vidu/q1/start-end-to-video

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.

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vidu/q1/start-end-to-video
Vidu Q1 Start-end-to-video
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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.

Invoer

Parameterconfiguratie laden...

Uitvoer

Inactief
Uw gegenereerde video's verschijnen hier
Configureer parameters en klik op Uitvoeren om te beginnen met genereren

Elke uitvoering kost $0.34. Voor $10 kunt u ongeveer 29 keer uitvoeren.

U kunt doorgaan met:

Parameters

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/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()

Installeren

Installeer het vereiste pakket voor uw programmeertaal.

bash
pip install requests

Authenticatie

Alle API-verzoeken vereisen authenticatie via een API-sleutel. U kunt uw API-sleutel ophalen via het Atlas Cloud dashboard.

bash
export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP-headers

python
import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}
Bescherm uw API-sleutel

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.

POST/api/v1/model/generateVideo

Verzoekinhoud

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']}")

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.

GET/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.

POST/api/v1/model/uploadMedia

Upload-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.

Totaal: 0Vereist: 0Optioneel: 0

Geen parameters beschikbaar.

Voorbeeld verzoekinhoud

json
{
  "model": "vidu/q1/start-end-to-video"
}

Uitvoer-Schema

De API retourneert een voorspellingsantwoord met de gegenereerde uitvoer-URL's.

idstringrequired
Unique identifier for the prediction.
statusstringrequired
Current status of the prediction.
processingcompletedsucceededfailed
modelstringrequired
The model used for generation.
outputsarray[string]
Array of output URLs. Available when status is "completed".
errorstring
Error message if status is "failed".
metricsobject
Performance metrics.
predict_timenumber
Time taken for video generation in seconds.
created_atstringrequired
ISO 8601 timestamp when the prediction was created.
Format: date-time
completed_atstring
ISO 8601 timestamp when the prediction was completed.
Format: date-time

Voorbeeldantwoord

json
{
  "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

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ ondersteunde clients

Installeren

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

API-sleutel instellen

Haal uw API-sleutel op via het Atlas Cloud dashboard en stel deze in als omgevingsvariabele.

bash
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.

BeeldgeneratieGenereer afbeeldingen met modellen zoals Nano Banana 2, Z-Image en meer.
VideocreatieMaak video's van tekst of afbeeldingen met Kling, Vidu, Veo, enz.
LLM-chatChat met Qwen, DeepSeek en andere grote taalmodellen.
Media uploadenUpload lokale bestanden voor beeldbewerking en afbeelding-naar-video workflows.

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

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ ondersteunde clients

Installeren

bash
npx -y atlascloud-mcp

Configuratie

Voeg de volgende configuratie toe aan het MCP-instellingenbestand van uw IDE.

json
{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Beschikbare tools

atlas_generate_imageGenereer afbeeldingen op basis van tekstprompts.
atlas_generate_videoMaak video's van tekst of afbeeldingen.
atlas_chatChat met grote taalmodellen.
atlas_list_modelsBlader door meer dan 300 beschikbare AI-modellen.
atlas_quick_generateContentcreatie in één stap met automatische modelselectie.
atlas_upload_mediaUpload lokale bestanden voor API-workflows.

API Schema

Schema niet beschikbaar

Inloggen om aanvraaggeschiedenis te bekijken

U moet ingelogd zijn om toegang te krijgen tot uw modelaanvraaggeschiedenis.

Inloggen

Vidu 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

ParameterRequiredDescription
promptYesText description of the transition, motion, and action between frames
start_imageYesThe first frame image (URL or upload)
end_imageYesThe last frame image (URL or upload)
resolutionNoOutput quality: 1080p
durationNoFixed video length of 5 seconds
generate_audioNoGenerate synchronized audio (default: enabled)
bgmNoAdd background music (default: enabled)
seedNoRandom seed for reproducibility

How to Use

  1. Upload your start image — provide the image representing the first frame of the video.
  2. Upload your end image — provide the image representing the last frame of the video.
  3. Write your prompt — describe the transition, motion, and how the scene evolves between frames.
  4. Configure audio (optional) — enable/disable audio generation and background music.
  5. Run — submit and download your video.

Pricing

ResolutionCost
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.

Begin met 300+ Modellen,

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