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Ic Light

wavespeed-ai /

IC-Light V2 is an AI-powered image relighting model. Relight any image with customizable lighting direction. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-image
Entrée

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studio portrait lighting, do not change the background

$0.2par exécution·~50 / $10

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studio portrait lighting, do not change the background

studio portrait lighting, do not change the background

Modèles associés

README

IC-Light

IC-Light is an AI-powered image relighting model that transforms the lighting of any photo with a simple text prompt. Change the direction, mood, and quality of light in your images — from dramatic side lighting to soft ambient glow — all without manual editing.

Why Choose This?

  • Text-driven relighting Describe the lighting you want (e.g., "sunlight", "soft studio light", "golden hour") and the model applies it naturally.

  • Directional control Choose from five lighting directions — None, Left, Right, Top, Bottom — for precise control over light placement.

  • Non-destructive transformation Preserves subject details, textures, and colors while only changing the lighting characteristics.

  • Product-ready results Perfect for e-commerce, photography enhancement, and creative projects requiring consistent lighting.

Parameters

ParameterRequiredDescription
promptYesDescribe the desired lighting effect (e.g., sunlight, studio light, warm glow)
imageYesSource image to relight (upload or URL)
lighting_directionNoLight direction: None, Left, Right, Top, Bottom

How to Use

  1. Upload your image — drag and drop or paste a public URL.
  2. Write your prompt — describe the lighting style you want (e.g., "sunlight", "cinematic side lighting", "soft diffused light").
  3. Select lighting direction — choose where the light comes from (Left, Right, Top, Bottom) or None for ambient.
  4. Run — submit and download your relit image.

Pricing

OutputCost
Per image$0.20

Best Use Cases

  • E-commerce Photography — Standardize product lighting across catalogs without reshooting.
  • Portrait Enhancement — Add flattering light to photos taken in poor lighting conditions.
  • Creative Projects — Experiment with dramatic lighting for artistic effects.
  • Real Estate — Brighten interior shots or add warm, inviting light to property photos.
  • Social Media Content — Elevate everyday photos with professional-quality lighting.

Pro Tips

  • Use specific lighting terms in your prompt for better results (e.g., "warm golden hour sunlight" vs. just "light").
  • Combine prompt and direction for maximum control — describe the quality while specifying the angle.
  • For product shots, "Left" or "Right" directions often create appealing depth and dimension.
  • Use "None" direction when you want the prompt to fully control lighting placement.
  • Works best with clear subjects and well-defined edges.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • For best results, use high-quality source images with clear subjects.
  • The model preserves original image resolution.
Remarque :Ce site utilise des modèles d'IA fournis par des tiers.

Ic Light API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ic-light 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 Ic Light below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "lighting_direction": "None"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ic-light" \
  -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/wavespeed-ai/ic-light";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "lighting_direction": "None"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "lighting_direction": "None"
}

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/wavespeed-ai/ic-light", 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)

Ic Light API — Frequently asked questions

What is the Ic Light API?

Ic Light is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. IC-Light V2 is an AI-powered image relighting model. Relight any image with customizable lighting direction. 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 Ic Light 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/wavespeed-ai/ic-light.

How much does Ic Light cost per run?

Ic Light starts at $0.20 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 Ic Light accept?

Key inputs: `prompt`, `image`, `lighting_direction`. 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/wavespeed-ai/ic-light.

How long does Ic Light take to generate?

Median end-to-end generation time on WaveSpeedAI is around 239 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Ic Light outputs commercially?

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

Ic Light | Fast Image Editing API | WaveSpeedAI