Vidu Start End To Video Q1

Vidu Start End To Video Q1

Playground

Try it on WaveSpeedAI!

Vidu Q1 Start-End To Video turns specified start and end images into smooth image-to-video transitions for morphs and scene fades. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Vidu Q1 Start-End to Video generates smooth, coherent motion sequences between a specified start frame and end frame, transforming static images into cinematic 5-second transitions. Built on the Vidu Q-series architecture, it delivers high-quality motion interpolation, making it ideal for professional storytelling, editing, and scene development.


Key Features

  • Bi-frame Guided Synthesis Generates realistic motion by interpreting both start and end frames, ensuring a seamless visual flow.

  • Strong Narrative Continuity Preserves scene logic and emotional tone across frames, maintaining coherent storytelling through motion.

  • Object- and Human-Aware Motion Handles complex transitions involving people, objects, and environments with spatial consistency and natural dynamics.

  • Adaptive Camera Behavior Simulates camera pans, zooms, or layout changes to achieve cinematic motion depth.

  • High-Fidelity Quality (720p) Provides production-ready visuals with accurate textures, lighting, and temporal consistency.


Use Cases

  • Storyboarding and concept animation
  • Scene interpolation for long-form content or cinematic projects
  • Instructional or educational visual transitions
  • Film previsualization and creative prototyping

Pricing

ResolutionDurationCost per Clip
720p5s$0.40

How to Use

  1. Upload your start frame and end frame (JPEG/PNG).
  2. Optionally include a prompt describing the desired motion or transition style.
  3. Adjust movement_amplitude (auto, small, medium, large).
  4. Click Run to generate your cinematic transition video and download it.

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-q1" \
  -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
© 2026 WaveSpeedAI. All rights reserved.