Vidu Start End To Video

Vidu Start End To Video

Playground

Try it on WaveSpeedAI!

Vidu Start-End to Video converts a start and end image into a smooth transition Image-to-Video clip that morphs scenes seamlessly. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Vidu Start-End to Video generates smooth cinematic transitions between two specified images — turning a start and end frame into a 5-second, coherent video. Ideal for storyboarding, scene linking, and concept animation, it combines motion interpolation with prompt-guided realism for visually stunning results.


🌟 Why it stands out

  • 🎞️ Bi-Frame Guided Generation Creates natural motion between the start and end image while maintaining subject integrity.

  • ⚡ Temporal Coherence Ensures stable transitions with no flicker or frame artifacts.

  • 🧠 Context-Aware Motion Uses the text prompt to guide the transformation direction and emotional tone.

  • 🎬 Cinematic Realism Simulates real camera motion—zoom, pan, fade, or morph—matching your creative intent.


⚙️ Input Parameters

  • prompt — Describe the transition or narrative.

  • image — Upload the starting frame (JPEG/PNG).

  • last_image — Upload the ending frame (JPEG/PNG).

  • movement_amplitude — Controls the motion intensity within the transition:

  • auto – Automatically adjusts based on content.

  • small – Subtle, gentle motion for static or emotional scenes.

  • medium – Balanced camera and object movement.

  • large – Dynamic, cinematic transitions with stronger visual motion.


💰 Pricing

DurationCost per VideoResolution
5 seconds$0.20720p

🚀 How to Use

  1. 🖼️ Upload your start and end images.
  2. ✍️ Write a prompt describing the desired motion.
  3. 🎚️ Select movement_amplitude (auto, small, medium, or large).
  4. ▶️ Click Run ($0.20) to generate your transition.
  5. 💾 Preview and download your cinematic result.

💡 Pro Tips

  • Keep both input images aligned in composition and perspective for best transitions.
  • Use “medium” for natural storytelling and “large” for action or dramatic shifts.
  • Describe visual elements like lighting, direction, or camera movement for finer control.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "last_image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "movement_amplitude": "auto",
  "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/vidu/start-end-to-video" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagestringYes-The start image for generating the output.
last_imagestringYes--The end image for generating the output.
movement_amplitudestringNoautoauto, small, medium, largeThe movement amplitude of objects in the frame. Defaults to auto, accepted value: auto small medium large.
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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