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AI Ghibli Filter Video transforms a photo into a Studio Ghibli anime style video with customizable duration. Ready-to-use REST inference API, no coldstarts, affordable pricing.

image-to-video
Input

Idle

$0.3per run·~33 / $10

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README

AI Ghibli Filter Video

Transform any video clip into a hand-painted Studio Ghibli-style animated scene. AI Ghibli Filter Video reimagines your real-world footage with the soft watercolor textures, warm color palettes, and dreamlike atmosphere that define Ghibli's iconic visual style — no animation skills required.

Upload a video, set your duration, and watch your everyday moments become scenes straight out of a Miyazaki film.

Why You'll Love It

  • Authentic Ghibli aesthetics Captures the signature soft brushwork, painterly backgrounds, and warm, luminous color grading of classic Studio Ghibli films.

  • Works on any scene Landscapes, street scenes, people in motion — the filter adapts beautifully to a wide range of real-world footage.

  • Adjustable duration Process between 5 and 15 seconds of video to get the perfect stylized clip.

  • Instant, shareable results Ready to post, share, or use as creative content in seconds.

How to Use

  1. Upload your video — a clear clip with good lighting and stable framing works best.
  2. Set duration — drag the slider to choose between 5 and 15 seconds.
  3. Hit Run — AI transforms your footage into Ghibli-style animation.
  4. Download and share your stylized video.

Pricing

DurationCost
5s$0.30
10s$0.60
15s$0.90

Rate: $0.06 per second.

Best Use Cases

  • Social media content — Turn travel clips, nature footage, or everyday moments into viral Ghibli-style videos.
  • Creative projects — Add a hand-painted animated feel to short films, intros, or mood reels.
  • Gifts and keepsakes — Reimagine memorable moments as something magical and artistic.
  • Fan art & tributes — Celebrate your love of Studio Ghibli with your own footage as the canvas.

Pro Tips

  • Outdoor scenes with natural light, greenery, and movement produce the most Ghibli-like results.
  • Smooth, stable footage transforms more cleanly than shaky or heavily compressed clips.
  • Try running the same clip at different durations to find the most visually striking segment.
  • Scenes with a clear subject and open background tend to look most cinematic after transformation.

Notes

  • Image (video) is the only required field.
  • Duration range is 5 to 15 seconds.
  • Ensure video URLs are publicly accessible if using a link rather than a direct upload.
  • Please ensure your content complies with WaveSpeed AI's usage policies.
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.

Ghibli Filter Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ghibli-filter/video 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 Ghibli Filter Video 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",
    "duration": 5
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ghibli-filter/video" \
  -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/ghibli-filter/video";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "duration": 5
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "duration": 5
}

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/ghibli-filter/video", 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)

Ghibli Filter Video API — Frequently asked questions

What is the Ghibli Filter Video API?

Ghibli Filter Video is a WaveSpeedAI model for video generation from images, exposed as a REST API on WaveSpeedAI. AI Ghibli Filter Video transforms a photo into a Studio Ghibli anime style video with customizable duration. Ready-to-use REST inference API, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Ghibli Filter Video 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/ghibli-filter-video.

How much does Ghibli Filter Video cost per run?

Ghibli Filter Video starts at $0.30 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 Ghibli Filter Video accept?

Key inputs: `image`, `duration`. 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/ghibli-filter-video.

How long does Ghibli Filter Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 153 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 Ghibli Filter Video 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.

Ghibli Filter Video | Fast Image-to-Video API on WaveSpeedAI