vision-framework

Implement computer vision features including text recognition (OCR), face detection, barcode scanning, image segmentation, object tracking, and document scanning in iOS apps. Covers both the modern Swift-native Vision API (iOS 16+) and legacy VNRequest patterns, VisionKit DataScannerViewController for live camera scanning, and VNCoreMLRequest for custom model inference. Use when adding OCR, barcode scanning, face detection, or custom Core ML model inference with Vision.

753stars40forksUpdated 6/16/2026

Data Science & ML #ios #image-processing #machine-learning #ocr #swift #computer-vision

Security Assessment

Safe(100/100)

Security Score100/100

About vision-framework

The Vision Framework skill enables developers to implement advanced computer vision capabilities in iOS applications using Apple's native Vision API. This skill covers the complete spectrum of on-device image and video analysis, including optical character recognition (OCR), face detection, barcode scanning, image segmentation, object tracking, and document scanning. It addresses the common challenge of integrating complex computer vision features without requiring extensive machine learning expertise or cloud dependencies.

This skill encompasses both the modern Swift-native Vision API introduced in iOS 18+ and the legacy VNRequest patterns for backward compatibility with iOS 11+. It includes integration with VisionKit's DataScannerViewController for real-time camera scanning and VNCoreMLRequest for running custom Core ML models through the Vision pipeline. The skill provides patterns for handling various image input formats including CGImage, CIImage, CVPixelBuffer, CMSampleBuffer, Data, and URL, with native async/await support in modern implementations.

Ideal for iOS developers building apps that require text extraction from images, real-time barcode scanning, facial recognition features, document digitization, or custom machine learning model inference. Common use cases include receipt scanning apps, ID verification systems, augmented reality experiences, accessibility tools for visually impaired users, and inventory management systems. The skill targets iOS 26+ with Swift 6.3 while maintaining compatibility patterns for older deployments.

FAQ

What's the difference between the modern Vision API and the legacy VNRequest pattern?

The modern API (iOS 18+) uses native Swift async/await with typed request structs like RecognizeTextRequest, while the legacy API uses VNImageRequestHandler with completion handlers and ObjC-style classes like VNRecognizeTextRequest. The modern API provides cleaner syntax and better type safety, but the legacy pattern is needed for backward compatibility with iOS 11-17.

Can I use Vision Framework for real-time camera scanning?

Yes, through VisionKit's DataScannerViewController which provides live camera scanning for text recognition and barcode detection. For custom real-time processing, you can use stateful tracking requests like TrackObjectRequest or DetectTrajectoriesRequest that maintain state across video frames.

What are the minimum iOS requirements for Vision Framework features?

Basic Vision features are available from iOS 11+, but the modern Swift-native API requires iOS 18+ (macOS 15+). Document scanning features mentioned require iOS 26+. The skill documentation targets iOS 26+ with Swift 6.3 but includes backward-compatible patterns for older versions.

How do I integrate custom Core ML models with Vision?

Use VNCoreMLRequest to run custom Core ML models through the Vision pipeline. This allows you to leverage Vision's image preprocessing and request handling infrastructure while using your own trained models for specialized object detection or classification tasks.

Does Vision Framework require an internet connection?

No, all Vision Framework processing happens on-device. This provides privacy benefits, works offline, and has lower latency compared to cloud-based computer vision services. However, on-device processing is limited by the device's computational capabilities.