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SnapOtter 7db6bb97da docs: add per-tool API documentation and fix parity gaps

- Create 53 per-tool VitePress documentation pages with accurate
  parameters from Zod schemas, example requests, and response formats
- Add root llms.txt for LLM-friendly repo browsing
- Fix OpenAPI spec: add auth and 422 error schemas to
  edit-metadata/inspect and strip-metadata/inspect sub-routes
- Fix tool count inconsistency (52 -> 53) across landing site,
  e2e tests, and local docs
- Rename color-adjustments.ts to adjust-colors.ts to match tool ID
- Update VitePress sidebar with all 8 tool categories and top nav

2026-06-08 11:52:28 +08:00

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AI Colorization

Convert black-and-white or grayscale photos to full color using AI (DDColor model with OpenCV DNN fallback).

API Endpoint

POST /api/v1/tools/colorize

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

Model bundle: object-eraser-colorize (1-2 GB)

Parameters

Parameter	Type	Required	Default	Description
file	file	Yes	-	Image file (multipart)
intensity	number	No	`1.0`	Color intensity (0-1). Lower values produce more subtle colorization
model	string	No	`"auto"`	Model to use: `auto`, `ddcolor`, `opencv`

Example Request

curl -X POST http://localhost:13490/api/v1/tools/colorize \
  -F "file=@old-bw-photo.jpg" \
  -F 'settings={"intensity":0.9,"model":"auto"}'

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":"Colorizing...","percent":55}

Final Result (via SSE)

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "downloadUrl": "/api/v1/download/{jobId}/old-bw-photo_colorized.jpg",
    "previewUrl": "/api/v1/download/{jobId}/preview.webp",
    "originalSize": 180000,
    "processedSize": 210000,
    "width": 1920,
    "height": 1080,
    "method": "ddcolor"
  }
}

Notes

Requires the object-eraser-colorize model bundle to be installed (1-2 GB).
DDColor produces higher quality results but is slower; OpenCV DNN is faster with slightly lower quality. auto uses DDColor when available with OpenCV fallback.
The intensity parameter blends between the original grayscale and the AI-colorized result. Use 1.0 for full color, lower values for a partially desaturated vintage look.
Output format matches the input format automatically.
For non-browser-previewable output formats, a WebP preview is generated alongside the main output.
Supports HEIC/HEIF, RAW, TGA, PSD, EXR, and HDR input formats via automatic decoding.

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