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SnapOtter/apps/docs/tools/image/erase-object.md
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2.2 KiB

description
description
Remove unwanted objects from images with AI inpainting (LaMa), guided by a mask of the region to erase.

Object Eraser

Remove unwanted objects from images using AI inpainting (LaMa model). Accepts an image and a mask indicating the region to erase.

API Endpoint

POST /api/v1/tools/image/erase-object

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 - Source image file (multipart)
mask file Yes - Mask image (white = area to erase, black = keep). Must be uploaded with fieldname mask
format string No "auto" Output format: auto, png, jpg, jpeg, webp, tiff, gif, avif, heic, heif, jxl
quality integer No 95 Output quality (1-100)

Example Request

curl -X POST http://localhost:1349/api/v1/tools/image/erase-object \
  -F "file=@photo.jpg" \
  -F "mask=@mask.png" \
  -F "format=png" \
  -F "quality=95"

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":"Inpainting...","percent":70}

Final Result (via SSE)

{
  "phase": "complete",
  "percent": 100,
  "result": {
    "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "downloadUrl": "/api/v1/download/{jobId}/photo_erased.png",
    "previewUrl": "/api/v1/download/{jobId}/preview.webp",
    "originalSize": 245000,
    "processedSize": 230000
  }
}

Notes

  • Requires the object-eraser-colorize model bundle to be installed (1-2 GB).
  • The mask must be the same dimensions as the source image. White pixels indicate areas to erase; the AI fills them with plausible content.
  • Uses LaMa (Large Mask Inpainting) for high-quality object removal.
  • 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.