Vision Framework Diagnostics

Systematic troubleshooting for Vision framework issues: subjects not detected, missing landmarks, low confidence, performance problems, and coordinate mismatches.

Core Principle

When Vision doesn't work, the problem is usually:

1. Environment (lighting, occlusion, edge of frame) - 40%
2. Confidence threshold (ignoring low confidence data) - 30%
3. Threading (blocking main thread causes frozen UI) - 15%
4. Coordinates (mixing lower-left and top-left origins) - 10%
5. API availability (using iOS 17+ APIs on older devices) - 5%

Always check environment and confidence BEFORE debugging code.

Common Issues

Subject Not Detected

Symptom: request.results is nil or empty

Diagnostic steps:

1. Verify request succeeded (no error thrown)
2. Check subject size (should be >10% of image)
3. Inspect lighting and contrast
4. Ensure subject not at edge of frame

Common causes:

• Subject too small
• Poor lighting/blur
• Low contrast with background
• Partial occlusion at edge

Hand Pose Missing Landmarks

Symptom: Hand detected but landmarks have low confidence

Diagnostic code:

let allPoints = try observation.recognizedPoints(.all)

for (key, point) in allPoints {
    if point.confidence < 0.3 {
        print("\(key): LOW CONFIDENCE (\(point.confidence))")
    }
}

Common causes:

• Hand parallel to camera (rotate hand toward lens)
• Hand near edge of frame
• Gloves or occlusion
• Feet misidentified as hands

UI Freezing

Symptom: App freezes during Vision processing

Diagnostic:

print("Thread: \(Thread.isMainThread ? "MAIN" : "Background")")

Fix: Move to background queue

DispatchQueue.global(qos: .userInitiated).async {
    let request = VNGenerateForegroundInstanceMaskRequest()
    try? handler.perform([request])

    DispatchQueue.main.async {
        // Update UI
    }
}

Overlays in Wrong Position

Symptom: UI overlays don't align with detected features

Root cause: Coordinate system mismatch (Vision uses lower-left origin, UIKit uses top-left)

Fix:

// ❌ WRONG
let uiY = visionPoint.y * height

// ✅ CORRECT
let uiY = (1 - visionPoint.y) * height  // Flip Y axis

Person Segmentation Missing People

Symptom: VNGeneratePersonInstanceMaskRequest detects fewer people than expected

Root cause: API segments up to 4 people maximum

Diagnostic:

let faceRequest = VNDetectFaceRectanglesRequest()
try handler.perform([faceRequest])

let faceCount = faceRequest.results?.count ?? 0

if faceCount > 4 {
    print("Crowded scene - some people will be missed/combined")
}

Fix: Fallback to VNGeneratePersonSegmentationRequest (single mask for all people)

Performance Optimization

Slow Processing

Diagnostic: Measure request time

let start = CFAbsoluteTimeGetCurrent()
try handler.perform([request])
let elapsed = CFAbsoluteTimeGetCurrent() - start

print("Request took \(elapsed * 1000)ms")

Common fixes:

Cause	Fix	Time Saved
maximumHandCount = 10	Set to actual need (2)	50-70%
Processing every frame	Skip frames (every 3rd)	66%
Full-res images	Downscale to 1280x720	40-60%

Quick Reference

Symptom	First Check	Pattern	Est. Time
No results	Subject size/lighting	Environment	30 min
Low confidence	Hand/body orientation	Confidence	45 min
UI freezes	Thread check	Threading	15 min
Wrong position	Coordinate conversion	Coordinates	20 min
Missing people (>4)	Face count	Crowded scene	30 min

Resources

• Vision Framework (Main Skill) - Implementation patterns
• Vision Framework API Reference - Complete API docs

Apple Documentation

• Vision Framework
• Vision Performance Best Practices