Vidu Reference To Video Q1 API Documentation
Playground
Try it on WaveSpeedAI!Generate videos from reference images while keeping characters, objects, and scene identity consistent using Multi-Entity Consistency. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Vidu Reference-to-Video Q1 generates high-quality 5-second videos guided by multiple reference images. It combines advanced appearance preservation and motion synthesis, allowing creators to animate characters, products, or scenes while maintaining their original identity and style.
🌟 Key Features
🔁 Multi-Entity Consistency
- Preserves the visual identity, color tone, and texture of all reference subjects.
- Supports consistent appearance across dynamic motion sequences.
- Ideal for animating characters, fashion items, or branded products.
🧩 Flexible Input Options
- Accepts 1–7 reference images to define the subject, outfit, or style.
- Supports aspect ratios 16:9, 9:16, and 1:1.
- Adjustable movement amplitude (auto, small, medium, large) for customized motion intensity.
🎥 Cinematic Motion Generation
- Adds smooth camera motion and ambient scene transitions.
- Creates realistic parallax effects and subject movement.
- Works well with both portraits and product shots.
⚙️ Requirements
Images
- Count: 1–7 reference images
- Formats: PNG, JPEG, JPG
- Aspect ratio: Between 1:4 and 4:1
- Max file size: 50 MB per image
Prompt
- Max length: 1500 characters
- Describe desired motion, scene, or style.
> Example: “The girl in image 2 wears the glasses from image 1 and walks through a sunny street, soft natural light, cinematic color tone.”
💰 Price
| Duration | Resolution | Cost per job |
|---|---|---|
| 5 seconds | 720p | $0.40 |
💡 Best Practices
- Use clear, high-resolution reference images for optimal appearance consistency.
- Describe the desired motion and scene context in detail.
- Experiment with movement amplitude to adjust animation style.
- Include multiple reference images for complex scenes or multi-object compositions.
- Keep visual themes consistent (lighting, color palette, resolution).
⚠️ Effect Boundaries
- Works best with realistic, well-lit images.
- Overly stylized or low-quality inputs may cause flickering or distortion.
- Movement amplitude directly affects scene dynamics and smoothness.
- Complex multi-character prompts may require more references for stability.
📝 Notes
- Make sure each uploaded image is accessible and properly formatted.
- Check that the prompt and image order correspond correctly (e.g., “image 1,” “image 2”).
- If outputs look inconsistent, simplify the scene or reduce reference count.
- Simple, focused prompts yield the best alignment and motion results.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "16:9",
"movement_amplitude": "auto",
"seed": 0
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/vidu/reference-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
doneParameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| images | array<string> | Yes | - | 0 ~ 7 items | Reference images for video generation. Requirements: 1. Accept 1-3 images; 2. Images can be URLs or Base64 encoded; 3. Supported formats: PNG, JPEG, JPG, WebP; 4. Minimum size: 128*128 pixels; 5. Aspect ratio: less than 1:4 or 4:1; 6. Maximum size: 50MB per image. |
| aspect_ratio | string | No | 16:9 | 16:9, 9:16, 1:1 | The aspect ratio of the generated media. |
| 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 | 0 | - | The random seed to use for the generation. |
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 |