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vision-framework

Implement on-device computer vision features in iOS apps using Apple's Vision framework.

981|50|Updated Mar 3, 2026
Search Tags:#ocr#ios#vision#image analysis#core ml#face detection#barcode scanning
One-click install
npx skills add https://github.com/dpearson2699/swift-ios-skills --skill vision-framework-dpearson2699
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: vision-framework
Source: https://github.com/dpearson2699/swift-ios-skills/tree/main/skills/vision-framework
Command: npx skills add https://github.com/dpearson2699/swift-ios-skills --skill vision-framework-dpearson2699

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill enables developers to integrate advanced on-device computer vision capabilities into their iOS applications, allowing for real-time analysis of images and video without relying on cloud services.

Core Features & Use Cases

  • Text Recognition (OCR): Extract text from images and documents.
  • Face Detection: Identify faces, their landmarks, and capture quality.
  • Barcode Scanning: Detect and decode various barcode types, including QR codes.
  • Image Segmentation: Separate subjects (like people) from backgrounds.
  • Object Tracking: Follow specific objects across video frames.
  • Core ML Integration: Run custom machine learning models for specialized vision tasks.
  • Use Case: Automatically read license plates from a video feed, detect faces in a photo album for tagging, or scan product barcodes in a retail app.

Quick Start

Use the vision-framework skill to detect all text within the provided image.

Frequently Asked Questions about vision-framework

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement on-device OCR text recognition in an iOS app?▼

On-device OCR text recognition in iOS uses Apple's Vision framework to extract text from images and documents without cloud services. It supports both modern Swift-native Vision APIs and legacy VNRequest patterns for real-time analysis.

Can I run custom Core ML models for image analysis using the Vision framework?▼

Running custom Core ML models for image analysis is supported through the Vision framework's integration. This allows specialized machine learning inference tasks to execute entirely on-device within your iOS application.

What is the best way to scan barcodes and detect faces in an iOS app?▼

Barcode scanning and face detection in iOS are best handled by the Vision framework, which identifies face landmarks and decodes formats like QR codes. VisionKit's DataScannerViewController can also be used for live camera scanning.

Does the Vision framework support image segmentation and object tracking for video feeds?▼

The Vision framework supports image segmentation to separate subjects from backgrounds and object tracking to follow items across video frames. These features process video feeds locally on the iOS device.

Do I need iOS 18 to use modern Swift-native Vision APIs for computer vision tasks?▼

Modern Swift-native Vision APIs require iOS 18 or later for computer vision tasks. However, the framework also supports legacy VNRequest patterns for compatibility with older iOS versions.

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