Augmented reality (AR), and computer vision technology are increasingly integral to consumer apps and services.
According to Apple, the wider adoption of AR-based apps could drive over $404 billion in revenue for mobile apps by 2025.
To enable developers to build immersive AR experiences and vision-based apps, Apple introduced the Vision framework.
It provides powerful machine learning models for face, text, barcode detection, and image analysis.
Our guide can help you get started with Apple’s Vision framework, utilize its key capabilities to build advanced vision apps, and publish them on the App Store.
10 Features That Separate Apple Vision Pro From The Rest
- Apple’s VisionOS is powered by the same M2 processor that all Mac products use
- Apple Vision Pro utilizes input from 12 cameras, six microphones, and five sensors (including LiDAR)
- Apple has designed a companion chip, the R1, to process multi-modal sensor data, and the latency is as low as 12 milliseconds
- Apple Vision Pro is the first VR headset with “eyesight” or passthrough eyes, enabling users to interact more naturally while wearing the device
- The device utilizes passthrough to display AR/MR content, similar to Meta Quest Pro
- It features a digital crown for adjusting immersion degrees and seamlessly switching between VR and AR/MR
- Apple Vision Pro is fully enabled by gestures and eye movements and is the first VR headset without controllers
- It is the first VR headset to show the user’s full face in a video call, showcasing their complete persona
- The inclusion of a 3D camera allows users to experience memories spatially
- It is compatible with many customized iOS apps available today
Key Features of the Vision Framework
Some of the key capabilities of the Vision framework are:
1. Machine Learning Models
The Vision framework offers pre-trained CoreML models for face detection, text detection, barcode recognition, object tracking, and more. These run efficiently on iOS devices.
2. Image Analysis
It can identify and track human faces, detect salient regions, estimate horizon levels, get image features for classification, and more.
3. Coordinate Conversions
The framework features APIs to smoothly convert between CoreGraphics, CoreVideo, ARKit, and other coordinate systems.
4. Performance
Vision utilizes hardware acceleration, and supports batch processing, multi-threading, and other optimizations to analyze images quickly and efficiently.
The Vision framework integrates tightly with CoreML, ARKit, CreateML, and other Apple frameworks to enable you to build advanced Vision apps.
Key Components of Apple Vision Framework
SwiftUI
SwiftUI is a great platform to bring your existing iOS apps to the platform. SwiftUI can help you develop awesome apps with a framework that supports depth, gestures, effects, and immersive scene types.
RealityKit has been deeply integrated with SwiftUI for you to build sharp, responsive, and volumetric interfaces.
SwiftUI also works seamlessly with UIKit to help you build apps for VisionOS.
RealityKit
RealityKit helps you present 3D content, animations, and visual effects in your app. Mention worthy achievements of RealityKit include:
- Automatically adjusting to physical lighting conditions and cast shadows
- Seamlessly integrating the real world within the virtual world
- Building stunning visual effects
RealityKit comes with MaterialX, which is an open standard for surface and geometry shader specification. These shaders are used by
- Leading Film Studios
- Visual Effects Studios
- Entertainment & Gaming Companies
ARKit
ARKit can fully understand a person’s surroundings, giving your apps new ways to interact with the space around them.
When working with an app that takes a full space to function, you can utilize ARKit APIs such as:
- Plane Estimation
- Scene Reconstruction
- Image Anchoring
- World Tracking
- Skeletal Hand Tracking
Getting Started With The Apple Vision Framework
The Vision framework provides high-level APIs for handling computer vision requests and performing efficient image analysis.
To start developing Vision apps, you need to understand key concepts like:
- VNRequest: Base request class for analyzing images with the Vision framework
- VNSequenceRequestHandler: For processing sequences of images
- VNImageRequestHandler: For single image analysis
You also need to set up the latest Xcode environment, iOS/iPadOS device, and developer account and then build your first app.
Apple provides comprehensive guides on adding Vision framework to your apps. Their sample code can
- Detect faces in images
- Identify the central saliency region
- Scan barcodes
- Detect horizons
4 Tips For Building Advanced Vision Pro Apps
Here are some tips to build more advanced vision apps with the Apple Vision framework:
1. Combining with ARKit
You can create interactive AR apps by combining the Vision framework with ARKit. For example, detect surfaces or specific objects and use that to place AR overlays.
2. Optimizations
Use batch processing, and multi-threading and prefer GPU over CPU-intensive tasks to keep vision analysis smooth and power efficient.
3. Improving Accuracy
Fine-tune the machine learning models with more context-specific training data to improve accuracy for your specific use case.
4. Specialized Domain Apps
The Vision framework can be customized for specialized domains like medical imaging, agriculture, sports analytics, etc.
Possible Apps You Can Build With Vision Framework
Some example apps that can be built using the Vision framework:
1. Barcode and Object Scanning App
A complex app that can detect, recognize, and classify objects, scan QR codes, barcodes, and more.
2. Animoji-style Face Detection App
An app for detecting faces and facial contours and movements to apply animoji or memoji-like face filters.
3. Intelligent Photo Editing App
Apply saliency detection to identify key regions of images and auto-apply filters to highlight main subjects.
4. Medical Imaging Analytics
Use Vision framework along with CoreML to detect infections, lesions, tumors, and other irregularities in medical images.
BONUS: 4 Tips For Publishing Vision Apps On The App Store
To distribute your Vision apps through the App Store, make sure to:
1. Comply with App Store Guidelines
Apple has specific rules for submitting apps, user privacy, security, and more. Strictly adhere to these policies to ensure that the listing stays up.
2. Optimize App Store Listings
Craft compelling descriptions, app previews, and highlights to entice users to download your app.
Take detailed screenshots of your app to include in the listings so the users can understand the clear intention of your application.
3. Apply App Store Optimization Best Practices
Include relevant keywords in the title, description, and metadata to improve search visibility for your application. Look into Google Trends to find the best-trending keywords to be added to your app description.
4. Consider Paid Monetization Strategies
Add auto-renewable subscriptions, one-time in-app purchases, and other models to earn revenue.
To Wrap It All Up
The Apple Vision framework makes it easier to build feature-rich AR apps with interactive computer vision capabilities.
The key is to start simple and keep enhancing your apps by combining the Vision framework with other Apple technologies.
Planning to leverage the power of Apple Vision? Impala Intech can help you leverage the power of Apple Vision Pro with intuitive and innovative apps.
