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SnapOtterandGitHub 00b651c9f8 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.

2026-07-11 13:01:55 +08:00

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description

description
Repair scratches, tears, and damage on old photos with an AI pipeline for restoration, face enhancement, and color.

Photo Restoration

Fix scratches, tears, and damage on old photos using a multi-step AI pipeline. Combines scratch repair, face enhancement, denoising, and optional colorization.

API Endpoint

POST /api/v1/tools/image/restore-photo

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

Model bundle: photo-restoration (4-5 GB)

Parameters

Parameter	Type	Required	Default	Description
file	file	Yes	-	Image file (multipart)
scratchRemoval	boolean	No	`true`	Remove scratches and surface damage
faceEnhancement	boolean	No	`true`	Enhance faces in the restored photo
fidelity	number	No	`0.7`	Face enhancement fidelity (0-1). Higher values preserve original features more
denoise	boolean	No	`true`	Apply denoising to the restored result
denoiseStrength	number	No	`25`	Denoising strength (0-100)
colorize	boolean	No	`false`	Colorize the restored photo (for grayscale images)
colorizeStrength	number	No	`85`	Colorization intensity (0-100)

Example Request

curl -X POST http://localhost:1349/api/v1/tools/image/restore-photo \
  -F "file=@damaged-old-photo.jpg" \
  -F 'settings={"scratchRemoval":true,"faceEnhancement":true,"fidelity":0.6,"colorize":true}'

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":"Removing scratches...","percent":30}

event: progress
data: {"phase":"processing","stage":"Enhancing faces...","percent":60}

Final Result (via SSE)

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "downloadUrl": "/api/v1/download/{jobId}/damaged-old-photo_restored.jpg",
    "previewUrl": "/api/v1/download/{jobId}/preview.webp",
    "originalSize": 200000,
    "processedSize": 350000,
    "width": 1200,
    "height": 900,
    "steps": ["scratch_removal", "face_enhancement", "denoise", "colorize"],
    "scratchCoverage": 12.5,
    "facesEnhanced": 2,
    "isGrayscale": true,
    "colorized": true
  }
}

Notes

Requires the photo-restoration model bundle to be installed (4-5 GB).
The pipeline runs multiple AI steps sequentially: scratch repair, face enhancement (GFPGAN), denoising, and optionally colorization.
The steps array in the result shows which processing steps were actually executed.
scratchCoverage is an estimated percentage of the image area that had scratch damage.
fidelity controls how strongly faces are enhanced vs. preserving the original appearance. Lower values produce more aggressive enhancement; higher values are more conservative.
The colorize option automatically detects if the image is grayscale. The isGrayscale flag in the result confirms this detection.
Output format matches the input format automatically.
Supports HEIC/HEIF, RAW, TGA, PSD, EXR, HDR, and AVIF input formats via automatic decoding.

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