Video Restorer cleans up damaged footage: strip compression artifacts from low-bitrate video or bring out-of-focus footage back into sharp focus, keeping the subject, framing and motion exactly as they are. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.2per run·~50 / $10
Video Restorer improves damaged footage while preserving the original content, framing, and motion. It supports two restoration modes: decompress for low-bitrate compression artifacts and deblur for soft or out-of-focus footage.
Use it to clean up blocky, smeared, or blurry videos without changing the scene itself.
Video restoration workflow
Restore damaged footage while keeping the original subject, timing, framing, and motion.
Compression artifact removal
Use decompress to reduce macroblocking, ringing, banding, chroma bleed, and other low-bitrate artifacts.
Focus recovery
Use deblur to sharpen soft or out-of-focus footage.
Prompt-guided restoration
Optionally describe the scene to help guide the restoration process.
Multiple output resolutions
Choose 480p, 720p, or 1080p while preserving the original aspect ratio.
Seed support
Set a seed when reproducible restoration results are needed.
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Input video URL or uploaded video. Up to 120 seconds is processed. |
| mode | No | Restoration mode: decompress or deblur. Default: decompress. |
| prompt | No | Short description of the scene. Leave empty for generic restoration. |
| target_resolution | No | Output resolution: 480p, 720p, or 1080p. Default: 720p. Aspect ratio is preserved. |
| seed | No | Random seed for reproducible results. |
decompress for compression artifacts or deblur for soft-focus footage.480p, 720p, or 1080p.Pricing is based on input video duration and selected target_resolution.
Billed duration is rounded up to the next whole second, with a minimum billed duration of 3 seconds and a maximum billed duration of 120 seconds.
| Output Resolution | Per 5s | Per second |
|---|---|---|
| 480p | $0.10 | $0.02 |
| 720p | $0.20 | $0.04 |
| 1080p | $0.50 | $0.10 |
| Input Duration | Billed Duration | 480p | 720p | 1080p |
|---|---|---|---|---|
| 1s | 3s | $0.06 | $0.12 | $0.30 |
| 3s | 3s | $0.06 | $0.12 | $0.30 |
| 5s | 5s | $0.10 | $0.20 | $0.50 |
| 10s | 10s | $0.20 | $0.40 | $1.00 |
| 60s | 60s | $1.20 | $2.40 | $6.00 |
| 120s | 120s | $2.40 | $4.80 | $12.00 |
mode, prompt, and seed do not add separate charges.
decompress for blocky footage, smeared colors, banding, ringing, or compression artifacts.deblur for footage that is generally soft or out of focus.deblur targets defocus blur, not motion blur.seed when you want to reproduce a restoration result.120 seconds.120 seconds is not processed or billed.video is required.mode defaults to decompress.target_resolution defaults to 720p.3–120 seconds.3 seconds.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/video-restorer with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Video Restorer below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"mode": "decompress",
"target_resolution": "720p"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-restorer" \
-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
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-restorer";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"mode": "decompress",
"target_resolution": "720p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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));
}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 = {
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"mode": "decompress",
"target_resolution": "720p"
}
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/video-restorer", 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)Video Restorer is a WaveSpeedAI model for video editing, exposed as a REST API on WaveSpeedAI. Video Restorer cleans up damaged footage: strip compression artifacts from low-bitrate video or bring out-of-focus footage back into sharp focus, keeping the subject, framing and motion exactly as they are. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
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/video-restorer.
Video Restorer starts at $0.2 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.
Key inputs: `prompt`, `video`, `seed`, `mode`, `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/video-restorer.
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.
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.