Vidu Start End To Video 2.0

Playground

Vidu Start-End to Video 2.0 generates smooth transition videos interpolating between given start and end images for natural morphing effects. Ready-to-use REST API, best performance, no coldstarts, affordable pricing.

Features

Vidu Start-End-to-Video 2.0 — vidu/start-end-to-video-2.0

Vidu Start-End-to-Video 2.0 generates a short video that transitions from a start image to an end image, guided by a text prompt. You provide the first frame (image) and the final target frame (last_image), then describe the transformation story in the prompt. The model fills in the in-between motion and visual continuity, making it ideal for morphs, product reveals, character transformations, and “before → after” storytelling. You can control how dramatic the motion is with movement_amplitude.

Key capabilities

Start-to-end guided video generation (image → last_image)
Prompt-driven transformation with controllable motion intensity
Designed for smooth visual transitions and narrative continuity
Movement amplitude control: auto / small / medium / large
Seed control for reproducible variations

Use cases

Character transformation and morph sequences (human → creature, outfit swaps, style shifts)
Product reveals (closed box → unboxed product, sketch → final render)
Before/after transitions (room makeover, color grading shift, weather change)
Logo or brand animations (static mark → dynamic finish frame)
Short cinematic transitions for ads and social clips

Pricing

Output	Price per run
Start-End-to-Video (per generation)	$0.30

Inputs

prompt (required): describe the transition and what happens in-between
image (required): start image (first frame)
last_image (required): end image (final frame)

Parameters

movement_amplitude: motion intensity (auto, small, medium, large)
seed: random seed (-1 for random; fixed for reproducible results)

Prompting guide (start → end)

Write prompts that explain how the start becomes the end:

Describe the transformation mechanism (morphing, unfolding, dissolving, assembling)
Call out key beats (sparks, parts shifting, panels opening, smoke/energy)
Mention camera intent (fixed shot, slow push-in) if you need it
Keep continuity constraints clear (same framing, stable background, consistent lighting)

Template: Fixed camera. Start as [start]. The subject transforms by [mechanism] into [end]. Smooth transition, coherent motion, consistent lighting, no flicker.

Example prompts

A metal suit transforms into a sleek sports car through mechanical folding panels, glowing arc energy, parts assembling smoothly, fixed camera, cinematic lighting, seamless morph from start to end.
A sketch drawing gradually fills with color and detail, turning into a polished illustration, gentle dust particles, slow push-in, smooth transition.
A winter landscape melts into spring: snow dissolves, grass emerges, flowers bloom, warm sunlight grows stronger, smooth continuous motion.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/vidu/start-end-to-video-2.0" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "movement_amplitude": "auto",
    "seed": -1
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

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	-1 ~ 2147483647	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	Array of URLs to the generated content (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.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
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, the ID of the prediction to get
data.model	string	Model ID used for the prediction
data.outputs	string	Array of URLs to the generated content (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

Vidu Start End To Video Vidu Start End To Video Q1