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Seedream V5.0 Pro Layer Decomposition separates a single image into a base image and transparent layers, enabling flexible compositing, image editing, asset extraction, and layered design workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-image
Input

Idle

$0.75per run·~13 / $10

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Seedream V5.0 Pro Layer Decomposition

Seedream V5.0 Pro Layer Decomposition separates a single input image into one base image and transparent image layers for compositing, design, and editing workflows. It is useful for breaking a flat image into editable visual components that can be reused, rearranged, or refined in downstream creative tools.

Why Choose This?

  • Layered image decomposition
    Separate one image into a base image and multiple transparent layers.

  • Editing-ready outputs
    Use the decomposed layers for compositing, retouching, layout design, and creative editing.

  • Prompt-guided layer control
    Optionally describe the desired layers, targets, objects, bounding boxes, or grouping behavior.

  • Automatic element detection
    When no prompt is provided, the model can identify the main elements automatically.

  • Flexible output sizes
    Choose auto, 1k, 1.5k, or 2k depending on your workflow needs.

  • Transparent PNG layers
    Extracted layers are returned as PNG files with transparency for easier reuse.

Parameters

ParameterRequiredDescription
imageYesA single PNG or JPEG image to decompose.
promptNoOptional instruction describing the desired layers, targets, objects, bounding boxes, or grouping. If omitted, the model identifies the main elements automatically.
sizeNoOutput size: auto, 1k, 1.5k, or 2k.
output_formatNoOutput format for the base image: jpeg or png. Transparent layers are always returned as PNG.

How to Use

  1. Upload an image — Provide a single PNG or JPEG image for decomposition.
  2. Add a prompt optional — Describe the objects, groups, targets, or layer structure you want.
  3. Choose size — Select auto, 1k, 1.5k, or 2k.
  4. Choose output format — Select jpeg or png for the base image.
  5. Configure prompt optimization optional — Use optimize_prompt_options when you want standard or fast prompt optimization.
  6. Submit — Generate the base image and transparent layer outputs.

Pricing

Pricing is based on the selected size.

SizePrice
1k$0.765
1.5k$0.765
2k$1.53

Best Use Cases

  • Compositing workflows — Separate foreground objects and background elements for layered editing.
  • Design production — Convert flat images into editable visual components.
  • Marketing asset preparation — Extract reusable objects, people, products, or scene elements from campaign images.
  • Creative editing — Rearrange, restyle, replace, or refine isolated image layers.
  • Layout workflows — Prepare clean visual parts for presentations, ads, thumbnails, and design systems.
  • Post-production — Use decomposed layers for downstream image editing, animation, or visual effects workflows.

Pro Tips

  • Use a clear image with distinct foreground, subject, and background regions.
  • Add a prompt when you need specific objects, groupings, or layer order.
  • Keep the prompt focused on what should become separate layers.
  • Choose 2k when higher-resolution layer outputs are needed.
  • Use png for the base image when you want a cleaner image-editing workflow.
  • Avoid cluttered scenes when you need precise layer separation.

Related Models

Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Seedream v5.0 Pro Layer Decomposition API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.0-pro/layer-decomposition 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 Seedream v5.0 Pro Layer Decomposition 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",
    "resolution": "1k",
    "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.0-pro/layer-decomposition" \
  -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=$(printf '%s' "$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' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.0-pro/layer-decomposition";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "resolution": "1k",
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  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",
    "resolution": "1k",
    "output_format": "jpeg"
}

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/bytedance/seedream-v5.0-pro/layer-decomposition", 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 = task.get("urls", {}).get("get") or 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"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Seedream v5.0 Pro Layer Decomposition API — Frequently asked questions

What is the Seedream v5.0 Pro Layer Decomposition API?

Seedream v5.0 Pro Layer Decomposition is a ByteDance model for image editing, exposed as a REST API on WaveSpeedAI. Seedream V5.0 Pro Layer Decomposition separates a single image into a base image and transparent layers, enabling flexible compositing, image editing, asset extraction, and layered design workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Seedream v5.0 Pro Layer Decomposition 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 production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bytedance/bytedance-seedream-v5.0-pro-layer-decomposition.

How much does Seedream v5.0 Pro Layer Decomposition cost per run?

Seedream v5.0 Pro Layer Decomposition starts at $0.75 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 Seedream v5.0 Pro Layer Decomposition accept?

Key inputs: `prompt`, `image`, `resolution`, `output_format`. 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/bytedance/bytedance-seedream-v5.0-pro-layer-decomposition.

How do I get started with the Seedream v5.0 Pro Layer Decomposition API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Seedream v5.0 Pro Layer Decomposition outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (ByteDance). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Seedream V5.0 Pro Layer Decomposition API on WaveSpeedAI