Luma Photon Modify

Luma Photon Modify

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Luma Photon Modify is a text-to-image generation model that converts text prompts into images for creative and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Edit and transform images with natural language using Luma Photon Modify. Simply describe the changes you want — swap backgrounds, modify elements, or transform scenes — and watch your image transform instantly. Perfect for quick edits, background replacements, and creative modifications.

Why It Looks Great

  • Natural language editing: Describe changes in plain English — no complex tools needed.
  • Background replacement: Seamlessly swap backgrounds while preserving subjects.
  • Scene transformation: Modify environments, lighting, and context effortlessly.
  • Subject preservation: Maintains the integrity of your main subject during edits.
  • Prompt Enhancer: Built-in tool to refine your editing instructions.
  • Ultra-affordable: Professional image editing at just $0.015 per image.

Parameters

ParameterRequiredDescription
promptYesText instruction describing the edit or modification you want.
imageNoSource image to modify (upload or public URL).

How to Use

  1. Write your edit instruction — describe what you want to change.
  2. Use Prompt Enhancer (optional) — click to refine your instruction.
  3. Upload your image — drag and drop or paste a public URL.
  4. Run — click the button to apply the edit.
  5. Download — preview and save your modified image.

Pricing

Flat rate per image.

OutputCost
Per image$0.015

Best Use Cases

  • Background Replacement — Change backgrounds to any scene or setting.
  • Scene Transformation — Move subjects to different environments or contexts.
  • Creative Compositing — Place subjects in imaginative or fantastical settings.
  • Product Photography — Swap product backgrounds for professional presentations.
  • Social Media Content — Quick edits for engaging visual content.

Example Prompts

  • “Change the background to large performance stage”
  • “Replace the background with a tropical beach at sunset”
  • “Put the subject in a futuristic cityscape”
  • “Change the setting to a cozy coffee shop interior”
  • “Transform the background to a snowy mountain landscape”
  • “Place in a professional studio with white backdrop”

Pro Tips for Best Results

  • Be specific about the new background or setting you want.
  • Photon Modify excels at background replacements and scene changes.
  • Include lighting and atmosphere details for more cohesive results.
  • Works best when the subject is clearly defined in the original image.
  • Use for quick iterations — at $0.015, you can experiment freely.
  • Combine with descriptive atmosphere: “dramatic lighting”, “warm tones”, “soft focus”.

Notes

  • If using a URL, ensure it is publicly accessible.
  • Best results come from images with clear subject-background separation.
  • Processing is fast and efficient for rapid workflow integration.
  • Ideal for batch processing due to low cost per image.

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'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/luma/photon-modify" \
  -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
promptstringYes-The positive prompt for the generation.
imagestringNo-The image to generate an image from.
enable_base64_outputbooleanNofalse-If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.

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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