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SnapOtterandGitHub ec98dfde9a feat(landing,docs): SEO fixes and query-matched tool pages (#383 )

Landing:
- Preload the Bricolage display font (LCP heading) to cut first paint
- Cap tool-page meta descriptions at ~160 chars via whole-sentence
  truncation, so SERP snippets no longer overflow or cut mid-phrase
- Drop dead HowTo + FAQPage JSON-LD from tool pages (Google removed
  HowTo rich results in 2023 and FAQ rich results in 2026); the visible
  content stays. Breadcrumb + WebApplication schema retained
- Shorten 22 tool titles that exceeded the ~60-char SERP limit
- Add an optional h1 override to tool SEO data
- Rewrite adjust-colors, smart-crop, and ringtone-maker to match real
  Search Console query intent (saturation; object-aware cropping;
  convert audio to ringtone), with query-matched H1s and FAQs

Docs:
- Add meta descriptions to 20 pages missing frontmatter

Repo:
- Ignore local credential JSON files (.secrets/, *client_secret*, *service_account*)

2026-07-01 16:20:05 +08:00

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description

description
Auto-detect and blur faces in images with AI face detection for privacy and GDPR-compliant anonymization.

Face / PII Blur

Auto-detect and blur faces in images using AI-powered face detection (MediaPipe).

API Endpoint

POST /api/v1/tools/image/blur-faces

Processing: Asynchronous (returns 202, poll /api/v1/jobs/{jobId}/progress for status via SSE)

Model bundle: face-detection (200-300 MB)

Parameters

Parameter	Type	Required	Default	Description
file	file	Yes	-	Image file (multipart)
blurRadius	number	No	`30`	Blur radius applied to detected faces (1-100)
sensitivity	number	No	`0.5`	Face detection sensitivity (0-1). Lower values detect fewer faces with higher confidence

Example Request

curl -X POST http://localhost:1349/api/v1/tools/image/blur-faces \
  -F "file=@group-photo.jpg" \
  -F 'settings={"blurRadius":40,"sensitivity":0.3}'

Response

Initial Response (202 Accepted)

{
  "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "async": true
}

Progress (SSE at `/api/v1/jobs/{jobId}/progress`)

event: progress
data: {"phase":"processing","stage":"Detecting faces...","percent":40}

Final Result (via SSE)

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "downloadUrl": "/api/v1/download/{jobId}/group-photo_blurred.jpg",
    "originalSize": 450000,
    "processedSize": 420000,
    "facesDetected": 3,
    "faces": [
      {"x": 100, "y": 50, "w": 80, "h": 80},
      {"x": 300, "y": 60, "w": 75, "h": 75},
      {"x": 500, "y": 55, "w": 85, "h": 85}
    ]
  }
}

No Faces Detected

If no faces are found, the result includes a warning:

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "facesDetected": 0,
    "warning": "No faces detected in this image. Try increasing detection sensitivity."
  }
}

Notes

Requires the face-detection model bundle to be installed (200-300 MB).
Output format matches the input format automatically.
The faces array contains bounding box coordinates (x, y, width, height) for each detected face.
Increase sensitivity (closer to 1.0) to detect more faces, including partially occluded ones.
Supports HEIC/HEIF, RAW, TGA, PSD, EXR, and HDR input formats via automatic decoding.

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