Home/Explore/ByteDance/Seedream V5.5/Layer Decomposition

Seedream 5.5 Layers Image Decomposition API

bytedance/seedream-v5.5/layer-decomposition

Seedream 5.5 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 Tools
Input

Drag & drop or click to upload

preview

Idle

$0.6per run·~16 / $10

ExamplesView all

Related Models

README

Seedream 5.5 Layer Decomposition

Seedream 5.5 Layer Decomposition separates a single input image into a base image and transparent image layers for compositing, design, and editing workflows. It breaks 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.

  • Transparent PNG layers
    Every layer is returned as a PNG with an alpha channel, ready to drop into a design tool.

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

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

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

  • Flexible resolution tiers
    Choose 1k, 1.5k, or 2k depending on your workflow needs.

Parameters

ParameterRequiredDescription
imageYesThe image to decompose into layers. Supports PNG and JPEG images.
promptNoOptional positive prompt describing the desired layers, targets, objects, or grouping behavior.
resolutionNoOutput resolution tier: 1k, 1.5k, or 2k.
max_imagesNoMaximum number of images to return, base image plus layers: 2 to 100. Default: 30. The price is set by this value (see Pricing).
output_formatNoFormat of the base image: png (default) or jpeg. Every layer is a PNG with transparency.

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 resolution — Select 1k, 1.5k, or 2k.
  4. Set max_images optional — A larger value allows a finer split and costs more.
  5. Submit — Generate the decomposed image result: the base image first, then the layers.

Pricing

Each request costs max_images times the per-image price of the selected resolution. You are charged for max_images, the most images the request can return, not for the number actually returned: a simple image may come back with fewer layers than max_images and still costs the full amount. Set max_images to about the number of layers you need.

ResolutionPrice per image
1k$0.02
1.5k$0.02
2k$0.027

The default max_images is 30, so a default request costs $0.60 at 1k or 1.5k and $0.81 at 2k. Examples: max_images 5 at 1k costs $0.10; max_images 100 at 2k costs $2.70.

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.

Pro Tips

  • Use a clear image with distinct foreground, subject, and background regions.
  • Add a prompt when you need specific objects, groupings, or layer behavior, and keep it focused on what should become separate layers.
  • Choose 1k or 1.5k for lower-cost iteration, and 2k when higher-resolution layers are needed.
  • 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 v5.5 Layer Decomposition API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.5/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 v5.5 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",
    "max_images": 30,
    "output_format": "png"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/bytedance/seedream-v5.5/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="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/bytedance/seedream-v5.5/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "resolution": "1k",
        "max_images": 30,
        "output_format": "png"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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",
    "resolution": "1k",
    "max_images": 30,
    "output_format": "png"
}

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-v5.5/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 = 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)

Seedream v5.5 Layer Decomposition API — Frequently asked questions

What is the Seedream v5.5 Layer Decomposition API?

Seedream v5.5 Layer Decomposition is a ByteDance model for image processing, exposed as a REST API on WaveSpeedAI. Seedream 5.5 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 v5.5 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 Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/bytedance/bytedance-seedream-v5.5-layer-decomposition.

How much does Seedream v5.5 Layer Decomposition cost per run or per second?

Seedream v5.5 Layer Decomposition starts at $0.6 per run or per second. 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 v5.5 Layer Decomposition accept?

Key inputs: `prompt`, `image`, `resolution`, `max_images`, `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-v5.5-layer-decomposition.

How do I get started with the Seedream v5.5 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 v5.5 Layer Decomposition outputs commercially?

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

llms.txt — bytedance/seedream-v5.5/layer-decomposition for AI agents and LLMs