Seedream 5.0 Pro is LIVE | Try in Image Generator →
Home/Explore/Higgsfield/Dop/Image To Video

Dop Image to Video

higgsfield /

DoP converts static images into dynamic 5-second Image-to-Video clips with AI motion synthesis for realistic motion effects. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
Input

Idle

$0.125per run·~80 / $10

Next:

ExamplesView all

boxing

Related Models

README

Higgsfield DoP — Image-to-Video Model

Higgsfield DoP (Director of Photography) transforms static images into cinematic 5-second motion clips, breathing life into still visuals through advanced AI motion synthesis. It is designed to replicate natural camera dynamics, subtle environmental movement, and realistic scene depth — making every frame feel alive.

🎬 Why it stands out

  • AI Motion Synthesis Applies physically consistent camera movement and environmental dynamics to still images, creating smooth and natural video motion.

  • Cinematic Look and Feel Simulates depth of field, lighting shifts, and parallax effects inspired by real-world cinematography.

  • High Visual Fidelity Maintains the original image’s resolution, color balance, and subject clarity while adding dynamic motion layers.

  • One-Click Storytelling Converts a single static image into an engaging 5-second video ready for social media, advertising, or creative production.

  • Versatile Creative Control Ideal for concept visualization, animated product showcases, fashion imagery, and digital storytelling.

⚙️ How to use

  • Input: First frame image and last frame image (JPEG / PNG / WEBP)
  • Output: 5-second MP4 video with smooth AI motion
  • Motion Types: 360 Orbit, 3D Rotation, Abstract, Action Run, Agent Reveal, Angel Wings, Arc Left, Arc Right...
  • Simple prompt: just describe your desired style, and the model will handle the rest beautifully.

⚡ Model Versions

Higgsfield DoP offers three model variants optimized for different creative and production needs:

  • dop-lite — Entry-level model offering basic speed and efficiency, ideal for quick concept previews or rough motion drafts.
  • dop-turbo — Mid-tier mode with 2× faster generation and priority queue access, suitable for smooth and detailed outputs in less time.
  • dop-preview — Premium mode ensuring highest video quality, enhanced lighting realism, and priority processing for professional-grade production.

💰 Pricing

ModelDurationDescriptionUSD
Lite5sBasic speed$0.125
Turbo5s2× speed, priority queue$0.406
Preview5sHigher quality, priority queue$0.563

💡 Best Use Cases

  • Social Media Marketing — Turn static campaign visuals into scroll-stopping videos.
  • E-commerce & Product Ads — Add depth and subtle motion to product photography.
  • Creative Portfolios — Animate artwork and photography to showcase atmosphere and style.
  • Film & Design Previsualization — Prototype cinematic shots from reference stills.

📝 Notes

  • Please ensure your uploaded images are clear, well-lit, and properly licensed.
  • If motion generation results appear unstable, try re-uploading with simpler composition or fewer overlapping subjects.
  • If your prompt is too complex, the generated result may not be as accurate or visually consistent.
Note:This website uses AI models provided by third parties.

Dop Image To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/higgsfield/dop/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 Dop 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",
    "motions": [
        {
            "motion": "360 Orbit",
            "strength": 0
        }
    ],
    "options": "dop-turbo"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/higgsfield/dop/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/higgsfield/dop/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "motions": [
                {
                        "motion": "360 Orbit",
                        "strength": 0
                }
        ],
        "options": "dop-turbo"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "motions": [
        {
            "motion": "360 Orbit",
            "strength": 0
        }
    ],
    "options": "dop-turbo"
}

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/higgsfield/dop/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)

Dop Image To Video API — Frequently asked questions

What is the Dop Image To Video API?

Dop Image To Video is a Higgsfield model for video generation from images, exposed as a REST API on WaveSpeedAI. DoP converts static images into dynamic 5-second Image-to-Video clips with AI motion synthesis for realistic motion effects. 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 Dop 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/higgsfield/higgsfield-dop-image-to-video.

How much does Dop Image To Video cost per run?

Dop Image To Video starts at $0.13 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 Dop Image To Video accept?

Key inputs: `prompt`, `image`, `end_image`, `motions`, `options`. 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/higgsfield/higgsfield-dop-image-to-video.

How long does Dop Image To Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 61 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 Dop Image To Video outputs commercially?

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

Dop Image to Video | Fast Image-to-Video API | WaveSpeedAI