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Computer Vision on iOS
With recent advances in both iPhone camera and AI-accelerated chip technology (i.e. the A13 Bionic in the iPhone 11 series), it’s no wonder that some of the most innovative, transformative use cases for machine learning on iOS come in the form of computer vision.
From understanding scenes and creating artistic masterpieces to tracking human movement and even changing hair color, the promise of real-time computer vision on iOS is real.
But it can be tough to know where to get started. That’s why we’ve worked to curate and assemble an authoritative collection of articles and tutorials that explore what’s possible with computer vision-based machine learning on iOS.
Automatically Pixelate Faces on iOS using Face Detection with Native Swift Code
Leveraging the native Swift library to perform face detection in an iOS app
— by Omar M’Haimdat
Safer and Smarter: Contactless shopping with on-device object detection
Scaling out to a cloud platform for fast model training, evaluation, inferencing, logging, and monitoring.
— by Jamshed Khan
Build a SwiftUI + Core ML Emoji Hunt Game for iOS
Create a fun machine learning iOS camera app that lets you search for things in your house that are similar to emojis.
— by Anupam Chugh
Semantic and Instance Segmentation on iOS Using a Flask API — DeepLabV3+ and Mask R-CNN
Build an API that performs image segmentation and consume it with an iOS application
— by Omar M’Haimdat
Implement Depth Estimation on iOS Using a FCRN Model
Predict the depth of a scene and estimate how close an object is to the camera.
— by Omar M’Haimdat
Using TensorFlow.js in a Native iOS App to Perform Object Detection
Browser-based machine learning — in an iOS app.
— by Konrad Mokiejewski
Face Recognition and Detection on iOS Using Native Swift Code, Core ML, and ARKit
Leveraging the native Swift library to perform face recognition and detection in an iOS app.
— by Omar M’Haimdat
Scanning Credit Cards with Computer Vision on iOS
Leverage Vision’s Rectangle Detection and Text Recognizer to detect credit and other business cards in a live camera feed.
— by Anupam Chugh
Build a Touchless Swipe iOS App Using ML Kit’s Face Detection API
Leverage ML Kit’s Face Detection API to perform swipe gestures using blinks, winks, and head turns
— by Anupam Chugh
Compute Image Similarity Using Computer Vision in iOS
Determine the Euclidean distance between images using their feature prints to determine image similarity on iOS.
— by Anupam Chugh
Training a TensorFlow Lite model for mobile using AutoML Vision Edge
Learn how to leverage Google’s AutoML Vision Edge training framework to train a custom image classification TensorFlow Lite model that’s ready for mobile deployment.
— By Harshit Dwivedi
Computer Vision in iOS: Determine the Best Facial Expression in Live Photos
Work through an iOS implementation of Vision framework’s new face capture quality request to programmatically select the best video frame from a Live Photo.
— by Anupam Chugh
License Plate Recognition, Detection, and Plate Number Extraction on iOS
Creating an iOS application to recognize, detect, and extract license plate numbers.
— by Omar M’Haimdat
Incorporating machine learning into iOS apps
Learn how to get started with machine learning on iOS: Classification using Core ML and Vision.
— by Pradnya Nikam
https://heartbeat.comet.ml/incorporating-machine-learning-into-ios-apps-a5eb8bccd915
Building a Barcode Scanner in Swift on iOS
Learn how to use Apple’s Vision framework to build an iOS app that can scan barcodes and return information about what’s being scanned.
— by Rick Wierenga
[Text Recognition] Building an iOS camera calculator with Core ML’s Vision and Tesseract OCR
Using Core ML’s Vision in iOS and Tesseract, learn how to build iOS apps powered by computer vision and optical character recognition.
— by Khoa Pham
[Object Detection] Building a real-time object detection iOS app that detects sushi
Learn how to build an iOS app that can see and detect objects in real time.
— by Junji Watanabe
[Image Segmentation, Object Detection, AR] Hand Detection with Core ML and ARKit
ARKit allows mixing virtual objects and real world environment. In this post we explore how we can make our real hands interact with virtual objects using machine learning and Core ML in particular.
—by Gil Nakache
[Image Classification] Detecting Pneumonia in an iOS App with Create ML
Learn how to use Create ML to train and implement your own image classification model in an iOS app.
— by Özgür Şahin
[Gesture Recognition + AR] Using Core ML and ARKit to Build a Gesture-Based Interface iOS App
Harnessing mobile machine learning and augmented reality on iOS to browse the Internet with hand gestures.
— by Bruno Muniz
[Image Classification] Using Core ML and Vision in iOS for Age Detection
Learn how to build an iOS app that detects age using Core ML and Apple’s Vision framework.
— by Sayalee Pote
[Image Classification] Using Core ML and Custom Vision to Build a Real-Time Hand Sign Detector in iOS
Learn how to train your own Core ML model and integrate it in an iOS app with Custom Vision.
— by Sayalee Pote
[Image Classification] How to fine-tune ResNet in Keras and use it in an iOS App via Core ML
An end-to-end tutorial that shows you how to fine-tune a Keras model, convert it to Core ML, and integrate it into an iOS app.
— by Özgür Şahin
[Text Recognition] Intro to machine learning on iOS: Using Core ML to recognize handwritten digits
A crash course on using machine learning in iOS app development — handwritten text recognition.
— by manu rink
[Image Classification] Training a Core ML Model with Turi Create to Classify Dog Breeds
Learn how to train an image classification Core ML model using Turi Create — to classify dog breeds!
— by Vardhan Agrawal
[Image Classification] Building Not Hotdog with Turi Create and Core ML — in an afternoon
Recreating the (in)famous Not Hot Dog app from HBO’s Silicon Valley using Turi Create and Core ML.
— by Jameson Toole
[Image Classification] Making a “Pokédex” for iOS Using Create ML and Core ML with Vision
Learn how to use Apple’s machine learning frameworks to build a custom image classification model that can identify different Pokémon in real-time.
— by Kyle Aquino
[Pose Estimation + Text Recognition] “Just Point It”: Machine Learning on iOS with Pose Estimation + OCR Using Core ML and ML Kit
A look a “Just Point It”, an iOS app that leverages machine learning to allow users to point at text on a paper document and look up the word that’s being pointed at.
— by tucan9389
[Image Classification] Moving AI from the Cloud to the Edge with Crowd Count and Apple’s Core ML
Learn how to build and implement a crowd classifier model that predicts crowd size, density, and more.
— by Dimitri Roche
[Object Detection] Evaluate Construction Site Safety on iOS using Machine Learning
Building an iOS application for safety on site with Swift, Turi Create, and Core ML.
— by Omar M’Haimdat
Style Transfer iOS Application Using Convolutional Neural Networks
Training a style transfer neural network using Turi Create to create artistic images.
— by Omar M’Haimdat
PyTorch Mobile: Image Classification on iOS
Learn how to implement an image classification machine learning model on iOS with PyTorch Mobile.
— by Anupam Chugh
Building a multi-class image classifier on iOS
Learn how to build an iOS app that uses deep learning to predict an image’s content based on twenty possible classes of food.
— by Navdeep Singh
Simple Semantic Image Segmentation in an iOS Application — DeepLabV3 Implementation
Quick overview of image segmentation and leveraging Core ML to use it in iOS applications.
— by Omar M’Haimdat
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