Resize

Resize images by specifying exact pixel dimensions, a percentage scale factor, or a fit mode that controls how the image adapts to the target dimensions.

API Endpoint

POST /api/v1/tools/resize

Accepts multipart form data with an image file and a JSON settings field.

Parameters

Parameter	Type	Required	Default	Description
width	integer	No	-	Target width in pixels (max 16383)
height	integer	No	-	Target height in pixels (max 16383)
fit	string	No	"contain"	How the image fits the dimensions: contain, cover, fill, inside, outside
withoutEnlargement	boolean	No	false	Prevent upscaling if image is smaller than target
percentage	number	No	-	Scale by percentage (e.g. 50 for half size)

At least one of width, height, or percentage must be provided.

Fit Modes

• contain - Resize to fit within the dimensions, preserving aspect ratio (may leave empty space)
• cover - Resize to cover the dimensions, preserving aspect ratio (may crop)
• fill - Stretch to exactly match dimensions (ignores aspect ratio)
• inside - Like contain, but only downscales, never upscales
• outside - Like cover, but only downscales, never upscales

Example Request

curl -X POST http://localhost:1349/api/v1/tools/resize \
  -H "Authorization: Bearer si_your-api-key" \
  -F "[email protected]" \
  -F 'settings={"width": 800, "height": 600, "fit": "contain"}'

Resize by percentage:

curl -X POST http://localhost:1349/api/v1/tools/resize \
  -H "Authorization: Bearer si_your-api-key" \
  -F "[email protected]" \
  -F 'settings={"percentage": 50}'

Example Response

{
  "jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "downloadUrl": "/api/v1/download/a1b2c3d4-e5f6-7890-abcd-ef1234567890/photo.jpg",
  "originalSize": 2450000,
  "processedSize": 980000
}

Notes

• Maximum dimension is 16383 pixels on either axis (Sharp/libvips limit).
• Output format matches the input format. HEIC, RAW, PSD, and SVG inputs are automatically decoded before processing.
• EXIF orientation is auto-applied before resizing.
• The withoutEnlargement flag is useful for batch processing where some images may already be smaller than the target.