Andrew Adams
Andrew Adams·Co-Founder & Operations at Wireflow

BiRefNet API

Remove backgrounds from images with BiRefNet, the state-of-the-art bilateral reference segmentation model, through a simple REST API call.

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BiRefNet API
Background Removal with BiRefNetOpen workflow

While developing Wireflow's birefnet api pipeline, we processed 1000+ test generations across multiple AI models to find the configurations that produce the most reliable results. This workflow packages those findings.

Built on 1000+ internal test generations during development
12+ AI models benchmarked for optimal output quality
40+ configurations tested to find the best defaults

Pixel-Perfect Background Removal via API

BiRefNet uses a dual-module architecture: a localization module identifies the subject using global semantics, then a reconstruction module refines edges using bilateral references from both image patches and gradient maps. The result is clean cutouts on hair, fur, transparent objects, and complex fabric that older models like U2-Net and rembg struggle with.

On Wireflow, BiRefNet runs as a processing node you can call directly through the REST API or wire into visual workflows. Send an image URL, receive a transparent PNG. No GPU provisioning, no model hosting, no infrastructure to manage.

BiRefNet API Capabilities

✂️

High-Resolution Segmentation

Process images up to 2K resolution with clean edge detection on hair, fur, glass, and semi-transparent materials.

🔌

REST API Integration

Call BiRefNet through a standard REST endpoint. Send an image URL in the request body, receive the processed result in the response.

📦

Batch Processing

Run background removal across hundreds of product images in a single workflow execution using iterator configurations.

🔗

Pipeline Chaining

Connect BiRefNet output to other nodes like image generators or upscalers to build complete image processing pipelines.

🎭

Dual Output Format

Get both the background-removed image with transparency and the raw segmentation mask for custom compositing.

⚡

Sub-Second Processing

BiRefNet processes most images in under one second per frame, making it viable for real-time and high-volume applications.

More Than Just BiRefNet API

Production Background Removal

BiRefNet handles the hardest segmentation cases, from wispy hair to transparent glass, delivering cleaner results than legacy models. Pair it with the AI background remover workflow for one-click processing.

Production Background Removal

Transparent PNG Output

Every processed image returns as a transparent PNG ready for compositing. Use it with the AI transparent background pipeline to swap subjects onto new scenes automatically.

Transparent PNG Output

Batch API for E-Commerce

Process entire product catalogs through the API using iterator configs. The batch image generation API pattern handles queuing and parallel execution across hundreds of images.

Batch API for E-Commerce

Chain With Upscalers

Connect BiRefNet output to ClarityAI or other post-processing nodes. Learn how in the guide on making image backgrounds transparent with AI for complete pipeline examples.

Chain With Upscalers

API-First Architecture

No SDK required. Call workflows with curl, fetch, or any HTTP client. The ClarityAI upscaler API follows the same REST pattern, so integrating multiple processing nodes is consistent.

API-First Architecture
Multi-Model

Birefnet api Workflows

Visual Builder

No Code Required

Production Ready

API & Batch Processing

FAQs

What is the BiRefNet API on Wireflow?
It is a REST endpoint that runs BiRefNet, a bilateral reference segmentation model, to remove backgrounds from images. You send an image URL and receive a transparent PNG with the subject cleanly cut out.
How accurate is BiRefNet for background removal?
BiRefNet is the current state-of-the-art for dichotomous image segmentation. It handles hair, fur, transparent glass, and complex edges better than older models like U2-Net and rembg.
Can I process multiple images in one API call?
Yes. Use Wireflow's iterator configuration to batch process hundreds of images through a single workflow execution. Each image runs through BiRefNet independently and returns its own transparent PNG.
What image formats does BiRefNet support?
BiRefNet accepts JPEG, PNG, and WebP input images. Output is always a transparent PNG with an alpha channel preserving the segmentation mask.
How do I authenticate API requests?
Generate an API key from your Wireflow dashboard under Settings. Include it as a Bearer token in the Authorization header of every request. Keys start with sk- and are shown only once.
Can I chain BiRefNet with other processing nodes?
Yes. Connect BiRefNet output to any downstream node like ClarityAI upscaler, image generators, or compositing nodes. The transparent PNG output works as input for subsequent pipeline steps.
What resolution does BiRefNet support?
BiRefNet processes images up to 2K resolution with clean edge detection. Higher resolution inputs preserve more detail in the segmentation mask, especially around fine features like hair.
Is there a rate limit on BiRefNet API calls?
Rate limits depend on your plan. Free tier allows 10 requests per minute and 50 daily executions. Pro tier allows 60 requests per minute and 1,000 daily executions. All plans cap at 10 concurrent executions.

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Andrew Adams

Written by

Andrew Adams

Co-Founder & Operations at Wireflow

Runs client operations and content strategy at Wireflow. Works directly with creative teams and agencies to build production AI workflows.

Content StrategyClient Operations

Start Removing Backgrounds with BiRefNet

Access BiRefNet through the Wireflow REST API. Remove backgrounds from single images or batch process entire catalogs with pixel-perfect segmentation and transparent PNG output.

View API Docs