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ideogram-ai/ideogram-v3/remove-text

Ideogram V3 Layerize Text separates flat graphic images into editable layers, extracting text and background for professional design workflows. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Image Object Removal
Ввод

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Ожидание

$0.09за запуск·~11 / $1

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ПримерыСмотреть всё

Похожие модели

README

Ideogram V3 Layerize Text

Ideogram V3 Layerize Text separates the text layer from the background in any image, returning the text as a clean transparent PNG ready for editing, replacement, or compositing. Upload an image with text and get back an isolated text layer in seconds.

How to Use

  1. Upload your image — provide any image containing text via URL or drag-and-drop.
  2. Submit — the model extracts and isolates the text layer with a transparent background.
  3. Download your clean text layer PNG ready for compositing or editing.

Pricing

Just $0.09 per image.

Best Use Cases

  • Design editing — Extract text from existing designs to reuse, reposition, or restyle it independently.
  • Localization & translation — Remove original text from images cleanly before replacing it with translated content.
  • Template creation — Strip text from branded assets to create reusable background templates.
  • Typography workflows — Isolate text elements for use in compositing, motion graphics, or print layouts.

Notes

  • image is the only required field.
  • Output is a PNG file with a transparent background containing only the isolated text layer.
  • Ensure image URLs are publicly accessible if using a link rather than a direct upload.
  • Please ensure your content complies with Ideogram's usage policies.
Примечание:Этот сайт использует модели ИИ, предоставляемые третьими лицами. Цены в документации справочные и могут устареть. Кнопка Generate показывает оценку; действует окончательная стоимость задачи.

Ideogram v3 Remove Text API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v3/remove-text with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ideogram v3 Remove Text below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_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/ideogram-v3/remove-text" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

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

# 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' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v3/remove-text";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/ideogram-ai/ideogram-v3/remove-text", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Ideogram v3 Remove Text API — Frequently asked questions

What is the Ideogram v3 Remove Text API?

Ideogram v3 Remove Text is a Ideogram model for image object removal, exposed as a REST API on WaveSpeedAI. Ideogram V3 Layerize Text separates flat graphic images into editable layers, extracting text and background for professional design workflows. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Ideogram v3 Remove Text API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/ideogram-ai/ideogram-ai-ideogram-v3-remove-text.

How much does Ideogram v3 Remove Text cost per run?

Ideogram v3 Remove Text starts at $0.09 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Ideogram v3 Remove Text accept?

Key inputs: `image`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/ideogram-ai/ideogram-ai-ideogram-v3-remove-text.

How long does Ideogram v3 Remove Text take to generate?

Reported generation time on WaveSpeedAI is around 19 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.

Can I use Ideogram v3 Remove Text outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Ideogram). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — ideogram-ai/ideogram-v3/remove-text for AI agents and LLMs