Feynobg

Feynobg

Playground

FeyNoBg removes the background from input images and returns a clean, transparent foreground image, making it ideal for product cutouts, portraits, e-commerce assets, and design workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

FeyNoBg Background Remover removes the background from a single input image and returns a transparent foreground image. Upload an image, run background removal, and receive a transparent PNG output through the standard WaveSpeed prediction response.

Why Choose This?

• Automatic background removal
  Remove the background from an image in a simple one-step workflow.

• Transparent PNG output
  Generate a foreground cutout with transparency for design, product, and compositing use.

• Broad image format support
  Supports common input formats including JPG, JPEG, PNG, WEBP, GIF, and AVIF.

• Simple public interface
  Only one input image is required.

• Standard image output
  Results are returned as image URLs in the standard WaveSpeed prediction response.

Parameters

How to Use

1. Upload image — Provide the image you want to process.
2. Submit — Run automatic background removal.
3. Use the result — Retrieve the transparent PNG output URL from the standard WaveSpeed prediction response.

Pricing

Best Use Cases

• Product cutouts — Remove backgrounds from product images for ecommerce, catalogs, and ads.
• Design assets — Create transparent foreground images for layouts, posters, and creative compositions.
• Marketing visuals — Prepare clean image assets for campaign graphics and social media content.
• Profile and subject isolation — Extract people, objects, or foreground subjects from simple images.
• Batch asset preparation — Standardize transparent image outputs for downstream design workflows.

Pro Tips

• Use clear images where the foreground subject is visible.
• Avoid heavily cluttered backgrounds when possible.
• Use images with strong contrast between subject and background for cleaner results.
• Use the transparent PNG output for compositing onto new backgrounds.
• Ensure the input image URL is publicly accessible.

## Authentication

For authentication details, please refer to the [Authentication Guide](/api-authentication).

## API Endpoints

### Submit Task & Query Result

<ApiTabs submitUrl={model.submitUrl} resultUrl={model.resultUrl} payload={model.defaultValues} />

## Parameters

### Task Submission Parameters

#### Request Parameters

<RequestParams params={model.params} />

#### Response Parameters

<SubmitResponse />

#### Result Request Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| id | string | Yes | - | Task ID |

#### Result Response Parameters

| Parameter | Type | Description |
|-----------|------|-------------|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., "success") |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array&lt;string \| object&gt; | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: `created`, `processing`, `completed`, or `failed` |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |