS 11+)
Language:Python 6259OFA-Sys / Chinese-CLIP
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
Language:Python 3736SwiftBrain / awesome-CoreML-models
Collection of models for Core ML
onnx / onnx-coreml
ONNX to Core ML Converter
Language:Python 389cocoa-ai / FacesVisionDemo
👀 iOS11 demo application for age and gender classification of facial images.
Language:Swift 313eugenebokhan / awesome-ml
Discover, download, compile & launch different image processing & style transfer CoreML models on iOS.
Language:C++ 207ph1ps / Food101-CoreML
A CoreML model which classifies images of food
Language:Swift 144buzsh / SwiftDiffusion
SwiftUI Stable Diffusion implementation using CoreML and PyTorch
Language:Swift 143juanmorillios / List-CoreML-Models
A Big Awesome List CoreML Models.
😃 iOS11 demo application for sentiment polarity analysis.
Language:Swift 120Predict handwritten digits with CoreML
Language:Python 67- SwiftSemanticSearch
ashvardanian / SwiftSemanticSearch
S3 stands for Swift Semantic Search - using USearch & UForm to builds scalable multimodal Retrieval-Augmented pipelines on Apple devices 🍏
Language:Swift 49 - SD-to-CoreML
Zabriskije / SD-to-CoreML
Shell script to convert Stable Diffusion 1.5 models to Core ML
Language:Shell 49 🏷 iOS11 demo application for predicting gender from first names.
Language:Swift 36🌅 iOS11 demo application for visual sentiment prediction.
Language:Swift 36VamshiIITBHU14 / VKSentimentAnalysis
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
Language:Swift 31JustinFincher / FastDepth-CoreML
a CoreML version of FastDepth
Language:Swift 27- Language:Swift 21
eelretep / mlmodelzoo
Build your iOS 11+ apps with the ready-to-use Core ML models below
IlijaMihajlovic / CoreML-and-Vision-with-a-pre-trained-deep-learning-SSD-model
This project shows how to use CoreML and Vision with a pre-trained deep learning SSD (Single Shot MultiBox Detector) model. There are many variations of SSD. The one we’re going to use is MobileNetV2 as the backbone this model also has separable convolutions for the SSD layers, also known as SSDLite. This app can find the locations of several different types of objects in the image. The detections are described by bounding boxes, and for each bounding box, the model also predicts a class.
Language:Swift 17Norod / CoreML-StyleTransfer
A few stylization coreML models that I've trained with CreateML
Language:Python 120xPr0xy / MobileNet-CoreML
MobileNet in CoreML with Vision implemented for iPhone iOS in Swift
Language:Swift 11ashislaha / ARDemo
Create an AR Project with ARKit. Explored Tracking, Plane Detection, Hit Testing, Light Estimation, SCNNode Rendering etc.
Language:Swift 11gazolla / Photo2Cartoon
Very simple app that uses CoreML model to transform image to anime style image.
Language:Swift 10Core ML and Vision object classifier with a lightweight trained model. The model is trained and tested with Create ML straight from Xcode Playgrounds with the dataset I provided.
Language:Swift 10- CoreML-VAEs
Ready to use Core ML VAEs in MLMODELC format
tinahaibodi / weScan
iOS AR application that helps engineers identify hardware with object recognition. Grand Prize Winner and Best Neural Network @ HackWescam 2018.
Language:Swift 7hskang9 / OCRProject
an end-to-end tutorial for OCR recognition using CNN
Language:Jupyter Notebook 6powermobileweb / ARTetris---SceneKit
Augmented Reality Tetris made with ARKit and SceneKit
Language:Swift 5DarkBlueArrowED / MedHub
Most developing countries have a serious shortage of qualified medical personnel. Particularly of qualified pathologists, which leads to long delays in the testing and the diagnosis of diseases. This in its own leads to needless suffering and unnecessary deaths. A review of literature on the field of ML in medical science shows that ML can partially contribute to correcting this problem. These have been specially designed to allow ML models to work with mobile and portable devices such as the iPhones, iPads and the android equivalents. The aim of this dissertation is to show the potential and possibility to develop the next stage of software that can be used in the medical field. The use of ML will reduce the need for other resources such as external databases and other heavy tools. The applications proposed in this project could allow medical professionals such as “Doctors without borders” to test and diagnose patients in field hospitals without having to carry a lot of equipment or have to send blood samples over long distances with related delays and the risk of contamination. The applications could also be used in developed countries where medical facilities are under pressure. The applications could provide an indication of a disease/illness, saving time and resources.
Language:Swift 4Dr-Groot / ObjectDetection_CoreML-Swift
Real time camera object detection with Machine Learning in swift. Basic introduction to Core ML, Vision and ARKit.
Language:Swift 4michalnowak061 / ImageClassifier-iOS-App
This project is simple iOS app using CoreML framework to predict object class on the photo
Language:Swift 3prabakarviji / picture-query
A SwiftUI app using CoreML & Vision to extract text content from the images and querying from the context. Underlying it uses Google's BERT model which converted into CoreML model
Language:Swift 3LucianoPAlmeida / mnist-number-classification
A simple classification of mnist handwritten digits
Language:Jupyter Notebook 2rishabh01solanki / PixeLearner
Combining the power of MobileNetV2 with the privacy of on-device learning. Benefit from real-time updates and efficient image processing, all while ensuring your data remains securely on your device. Experience precision, speed, and trust with PixeLearner.
Language:Swift 2freedomtan / coreml_models_for_mlperf
Converting models used by MLPerf Mobile working group to Core ML format
Language:Python 1
