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SnapOtter d24e244af4 docs: organize tool pages by modality under /tools/<modality>/

Move all 157 tool pages into image/video/audio/pdf/data subfolders so URLs read /tools/<modality>/<id> (e.g. /tools/image/crop). Nest the image sub-categories under an Image group in the sidebar so the nav reads by modality. Add public/_redirects (301, clean + .html forms) mapping every old flat /tools/<id> URL to its new path so inbound links keep working. Rewrite all internal /tools links. Verified with a clean docs build (no dead links).

2026-06-18 14:12:28 +08:00

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PNG Transparency Fixer

Fix fake transparent PNGs in one click. Uses AI matting (BiRefNet HR Matting model) to produce true alpha transparency, with defringe post-processing to clean up edges.

API Endpoint

POST /api/v1/tools/image/transparency-fixer

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

Model bundle: background-removal (4-5 GB)

Parameters

Parameter	Type	Required	Default	Description
file	file	Yes	-	Image file (multipart)
defringe	number	No	`30`	Defringe intensity (0-100). Removes semi-transparent fringe pixels around edges
outputFormat	string	No	`"png"`	Output format: `png` or `webp`
removeWatermark	boolean	No	`false`	Apply watermark removal pre-processing (median filter)

Example Request

curl -X POST http://localhost:13490/api/v1/tools/image/transparency-fixer \
  -F "file=@fake-transparent.png" \
  -F 'settings={"defringe":40,"outputFormat":"png"}'

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":"Processing transparency...","percent":50}

Final Result (via SSE)

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "downloadUrl": "/api/v1/download/{jobId}/fake-transparent_fixed.png",
    "originalSize": 180000,
    "processedSize": 150000,
    "filename": "fake-transparent.png"
  }
}

Notes

Requires the background-removal model bundle to be installed (4-5 GB).
Uses birefnet-hr-matting as the primary model for high-quality alpha matting. Falls back to birefnet-general if the HR model runs out of memory.
The defringe option removes semi-transparent fringe pixels that AI matting sometimes leaves around hair, fur, and fine edges. It works by blurring the alpha channel and zeroing out low-confidence pixels.
The removeWatermark option applies a median filter pre-processing step. It is a basic watermark reduction, not a dedicated watermark removal tool.
Only outputs PNG or lossless WebP (both support alpha transparency).
Supports HEIC/HEIF, RAW, TGA, PSD, EXR, and HDR input formats via automatic decoding.

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