falImage to imageComing soon

fal-ai/birefnet

Name: fal-ai/birefnet
Brand: fal

fal-ai/birefnet is an image to image tool from fal that runs in the background and returns images. Coming soon: listed with its price, not yet open to runs.

This tool is listed but not yet available to run.

Price pending

Pricing

Price pending.

Limits

Runs: In the background
Returns: image
Longest queue wait: 3600s
Run deadline: 1800s
Largest inline input: 1024 KB
Largest input file: 500 MB
Largest output: 4768 MB
Outputs per run: 16

Input

Field	Kind	Default	Description
`model`	one of General Use (Light), General Use (Heavy), Portrait	General Use (Light)	Model to use for background removal. The 'General Use (Light)' model is the original model used in the BiRefNet repository. The 'General Use (Heavy)' model is a slower but more accurate model. The 'Portrait' model is a model trained specifically for portrait images. The 'General Use (Light)' model is recommended for most use cases. The corresponding models are as follows: - 'General Use (Light)': BiRefNet-DIS_ep580.pth - 'General Use (Heavy)': BiRefNet-massive-epoch_240.pth - 'Portrait': BiRefNet-portrait-TR_P3M_10k-epoch_120.pth
`operating_resolution`	one of 1024x1024, 2048x2048	1024x1024	The resolution to operate on. The higher the resolution, the more accurate the output will be for high res input images.
`output_mask`	true or false	false	Whether to output the mask used to remove the background
`refine_foreground`	true or false	true	Whether to refine the foreground using the estimated mask
`image_url` required	URL or file	—	URL of the image to remove background from
`output_format`	one of webp, png, gif	png	The format of the output image

Same request in code

curl https://api.spiral.ai/v1/runs \
  -H "Authorization: Bearer $SPIRAL_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: $(uuidgen)" \
  -d '{
    "provider": "fal",
    "model": "fal-ai/birefnet",
    "input": {
      "image_url": "https://storage.googleapis.com/falserverless/example_inputs/birefnet-input.jpeg"
    }
  }'