Video Cleaner removes people, vehicles and other moving subjects from a video and rebuilds the background behind them, producing a clean plate of the same shot with the camera motion intact. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.2per run·~50 / $10
Video Cleaner removes people, pedestrians, vehicles, and other moving subjects from a video, then rebuilds the background behind them. It preserves the source video's camera movement, static scene structure, lighting, framing, and duration while creating a cleaner plate for editing, compositing, or restoration workflows.
Moving-subject removal
Remove people, crowds, cars, bikes, and other dynamic elements from video footage.
Background reconstruction
Rebuild the background where moving subjects were removed, including architecture, ground details, foliage, and static scene elements.
Clean plate generation
Create cleaner footage for compositing, advertising, restoration, or post-production workflows.
Prompt-guided cleanup
Use prompt to name extra objects that should also be removed.
Multiple output resolutions
Choose 480p, 720p, or 1080p while preserving the original aspect ratio.
Seed support
Set a seed when reproducible cleanup results are needed.
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Input video URL or uploaded video. Up to 120 seconds is processed. |
| prompt | No | Optional comma-separated list of extra objects to remove, such as bicycle, dog, handlebars. |
| target_resolution | No | Output resolution: 480p, 720p, or 1080p. Default: 720p. Aspect ratio is preserved. |
| seed | No | Random seed for reproducible results. |
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 | $12.00 |
prompt and seed do not add separate charges.
prompt when a specific object remains after the first cleanup pass.bicycle, dog, car, or person in the background.seed when you want to reproduce a result.120 seconds.120 seconds is not processed or billed.video is required.target_resolution defaults to 720p.3–120 seconds.3 seconds.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/video-cleaner with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Video Cleaner below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"target_resolution": "720p"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/video-cleaner" \
-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-cleaner";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"target_resolution": "720p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${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",
"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-cleaner", 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 Cleaner is a WaveSpeedAI model for video processing, exposed as a REST API on WaveSpeedAI. Video Cleaner removes people, vehicles and other moving subjects from a video and rebuilds the background behind them, producing a clean plate of the same shot with the camera motion intact. 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-cleaner.
Video Cleaner 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`, `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-cleaner.
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.