Ideogram AI Remove Background

Ideogram AI Remove Background

Playground

Try it on WaveSpeedAI!

Ideogram Remove Background is a fast AI background remover that removes image backgrounds and returns a clean transparent foreground image. Ready-to-use REST inference API for product photos, portraits, design assets, e-commerce images, and creative workflows with high-quality cutouts, simple integration, no coldstarts, and affordable pricing.

Features

Ideogram Remove Background removes the background from an input image and returns a transparent cutout, making it easy to isolate products, people, and objects for clean downstream use in design, e-commerce, and marketing workflows.


Why Choose This?

  • Fast background removal Remove image backgrounds in a single step with a simple upload workflow.

  • Transparent output Generate clean cutouts that are ready for compositing, product listings, and creative editing.

  • Simple one-image input Upload a single image and get a processed result without extra prompt engineering or manual masking.

  • Useful for production workflows Ideal for product photos, design assets, social content, and catalog preparation.

  • Production-ready API Easy to integrate into automated editing, creative tooling, and asset-preparation pipelines.


Parameters

ParameterRequiredDescription
imageYesInput image to process for background removal.

How to Use

  1. Upload your image — provide the image you want to process.
  2. Submit — run the model to remove the background.
  3. Download the result — use the transparent output in your workflow.

Example Use Case

Remove the background from a perfume bottle photo to create a clean transparent product cutout for e-commerce and ad creatives.


Pricing

Just $0.01 per image.


Best Use Cases

  • E-commerce product images — Create clean transparent cutouts for product listings and catalogs.
  • Marketing creatives — Isolate products or subjects for ads, banners, and promotional designs.
  • Design workflows — Prepare assets for compositing, layout, and visual editing.
  • Social media content — Quickly create clean foreground cutouts for posts and branded content.
  • Catalog and asset cleanup — Standardize image assets for internal or public-facing use.

Pro Tips

  • Use clear images with well-defined subjects for cleaner background removal.
  • Product photos with good contrast between subject and background usually work best.
  • Transparent outputs are especially useful for layered design workflows and marketplace listings.
  • Start with the highest-quality source image available for more precise edge handling.

Notes

  • image is the only required field.
  • Pricing is fixed at $0.01 per image.
  • The output is intended for transparent-background use cases.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/ideogram-ai/remove-background" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-The image whose background needs to be removed. JPEG, PNG and WebP formats are supported, maximum file size 10MB.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>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.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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