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HappyHorse 1.1 Image to Video API

alibaba /

Alibaba HappyHorse 1.1 Image to Video animates a reference image into a cinematic 720P or 1080P video, with optional text prompt guidance, smooth camera movement, and expressive, stable motion. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
Ввод

Ожидание

$0.7за запуск·~14 / $10

Далее:

ПримерыСмотреть всё

The whale slowly dives through the clouds, sending waves of mist outward. The hot air balloon sways from the air current, sunlight breaks through the cloud layer, and the camera follows the whale from above

Похожие модели

README

Alibaba Happy Horse 1.1 Image-to-Video

Alibaba Happy Horse 1.1 Image-to-Video animates a reference image into a cinematic video with optional text guidance for motion, camera movement, and scene direction. It supports 720p and 1080p output, while preserving the reference image's subject, composition, and visual style.

Why Choose This?

  • Image-faithful generation
    Preserves the reference image's subject, composition, and style while adding motion.

  • Optional prompt guidance
    Describe the camera movement, mood, action, and scene development in plain language.

  • Cinematic motion
    Generate smooth, expressive motion with stable subject preservation.

  • Flexible resolution options
    Choose 720p for standard generation or 1080p for higher-resolution output.

  • Production-ready API
    Use REST inference for image-to-video generation workflows.

Parameters

ParameterRequiredDescription
imageYesFirst-frame image URL. Supported formats: JPEG, PNG, BMP, WEBP. Minimum dimension: 300 px. Aspect ratio: 1:2.5 to 2.5:1. Maximum file size: 10 MB.
promptNoOptional text prompt guiding the animation. Maximum length: 2500 characters.
resolutionNoOutput resolution: 720p or 1080p. Default: 720p.
durationNoVideo length in seconds. Supported range: 3 to 15. Default: 5.
seedNoRandom seed for reproducibility. Supported range: 0 to 2147483647.

How to Use

  1. Upload image — Provide a first-frame image URL.
  2. Add prompt guidance (optional) — Describe the desired motion, camera behavior, mood, or action.
  3. Select resolution — Choose 720p or 1080p.
  4. Set duration — Choose a duration from 3 to 15 seconds.
  5. Set seed (optional) — Use a fixed seed for reproducible results.
  6. Generate — Create the image-to-video output.

Pricing

Pricing scales linearly with duration.

ResolutionPer 5sPer second
720p$0.70$0.14
1080p$0.945$0.189

Examples (5s):

ResolutionCost
720p$0.70
1080p$0.945

Examples (10s):

ResolutionCost
720p$1.40
1080p$1.89

Best Use Cases

  • Image-to-video animation — Animate a reference image into a short video.
  • Cinematic motion generation — Add smooth camera movement and scene motion to a still image.
  • Character and subject animation — Preserve the main subject while generating natural motion.
  • Creative video previews — Create short visual clips from concept images or storyboards.
  • Social media content — Generate short-form video assets from still images.

Pro Tips

  • Use a clear first-frame image with the main subject visible.
  • Keep the prompt focused on motion, camera behavior, and scene development.
  • Use 720p for standard generation and lower cost.
  • Use 1080p when higher-resolution output is needed.
  • Use a fixed seed when you want more reproducible results.
  • Make sure the input image matches the desired output composition.

Related Models

Примечание:Этот сайт использует модели ИИ, предоставляемые третьими лицами.

Happyhorse 1.1 Image To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/image-to-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 Happyhorse 1.1 Image To Video below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "resolution": "720p",
    "duration": 5
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/alibaba/happyhorse-1.1/image-to-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/alibaba/happyhorse-1.1/image-to-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "resolution": "720p",
        "duration": 5
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "resolution": "720p",
    "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/alibaba/happyhorse-1.1/image-to-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)

Happyhorse 1.1 Image To Video API — Frequently asked questions

What is the Happyhorse 1.1 Image To Video API?

Happyhorse 1.1 Image To Video is a Alibaba model for video generation from images, exposed as a REST API on WaveSpeedAI. Alibaba HappyHorse 1.1 Image to Video animates a reference image into a cinematic 720P or 1080P video, with optional text prompt guidance, smooth camera movement, and expressive, stable motion. 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 Happyhorse 1.1 Image To 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/alibaba/alibaba-happyhorse-1.1-image-to-video.

How much does Happyhorse 1.1 Image To Video cost per run?

Happyhorse 1.1 Image To Video starts at $0.70 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 Happyhorse 1.1 Image To Video accept?

Key inputs: `prompt`, `image`, `resolution`, `duration`, `seed`. 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/alibaba/alibaba-happyhorse-1.1-image-to-video.

How long does Happyhorse 1.1 Image To Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 137 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 Happyhorse 1.1 Image To Video outputs commercially?

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

HappyHorse 1.1 Image to Video API | WaveSpeedAI