Extract text, detect faces and barcodes from iOS photos and video frames.
npx skills add https://github.com/femitz/flyby --skill vision-framework-femitz
Please help me install this Agent Skill. Skill: vision-framework Source: https://github.com/femitz/flyby/tree/main/.agents/skills/vision-framework Command: npx skills add https://github.com/femitz/flyby --skill vision-framework-femitz
Implements computer vision capabilities in iOS apps using Vision and VisionKit to perform OCR, face and barcode detection, document scanning, and segmentation, all on-device.
Provide an image and ask the system to perform OCR to extract all readable text.
High-intent search queries and answers about installing and using this skill.
On-device OCR text recognition in iOS uses the Vision framework to extract readable text from images or video frames. It supports multilingual content with language hints and operates asynchronously to avoid blocking the main thread.
Face detection and barcode detection can process real-time video frames using Vision APIs. Face detection includes landmarks, body pose, and quality metrics, while barcode detection extracts payloads across multiple symbologies.
Modern iOS 18+ Vision APIs are supported with fallbacks for legacy platforms. This ensures robust operation and non-blocking threading across different device versions using asynchronous perform(on:) workflows.
Document scanning and structured data extraction use VisionKit integration for live scanning. This provides a pipeline that feeds scanned document images directly into OCR for downstream text extraction.
Coordinate conversions for UI overlays translate Vision framework detection results into SwiftUI coordinate spaces. This allows accurate mapping of detected face landmarks and bounding boxes onto visual interface layers.
OCR requests failing on non-English text often lack proper language hints. Specifying language hints in the Vision request configuration enables multilingual text recognition for accurate extraction.
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