Model API

Birefnet Background Removal V2

bilateral reference framework (BiRefNet) for high-resolution dichotomous image segmentation (DIS)

Model id

Use this in every request

birefnet/v2

Run it

Quote the input, start the generation with the quote, then poll the job. Set RAYWAKE_API_KEY first; see Authentication.

# 1. Price the exact input (quotes are valid for up to 10 minutes)
curl -s https://api.raywake.com/v1/quotes \
  -H "Authorization: Bearer $RAYWAKE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "birefnet/v2",
  "input": {
    "image_url": "https://example.com/input.png"
  }
}'

# 2. Start the generation with the quote_id from step 1
curl -s https://api.raywake.com/v1/generate \
  -H "Authorization: Bearer $RAYWAKE_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: $(uuidgen)" \
  -d '{"model": "birefnet/v2", "quote_id": "QUOTE_ID", "input": {"image_url":"https://example.com/input.png"}}'

# 3. Poll until the status is terminal
curl -s https://api.raywake.com/v1/jobs/JOB_ID \
  -H "Authorization: Bearer $RAYWAKE_API_KEY"

Input

Input fields for birefnet/v2
Name	Type	Description
`model`	string (enum)	Model to use for background removal. The 'General Use (Light)' model is the original model used in the BiRefNet repository. The 'General Use (Light 2K)' model is the original model used in the BiRefNet repository but trained with 2K images. The 'General Use (Heavy)' model is a slower but more accurate model. The 'Matting' model is a model trained specifically for matting images. The 'Portrait' model is a model trained specifically for portrait images. The 'General Use (Dynamic)' model supports dynamic resolutions from 256x256 to 2304x2304. The 'General Use (Light)' model is recommended for most use cases. The corresponding models are as follows: - 'General Use (Light)': BiRefNet - 'General Use (Light 2K)': BiRefNet_lite-2K - 'General Use (Heavy)': BiRefNet_lite - 'Matting': BiRefNet-matting - 'Portrait': BiRefNet-portrait - 'General Use (Dynamic)': BiRefNet_dynamic Default: `General Use (Light)` One of: `General Use (Light)`, `General Use (Light 2K)`, `General Use (Heavy)`, `Matting`, `Portrait`, `General Use (Dynamic)`
`operating_resolution`	string (enum)	The resolution to operate on. The higher the resolution, the more accurate the output will be for high res input images. The '2304x2304' option is only available for the 'General Use (Dynamic)' model. Default: `1024x1024` One of: `1024x1024`, `2048x2048`, `2304x2304`
`output_mask`	boolean	Whether to output the mask used to remove the background Default: `false`
`refine_foreground`	boolean	Whether to refine the foreground using the estimated mask Default: `true`
`sync_mode`	boolean	If `True`, the media will be returned as a data URI and the output data won't be available in the request history. Default: `false`
`image_url`required	string (image URL)	URL of the image to remove background from
`output_format`	string (enum)	The format of the output image Default: `png` One of: `webp`, `png`, `gif`
`mask_only`	boolean	Whether to return only the segmentation mask without applying it to the image. When set to `True`, only the mask will be returned and foreground refinement will be skipped. Useful for reducing computation and data transfer when only the mask is needed. Default: `false`

Output

A succeeded job lists its results under outputs, stored on our side. See Jobs for every field.

Job excerpt

"outputs": [
  { "type": "image", "url": "https://…", "mime_type": "image/png", "thumbnail_url": "https://…" }
]

Pricing

up to$0.28/ run

The exact charge for your input comes from a quote. How charges settle