axiom-vision

name: axiom-vision description: Use when implementing ANY computer vision feature — image analysis, pose detection, person segmentation, subject lifting, text recognition, barcode scanning. license: MIT

Computer Vision

You MUST use this skill for ANY computer vision work using the Vision framework.

Quick Reference

Decision Tree

digraph vision {
    start [label="Computer vision task" shape=ellipse];
    what [label="What do you need?" shape=diamond];

    start -> what;
    what -> "skills/vision-framework.md" [label="implement feature"];
    what -> "skills/vision-ref.md" [label="API reference"];
    what -> "skills/vision-ref.md" [label="Visual Intelligence"];
    what -> "skills/vision-ref.md" [label="tap-to-segment / watchOS / FM tools (27)"];
    what -> "skills/vision-diag.md" [label="something broken"];
}

1. Implementing (pose, segmentation, OCR, barcodes, documents, live scanning)? → skills/vision-framework.md
2. Visual Intelligence system integration (camera/screenshot search; iOS 26+, iPadOS27/macOS27)? → skills/vision-ref.md (Visual Intelligence section)
3. Tap-to-segment, Vision on watchOS, or Vision tools for Foundation Models (27 cycle)? → skills/vision-ref.md
4. Need API reference / code examples? → skills/vision-ref.md
5. Debugging issues (detection failures, confidence, coordinates)? → skills/vision-diag.md

Critical Patterns

Implementation (skills/vision-framework.md):

• Decision tree for choosing the right Vision API
• Subject segmentation with VisionKit
• Isolating objects while excluding hands (combining APIs)
• Hand/body pose detection (21/19 landmarks)
• Text recognition (fast vs accurate modes)
• Barcode detection with symbology selection
• Document scanning and structured extraction (iOS 26+)
• Live scanning with DataScannerViewController
• CoreImage HDR compositing

Diagnostics (skills/vision-diag.md):

• Subject detection failures (edge of frame, lighting)
• Landmark tracking issues (confidence thresholds)
• Performance optimization (frame skipping, downscaling)
• Coordinate conversion (lower-left vs top-left origin)
• Text recognition failures (language, contrast)
• Barcode detection issues (symbology, size, glare)
• DataScanner troubleshooting (availability, data types)

Anti-Rationalization

Example Invocations

User: "How do I detect hand pose in an image?" → See skills/vision-framework.md

User: "Isolate a subject but exclude the user's hands" → See skills/vision-framework.md

User: "How do I read text from an image?" → See skills/vision-framework.md

User: "Scan QR codes with the camera" → See skills/vision-framework.md

User: "Subject detection isn't working" → See skills/vision-diag.md

User: "Text recognition returns wrong characters" → See skills/vision-diag.md

User: "Show me VNDetectHumanBodyPoseRequest examples" → See skills/vision-ref.md

User: "How do I make my app work with Visual Intelligence?" → See skills/vision-ref.md

User: "Let users tap an object in a photo to cut it out" → See skills/vision-ref.md (Iterative Segmentation)

User: "Can I use Vision in my watchOS app?" → See skills/vision-ref.md (Vision on watchOS)

User: "RecognizeDocumentsRequest API reference" → See skills/vision-ref.md

User: "Group faces into people across my library" / "cluster faces on-device into persons" → Use axiom-media (skills/media-intelligence.md) — identity clustering across assets, not per-image detection