Vidu Q1 Reference-to-Video is an advanced AI video generation model that brings static images to life. Upload a reference image and describe the motion you want — the model generates high-quality video with smooth animation, optional audio, and cinematic quality up to 1080p.
INPUT
OUTPUT
IdleYour request will cost $0.34 per run. For $10 you can run this model approximately 29 times.
Here's what you can do next:
Code Example
import requests
import time
# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "vidu/q1/reference-to-video",
"prompt": "A beautiful sunset over the ocean with gentle waves",
"width": 512,
"height": 512,
"duration": 3,
"fps": 24,
}
generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]
# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
def check_status():
while True:
response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
result = response.json()
if result["data"]["status"] in ["completed", "succeeded"]:
print("Generated video:", result["data"]["outputs"][0])
return result["data"]["outputs"][0]
elif result["data"]["status"] == "failed":
raise Exception(result["data"]["error"] or "Generation failed")
else:
# Still processing, wait 2 seconds
time.sleep(2)
video_url = check_status()Install
Install the required package for your language.
pip install requestsAuthentication
All API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.
export ATLASCLOUD_API_KEY="your-api-key-here"HTTP Headers
import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.
Submit a request
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "your-model",
"prompt": "A beautiful landscape"
}
response = requests.post(url, headers=headers, json=data)
print(response.json())Submit a Request
Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.
/api/v1/model/generateVideoRequest Body
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "vidu/q1/reference-to-video",
"input": {
"prompt": "A beautiful sunset over the ocean with gentle waves"
}
}
response = requests.post(url, headers=headers, json=data)
result = response.json()
print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")Response
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Check Status
Poll the prediction endpoint to check the current status of your request.
/api/v1/model/prediction/{prediction_id}Polling Example
import requests
import time
prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
while True:
response = requests.get(url, headers=headers)
result = response.json()
status = result["data"]["status"]
print(f"Status: {status}")
if status in ["completed", "succeeded"]:
output_url = result["data"]["outputs"][0]
print(f"Output URL: {output_url}")
break
elif status == "failed":
print(f"Error: {result['data'].get('error', 'Unknown')}")
break
time.sleep(3)Status Values
processingThe request is still being processed.completedGeneration is complete. Outputs are available.succeededGeneration succeeded. Outputs are available.failedGeneration failed. Check the error field.Completed Response
{
"data": {
"id": "pred_abc123",
"status": "completed",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.mp4"
],
"metrics": {
"predict_time": 45.2
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}
}Upload Files
Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.
/api/v1/model/uploadMediaUpload Example
import requests
url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }
with open("image.png", "rb") as f:
files = {"file": ("image.png", f, "image/png")}
response = requests.post(url, headers=headers, files=files)
result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")Response
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Input Schema
The following parameters are accepted in the request body.
No parameters available.
Example Request Body
{
"model": "vidu/q1/reference-to-video"
}Output Schema
The API returns a prediction response with the generated output URLs.
Example Response
{
"id": "pred_abc123",
"status": "completed",
"model": "model-name",
"outputs": [
"https://storage.atlascloud.ai/outputs/result.mp4"
],
"metrics": {
"predict_time": 45.2
},
"created_at": "2025-01-01T00:00:00Z",
"completed_at": "2025-01-01T00:00:10Z"
}Atlas Cloud Skills
Atlas Cloud Skills integrates 300+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.
Supported Clients
Install
npx skills add AtlasCloudAI/atlas-cloud-skillsSetup API Key
Get your API key from the Atlas Cloud dashboard and set it as an environment variable.
export ATLASCLOUD_API_KEY="your-api-key-here"Capabilities
Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.
MCP Server
Atlas Cloud MCP Server connects your IDE with 300+ AI models via the Model Context Protocol. Works with any MCP-compatible client.
Supported Clients
Install
npx -y atlascloud-mcpConfiguration
Add the following configuration to your IDE's MCP settings file.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Available Tools
API Schema
Schema not availablePlease log in to view request history
You need to be logged in to access your model request history.
Log InVidu Q1 Reference-to-Video
Vidu Q1 Reference-to-Video is an efficient AI video generation model that generates video featuring specific subjects. Provide subject images alongside a motion prompt, and the model generates a 5-second 1080p video that faithfully preserves each subject's appearance, style, and identity — fast and at an accessible price point.
Why Choose This?
-
Fast generation Optimized for quick turnaround with minimal wait time.
-
Subject-driven generation Feature specific characters or objects with consistent appearance across the generated video.
-
1080p output Generate videos in full 1080p high definition quality.
-
5-second videos Produces crisp, fixed-length 5-second videos ready to share.
-
Audio generation Optional audio with configurable type: full audio, speech only, or sound effects only.
-
Prompt Enhancer Built-in tool to automatically improve your motion descriptions.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the desired motion and action |
| subjects | Yes | One or more subject images to feature in the video (URL or upload) |
| resolution | No | Output quality: 1080p |
| duration | No | Fixed video length of 5 seconds |
| aspect_ratio | No | Aspect ratio of the output: 16:9 (default), 9:16, 1:1, 4:3, 3:4 |
| movement_amplitude | No | Motion intensity: auto (default), small, medium, large |
| generate_audio | No | Whether to generate audio for the video (default: true) |
| audio_type | No | Audio type when generate_audio is true: all (default), speech_only, sound_effect_only |
| seed | No | Seed for generation (default: 0); use -1 for a random seed |
How to Use
- Upload your subject images — provide one or more images of the subjects to feature in the video.
- Write your prompt — describe the motion, camera movement, and desired action.
- Configure audio (optional) — enable audio and select the audio type: all, speech_only, or sound_effect_only.
- Set motion intensity (optional) — adjust movement_amplitude for subtle or dynamic animations.
- Run — submit and download your video.
Pricing
| Resolution | Cost |
|---|---|
| 1080p | $0.4 |
Best Use Cases
- Character Consistency — Generate video featuring a specific character or subject across scenes.
- Product Videos — Animate product photos while preserving brand appearance.
- Style-Consistent Content — Produce video that matches the visual aesthetic of existing assets.
- Social Media Content — Create engaging animated clips based on your existing image library.
- Rapid Prototyping — Quickly explore reference-guided video concepts before committing to higher-quality generation.
Pro Tips
- Use the Prompt Enhancer to refine your motion descriptions.
- Provide clear, well-lit subject images for the most consistent visual output.
- Be specific about movement direction, speed, and camera angles in your prompt.
- Use multiple subject images when the scene involves more than one character or object.
- Set audio_type to speech_only when the scene involves dialogue, or sound_effect_only for purely ambient audio.
- Describe environmental elements (lighting, background) in the prompt to guide the scene composition.
Notes
- Both prompt and subjects are required fields.
- Video duration is fixed at 5 seconds.
- When generate_audio is true, audio_type controls what is generated: all includes speech and sound effects, speech_only generates voice audio, sound_effect_only generates ambient and environmental sounds.
- Ensure uploaded subject image URLs are publicly accessible.
Related Models
- Vidu Q1 Image-to-Video — Animate a single reference image with text-guided motion.
- Vidu Q2-Pro-Fast Reference-to-Video — Higher quality reference-to-video with adjustable duration and resolution.
