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
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🎞️ Bi-Frame Guided Generation Creates natural motion between the start and end image while maintaining subject integrity.
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⚡ Temporal Coherence Ensures stable transitions with no flicker or frame artifacts.
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🧠 Context-Aware Motion Uses the text prompt to guide the transformation direction and emotional tone.
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🎬 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
| Duration | Cost per Video | Resolution |
|---|---|---|
| 5 seconds | $0.20 | 720p |
🚀 How to Use
- 🖼️ Upload your start and end images.
- ✍️ Write a prompt describing the desired motion.
- 🎚️ Select movement_amplitude (
auto,small,medium, orlarge). - ▶️ Click Run ($0.20) to generate your transition.
- 💾 Preview and download your cinematic result.
💡 Pro Tips
- Keep both input images aligned in composition and perspective for best transitions.
- Use “medium” for natural storytelling and “large” for action or dramatic shifts.
- Describe visual elements like lighting, direction, or camera movement for finer control.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(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
doneParameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| image | string | Yes | - | The start image for generating the output. | |
| last_image | string | Yes | - | - | The end image for generating the output. |
| movement_amplitude | string | No | auto | auto, small, medium, large | The movement amplitude of objects in the frame. Defaults to auto, accepted value: auto small medium large. |
| seed | integer | No | -1 | - | The random seed to use for the generation. -1 means a random seed will be used. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<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.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |