Vidu Q1 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.
Inmatning
Utmatning
VilandeVarje körning kostar $0.34. För $10 kan du köra cirka 29 gånger.
Du kan fortsätta med:
Kodexempel
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/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()Installera
Installera det nödvändiga paketet för ditt programmeringsspråk.
pip install requestsAutentisering
Alla API-förfrågningar kräver autentisering via en API key. Du kan hämta din API key från Atlas Cloud-instrumentpanelen.
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}"
}Exponera aldrig din API key i klientkod eller publika arkiv. Använd miljövariabler eller en backend-proxy istället.
Skicka en förfrågan
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())Skicka en förfrågan
Skicka en asynkron genereringsförfrågan. API:et returnerar ett prediction ID som du kan använda för att kontrollera statusen och hämta resultatet.
/api/v1/model/generateVideoFörfrågningsinnehåll
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/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']}")Svar
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}Kontrollera status
Polla prediction-endpointen för att kontrollera den aktuella statusen för din förfrågan.
/api/v1/model/prediction/{prediction_id}Polling-exempel
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)Statusvärden
processingFörfrågan bearbetas fortfarande.completedGenereringen är klar. Utdata är tillgängliga.succeededGenereringen lyckades. Utdata är tillgängliga.failedGenereringen misslyckades. Kontrollera error-fältet.Slutfört svar
{
"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"
}
}Ladda upp filer
Ladda upp filer till Atlas Cloud-lagring och få en URL som du kan använda i dina API-förfrågningar. Använd multipart/form-data för uppladdning.
/api/v1/model/uploadMediaUppladdningsexempel
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}")Svar
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Input Schema
Följande parametrar accepteras i förfrågningsinnehållet.
Inga parametrar tillgängliga.
Exempel på förfrågningsinnehåll
{
"model": "vidu/q1/start-end-to-video"
}Output Schema
API:et returnerar ett prediction-svar med de genererade utdata-URL:erna.
Exempelsvar
{
"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 integrerar 300+ AI-modeller direkt i din AI-kodassistent. Ett kommando för att installera, sedan använd naturligt språk för att generera bilder, videor och chatta med LLM.
Stödda klienter
Installera
npx skills add AtlasCloudAI/atlas-cloud-skillsKonfigurera API Key
Hämta din API key från Atlas Cloud-instrumentpanelen och ställ in den som en miljövariabel.
export ATLASCLOUD_API_KEY="your-api-key-here"Funktioner
När det är installerat kan du använda naturligt språk i din AI-assistent för att komma åt alla Atlas Cloud-modeller.
MCP Server
Atlas Cloud MCP Server ansluter din IDE med 300+ AI-modeller via Model Context Protocol. Fungerar med alla MCP-kompatibla klienter.
Stödda klienter
Installera
npx -y atlascloud-mcpKonfiguration
Lägg till följande konfiguration i din IDE:s MCP-inställningsfil.
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}Tillgängliga verktyg
API Schema
Schema ej tillgängligtLogga in för att visa förfrågningshistorik
Du måste vara inloggad för att få tillgång till din modellförfrågningshistorik.
Logga InVidu Q1 Start-End-to-Video
Vidu Q1 Start-End-to-Video is an efficient AI video generation model that creates smooth video transitions between two images. Provide a start frame and an end frame — the model generates a natural, coherent 5-second 1080p video that bridges the two visuals with fluid motion and optional audio.
Why Choose This?
-
Frame-to-frame control Define exactly where the video begins and ends with two reference images.
-
Smooth transitions Generate natural, coherent motion that seamlessly connects the start and end frames.
-
Fast generation Optimized for quick turnaround with minimal wait time.
-
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 synchronized audio and background music.
-
Prompt Enhancer Built-in tool to automatically improve your transition descriptions.
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: 1080p |
| duration | No | Fixed video length of 5 seconds |
| 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.
- Configure audio (optional) — enable/disable audio generation and background music.
- Run — submit and download your video.
Pricing
| Resolution | Cost |
|---|---|
| 1080p | $0.4 |
Best Use Cases
- Before & After Videos — Showcase transformations such as renovations, makeovers, or seasonal changes.
- Scene Transitions — Create smooth visual transitions between two scenes for film or storytelling.
- Product Reveals — Animate the transformation from a product packshot to a lifestyle shot.
- Visual Morphing — Generate morphing effects between two related subjects or compositions.
- Social Media Content — Produce eye-catching transition clips for Reels, TikTok, and Stories.
Pro Tips
- Use the Prompt Enhancer to refine your transition descriptions.
- Ensure start and end images share a compatible composition or subject for the most natural transition.
- Be specific in your prompt about how the motion or transformation should unfold between the two frames.
- Keep subject framing consistent between start and end images for smoother results.
- Enable generate_audio for synchronized sound effects that complement the transition.
Notes
- All three fields — prompt, start_image, and end_image — are required.
- Video duration is fixed at 5 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 Q1 Image-to-Video — Animate a single reference image with text-guided motion.
- Vidu Q1 Reference-to-Video — Generate video using one or more reference images as visual anchors.
