Birefnet Background Removal

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Image to Image

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

Inference$ Commercial useFrom 1 credit per run

About Birefnet Background Removal

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

background removalsegmentationhigh-resutility

Pricing

A run with the default settings costs 1 credits. The exact cost updates in the playground as you change settings, and you're only charged when you press Run. Failed runs are refunded automatically.

Inputs

modelselectdefault: "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

Options: General Use (Light), General Use (Heavy), Portrait

operating_resolutionselectdefault: "1024x1024"

The resolution to operate on. The higher the resolution, the more accurate the output will be for high res input images.

Options: 1024x1024, 2048x2048

output_maskbooleandefault: false

Whether to output the mask used to remove the background

refine_foregroundbooleandefault: true

Whether to refine the foreground using the estimated mask

sync_modebooleandefault: false

If `True`, the media will be returned as a data URI and the output data won't be available in the request history.

image_urlfilerequired

URL of the image to remove background from

output_formatselectdefault: "png"

The format of the output image

Options: webp, png, gif

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