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Recraft Crisp Upscale

recraft-ai /

Recraft Crisp Upscale enhances textures, fine details, and facial features to add depth beyond simple resolution boosts. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

upscaler
入力

待機中

$0.0041回あたり·~250 / $1

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関連モデル

README

Recraft Crisp Upscale – Image Restoration and Super-Resolution

Recraft Crisp Upscale is an AI-powered enhancer from Recraft that turns low-resolution, noisy, or aged photos into sharper, cleaner, high-resolution images. It is especially strong on portraits and fine details, making it ideal for photo restoration, profile pictures, product images, and social media visuals.

Why it stands out

  • Crisp detail recovery Sharpens edges, textures, and facial features so eyes, hair, and fabric folds look clean and well-defined.

  • Noise and artifact reduction Smooths grain, JPEG blocks, and minor motion blur while preserving structure and character identity.

  • Natural, photo-friendly look Enhances clarity without plastic skin or over-sharpening, keeping the original mood and style of the image.

  • Drop-in enhancement step Works as a final polish in your pipeline: restore old scans, then pass the result straight to design tools, websites, or print.

  • Flexible delivery Returns a standard image URL by default, or base64-encoded data when you enable base64 output via API.

Limits and performance

  • Input: single image (portrait, product photo, scan, or other)
  • Output: enhanced, higher-quality version of the same image (same composition and framing)
  • Typical processing time: a few seconds per image, depending on size and queue load
  • Best for: portraits and real-world photos; heavily stylised art may benefit but is not the primary target

The model focuses on restoration and super-resolution; it does not change content or composition beyond subtle aesthetic enhancement.

Pricing

Simple per-image billing:

  • $0.004 per processed image

Pro tips for best quality

  • Use the highest-quality version of your original image; less compression and higher resolution give the model more to work with.
  • For very old or heavily damaged scans, consider basic dust or scratch removal before running Crisp Upscale.
  • Use it as the last step after colour correction or light retouching to maximise overall clarity and perceived resolution.
注記:本サイトは第三者が提供するAIモデルを使用しています。

Recraft Crisp Upscale API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/recraft-ai/recraft-crisp-upscale 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 Recraft Crisp Upscale 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"
}
JSON
)

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

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/recraft-ai/recraft-crisp-upscale", 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)

Recraft Crisp Upscale API — Frequently asked questions

What is the Recraft Crisp Upscale API?

Recraft Crisp Upscale is a Recraft model for upscaling, exposed as a REST API on WaveSpeedAI. Recraft Crisp Upscale enhances textures, fine details, and facial features to add depth beyond simple resolution boosts. 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 Recraft Crisp Upscale 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/recraft-ai/recraft-ai-recraft-crisp-upscale.

How much does Recraft Crisp Upscale cost per run?

Recraft Crisp Upscale starts at $0.004 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 Recraft Crisp Upscale accept?

Key inputs: `image`, `enable_base64_output`. 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/recraft-ai/recraft-ai-recraft-crisp-upscale.

How long does Recraft Crisp Upscale take to generate?

Median end-to-end generation time on WaveSpeedAI is around 11 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 Recraft Crisp Upscale outputs commercially?

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

Recraft Crisp Upscale | AI Image Upscaler API | WaveSpeedAI