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wavespeed-ai/vosr2/image

VOSR2 Image Upscaler restores and upscales photos to 2K or 4K in a single pass, rebuilding fine structure, faces and small text with faithful color. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

upscaler
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Idle

$0.01per run·~100 / $1

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README

WaveSpeedAI VOSR2 Image Upscaler

VOSR2 Image Upscaler enlarges an input image to 2K or 4K while restoring fine visual detail in the same workflow. It is designed to improve hair, skin, foliage, fabric, small text, edges, and other high-frequency details while reducing blur and compression artifacts.

The input aspect ratio is preserved, making it suitable for photo restoration, portrait enhancement, product imagery, AI-generated images, and high-resolution display or print workflows.

Why Choose This?

  • 2K and 4K upscaling
    Generate higher-resolution outputs directly at the selected target resolution.

  • Detail restoration
    Recover fine structures such as hair, skin texture, fabric, foliage, edges, and small visual details.

  • Artifact cleanup
    Reduce blur, compression artifacts, and softness during the upscale process.

  • Aspect-ratio preservation
    Keep the original image composition and aspect ratio.

  • Simple workflow
    Upload an image, choose the target resolution and output format, then generate the enhanced result.

  • Fast processing
    Suitable for workflows where high-resolution output is needed without a lengthy restoration pipeline.

Parameters

ParameterRequiredDescription
imageYesURL of the image to upscale.
target_resolutionNoTarget output resolution: 2k or 4k. Default: 4k.
output_formatNoOutput image format: jpeg, png, or webp. Default: jpeg.

How to Use

  1. Provide an input image — Upload an image or provide its URL.
  2. Choose target resolution — Select 2k or 4k.
  3. Choose output format optional — Select jpeg, png, or webp.
  4. Submit — Generate the upscaled and restored image.
  5. Retrieve the result — Download the enhanced high-resolution output.

Pricing

Pricing is fixed at $0.01 per image.

Target ResolutionCost per Image
2K$0.01
4K$0.01

target_resolution and output_format do not add separate charges.

Best Use Cases

  • Photo restoration — Improve old, compressed, soft, or low-resolution photographs.
  • Portrait enhancement — Restore facial, hair, clothing, and skin detail.
  • Product imagery — Prepare product photos for e-commerce, advertising, or larger displays.
  • AI-generated images — Upscale generated artwork before publishing, printing, or further editing.
  • Print preparation — Create higher-resolution assets for posters, packaging, and physical media.
  • Large-display output — Improve image quality for presentations, screens, and high-resolution viewing.

Pro Tips

  • Use 2k when the source image is very small or when you want a more conservative upscale.
  • Use 4k when you need maximum output resolution for print, display, or detailed viewing.
  • Choose png when you want to avoid additional lossy compression.
  • Photographs and natural images generally benefit most from detail restoration.
  • For screenshots, charts, or flat graphics, inspect large uniform areas after upscaling because subtle texture may be introduced.
  • If a very small source looks overly smooth at 4k, try 2k instead.

Notes

  • image is required.
  • target_resolution defaults to 4k.
  • Supported target resolutions are 2k and 4k.
  • output_format defaults to jpeg.
  • Supported output formats are jpeg, png, and webp.
  • The original aspect ratio is preserved.
  • Very small inputs may require substantial enlargement, which can affect how much fine detail can be reconstructed.
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.

Vosr2 Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/vosr2/image 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 Vosr2 Image 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",
    "target_resolution": "4k",
    "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/wavespeed-ai/vosr2/image" \
  -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/wavespeed-ai/vosr2/image";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "target_resolution": "4k",
        "output_format": "jpeg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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",
    "target_resolution": "4k",
    "output_format": "jpeg"
}

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/vosr2/image", 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)

Vosr2 Image API — Frequently asked questions

What is the Vosr2 Image API?

Vosr2 Image is a WaveSpeedAI model for upscaling, exposed as a REST API on WaveSpeedAI. VOSR2 Image Upscaler restores and upscales photos to 2K or 4K in a single pass, rebuilding fine structure, faces and small text with faithful color. 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 Vosr2 Image 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/wavespeed-ai/vosr2-image.

How much does Vosr2 Image cost per run?

Vosr2 Image starts at $0.01 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 Vosr2 Image accept?

Key inputs: `image`, `enable_base64_output`, `enable_sync_mode`, `output_format`, `target_resolution`. 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/vosr2-image.

How do I get started with the Vosr2 Image 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 Vosr2 Image outputs commercially?

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

llms.txt — wavespeed-ai/vosr2/image for AI agents and LLMs