Bytedance Seedream V5.0 Flash Layer Decomposition API Documentation

Bytedance Seedream V5.0 Flash Layer Decomposition API Documentation

Playground

Try it on WaveSpeedAI!

Seedream V5.0 Flash Layer Decomposition separates a single image into a base image and transparent layers faster and at lower cost than Seedream V5.0 Pro, enabling flexible compositing, image editing, asset extraction, and layered design workflows at one price for 1K / 1.5K / 2K. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Seedream V5.0 Flash Layer Decomposition separates a single input image into a base image and transparent image layers for compositing, design, and editing workflows. It shares Seedream V5.0 Pro Layer Decomposition’s capability and returns layers faster at a lower price.


Why Choose This?

  • Layered image decomposition
    Separate one image into a base image and up to 16 transparent layers.

  • 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 identifies key visual elements automatically.

  • One price for every resolution
    1k, 1.5k, and 2k all cost the same.


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.
output_formatNoOutput image format: jpeg or png. Use png to keep layer 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 resolution1k, 1.5k, or 2k; the price is the same.
  4. Choose output format — Select png for transparent layers, or jpeg.
  5. Submit — Generate the base image and layers.

Pricing

A flat $0.459 per request at every resolution.

ResolutionPrice
1k$0.459
1.5k$0.459
2k$0.459

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, products, or scene elements from campaign images.
  • Creative editing — Rearrange, restyle, replace, or refine isolated image layers.
  • High-volume layer extraction — Process large image sets where speed and cost matter.

Pro Tips

  • Use a clear image with distinct foreground, subject, and background regions.
  • Add a prompt when you need specific objects, groupings, or a fixed number of layers.
  • Use png output when you need the layers’ transparent backgrounds.
  • Since every resolution costs the same, pick 2k when you need higher-resolution layers.
  • Avoid cluttered scenes when you need precise layer separation.

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",
  "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-flash/layer-decomposition" \
  -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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

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

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-The image to decompose into layers.
promptstringNo-The positive prompt for the generation.
resolutionstringNo1k1k, 1.5k, 2kThe size of the generated media in pixels (width*height).
output_formatstringNojpegjpeg, pngThe format of the output image.

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.statusstringTask status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses.
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.statusstringStatus: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses
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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