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feat(i18n): 21-language pipeline, landing/docs/API wiring, landing+API translations
Shared Claude Code translation pipeline (scripts/i18n, no API key) plus Astro/VitePress/Scalar i18n wiring. Landing and API reference translated into all 20 languages; docs i18n wiring + English source anchors. The translated docs markdown (apps/docs/<locale>/**, 3,620 files) follows in a companion PR because it exceeds GitHub's per-PR CI file limit.
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description: Auto-detect and blur faces in images with AI face detection for privacy and GDPR-compliant anonymization.
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---
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# Face / PII Blur
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# Face / PII Blur {#face-pii-blur}
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Auto-detect and blur faces in images using AI-powered face detection (MediaPipe).
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## API Endpoint
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## API Endpoint {#api-endpoint}
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`POST /api/v1/tools/image/blur-faces`
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**Model bundle:** `face-detection` (200-300 MB)
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## Parameters
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## Parameters {#parameters}
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| Parameter | Type | Required | Default | Description |
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|-----------|------|----------|---------|-------------|
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| blurRadius | number | No | `30` | Blur radius applied to detected faces (1-100) |
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| sensitivity | number | No | `0.5` | Face detection sensitivity (0-1). Lower values detect fewer faces with higher confidence |
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## Example Request
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## Example Request {#example-request}
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```bash
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curl -X POST http://localhost:1349/api/v1/tools/image/blur-faces \
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-F 'settings={"blurRadius":40,"sensitivity":0.3}'
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```
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## Response
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## Response {#response}
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### Initial Response (202 Accepted)
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### Initial Response (202 Accepted) {#initial-response-202-accepted}
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```json
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{
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}
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```
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### Progress (SSE at `/api/v1/jobs/{jobId}/progress`)
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### Progress (SSE at `/api/v1/jobs/{jobId}/progress`) {#progress-sse-at-api-v1-jobs-jobid-progress}
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```
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event: progress
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data: {"phase":"processing","stage":"Detecting faces...","percent":40}
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```
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### Final Result (via SSE)
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### Final Result (via SSE) {#final-result-via-sse}
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```json
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{
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}
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```
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### No Faces Detected
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### No Faces Detected {#no-faces-detected}
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If no faces are found, the result includes a warning:
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}
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```
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## Notes
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## Notes {#notes}
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- Requires the `face-detection` model bundle to be installed (200-300 MB).
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- Output format matches the input format automatically.
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