Vidu Q2-Turbo Start-end-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.
Invoer
Uitvoer
InactiefElke uitvoering kost $0.026. Voor $10 kunt u ongeveer 384 keer uitvoeren.
U kunt doorgaan met:
Codevoorbeeld
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/q2-turbo/start-end-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()Installeren
Installeer het vereiste pakket voor uw programmeertaal.
pip install requestsAuthenticatie
Alle API-verzoeken vereisen authenticatie via een API-sleutel. U kunt uw API-sleutel ophalen via het 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}"
}Stel uw API-sleutel nooit bloot in client-side code of openbare repositories. Gebruik in plaats daarvan omgevingsvariabelen of een backend-proxy.
Een verzoek indienen
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())Een verzoek indienen
Dien een asynchroon generatieverzoek in. De API retourneert een voorspellings-ID waarmee u de status kunt controleren en het resultaat kunt ophalen.
/api/v1/model/generateVideoVerzoekinhoud
import requests
url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
"model": "vidu/q2-turbo/start-end-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']}")Antwoord
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Status controleren
Bevraag het voorspellings-eindpunt om de huidige status van uw verzoek te controleren.
/api/v1/model/prediction/{prediction_id}Polling-voorbeeld
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)Statuswaarden
processingHet verzoek wordt nog verwerkt.completedDe generatie is voltooid. Resultaten zijn beschikbaar.succeededDe generatie is geslaagd. Resultaten zijn beschikbaar.failedDe generatie is mislukt. Controleer het foutveld.Voltooid antwoord
{
"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"
}
}Bestanden uploaden
Upload bestanden naar Atlas Cloud opslag en ontvang een URL die u kunt gebruiken in uw API-verzoeken. Gebruik multipart/form-data om te uploaden.
/api/v1/model/uploadMediaUpload-voorbeeld
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}")Antwoord
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Invoer-Schema
De volgende parameters worden geaccepteerd in de verzoekinhoud.
Geen parameters beschikbaar.
Voorbeeld verzoekinhoud
{
"model": "vidu/q2-turbo/start-end-to-video"
}Uitvoer-Schema
De API retourneert een voorspellingsantwoord met de gegenereerde uitvoer-URL's.
Voorbeeldantwoord
{
"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 integreert meer dan 300 AI-modellen rechtstreeks in uw AI-codeerassistent. Eén commando om te installeren, gebruik daarna natuurlijke taal om afbeeldingen, video's te genereren en te chatten met LLMs.
Ondersteunde clients
Installeren
npx skills add AtlasCloudAI/atlas-cloud-skillsAPI-sleutel instellen
Haal uw API-sleutel op via het Atlas Cloud dashboard en stel deze in als omgevingsvariabele.
export ATLASCLOUD_API_KEY="your-api-key-here"Mogelijkheden
Eenmaal geïnstalleerd kunt u natuurlijke taal gebruiken in uw AI-assistent om toegang te krijgen tot alle Atlas Cloud modellen.
MCP-server
De Atlas Cloud MCP-server verbindt uw IDE met meer dan 300 AI-modellen via het Model Context Protocol. Werkt met elke MCP-compatibele client.
Ondersteunde clients
Installeren
npx -y atlascloud-mcpConfiguratie
Voeg de volgende configuratie toe aan het MCP-instellingenbestand van uw IDE.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Beschikbare tools
API Schema
Schema niet beschikbaarInloggen om aanvraaggeschiedenis te bekijken
U moet ingelogd zijn om toegang te krijgen tot uw modelaanvraaggeschiedenis.
InloggenVidu Q2-Turbo Start-End-to-Video
Vidu Q2-Turbo Start-End-to-Video is the fastest start-end-to-video model in the Q2 family. Provide a start frame and an end frame, and the model generates a smooth video transition between them at ultra-low latency — built for high-volume pipelines, real-time previews, and cost-sensitive workflows where speed takes priority.
Why Choose This?
-
Ultra-fast generation The fastest start-end-to-video option in the Q2 lineup, optimized for throughput.
-
Precise frame control Define exactly where the video begins and ends with two reference images.
-
Affordable pricing The most cost-effective start-end-to-video option in the Q2 family.
-
High resolution output Generate videos in 540p, 720p, or 1080p quality.
-
Flexible duration Create videos from 1 to 10 seconds in length.
-
Audio generation Optional synchronized audio and background music.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the transition, motion, and action between frames |
| start_image | Yes | The first frame image (URL or upload) |
| end_image | Yes | The last frame image (URL or upload) |
| resolution | No | Output quality: 540p, 720p (default), 1080p |
| duration | No | Video length in seconds (1-10, default: 5) |
| generate_audio | No | Generate synchronized audio (default: enabled) |
| bgm | No | Add background music (default: enabled) |
| seed | No | Random seed for reproducibility |
How to Use
- Upload your start image — provide the image representing the first frame of the video.
- Upload your end image — provide the image representing the last frame of the video.
- Write your prompt — describe the transition, motion, and how the scene evolves between frames.
- Set resolution — choose based on your speed and quality requirements.
- Adjust duration — set video length up to 10 seconds.
- Configure audio (optional) — enable/disable audio generation and background music.
- Run — submit and download your video.
Pricing
| Resolution | Cost |
|---|---|
| 540p | Starts at 0.0100/sec |
| 720p | Starts at 0.0500/sec |
| 1080p | Starts at 0.0500/sec |
Best Use Cases
- High-Volume Pipelines — Process large batches of frame-to-frame transitions quickly and affordably.
- Real-Time Previews — Generate fast transition previews before committing to higher-quality renders.
- Rapid Prototyping — Explore start-to-end motion concepts with near-instant turnaround.
- Cost-Sensitive Projects — Deliver transition video content within tight budget constraints.
- Developer Testing — Integrate start-end video generation into applications with minimal latency.
Pro Tips
- Use concise, action-focused prompts — the Turbo pipeline responds well to clear, direct transition instructions.
- Ensure start and end images share a compatible composition for the most natural transition output.
- Use 540p for rapid iteration and upgrade to 720p or 1080p for final deliverables.
- Keep subject framing consistent between start and end images for smoother interpolation.
- Enable generate_audio to add energy and context to the transition without extra effort.
- Use seed to lock in a result you like while experimenting with different prompt variations.
Notes
- All three fields — prompt, start_image, and end_image — are required.
- Maximum video duration is 10 seconds.
- The model interpolates motion and scene content between the two provided frames.
- Audio generation adds synchronized sound effects and ambient audio.
- BGM adds background music appropriate to the scene mood.
- Ensure uploaded image URLs are publicly accessible.
Related Models
- Vidu Q2-Turbo Image-to-Video — Ultra-fast video animation from a single reference image.
- Vidu Q2-Pro-Fast Start-End-to-Video — Faster Pro-quality transitions with 1080p support.
- Vidu Q2-Pro Start-End-to-Video — Maximum quality transitions with extended duration and full resolution range.
