vidu/q2-pro/image-to-video

Bild-zu-Video

PRO

Vidu Q2 Pro Image-to-Video API by Vidu

vidu/q2-pro/image-to-video

Image-to-video

Vidu Q2-Pro Image-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.

Modelle vergleichen

Vidu Q2 Pro Image-to-Video wurde von ShengShu Technology entwickelt. Atlas Cloud (betrieben von Atlas Cloud AI LLC) stellt lediglich den Zugang bereit und ist nicht Eigentümerin des Modells. Alle Marken sind Eigentum ihrer jeweiligen Inhaber.

Eingabe

Prompt *

Bild *

Sie können Dateien hier ablegen oder zum Hochladen klicken

MAX:1

Auflösung

Dauer

Movement amplitude

Seed

Audio Erzeugen

Bgm

Ausgabe

Inaktiv

Ihre generierten Videos erscheinen hier

Konfigurieren Sie Parameter und klicken Sie auf Ausführen, um mit der Generierung zu beginnen

Jede Ausführung kostet $0.034. Für $10 können Sie ca. 294 Mal ausführen.

Sie können fortfahren mit:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameter

Codebeispiel
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-pro/image-to-video",  # Required. model name
    "image": "example_value",  # Required. The URL of the image to generate an image from
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. The positive prompt for the generation
    "duration": 5,  # The duration of the generated media in seconds. (min: 1, max: 10)
    "resolution": "720p",  # The resolution of the generated media. options: 540p | 720p | 1080p
    "movement_amplitude": "auto",  # The movement amplitude of objects in the frame. options: auto | small | medium | large
    "generate_audio": True,  # Whether to generate audio for the video
    "bgm": False,  # Whether to add background music to the generated video
    "seed": 1,  # The random seed to use for the generation
}

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()

Installieren

Installieren Sie das erforderliche Paket für Ihre Programmiersprache.

pip install requests

Authentifizierung

Alle API-Anfragen erfordern eine Authentifizierung über einen API-Schlüssel. Sie können Ihren API-Schlüssel über das Atlas Cloud Dashboard erhalten.

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

HTTP-Header

import os

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

Schützen Sie Ihren API-Schlüssel

Geben Sie Ihren API-Schlüssel niemals in clientseitigem Code oder öffentlichen Repositories preis. Verwenden Sie stattdessen Umgebungsvariablen oder einen Backend-Proxy.

Anfrage senden

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())

Anfrage senden

Senden Sie eine asynchrone Generierungsanfrage. Die API gibt eine Vorhersage-ID zurück, mit der Sie den Status prüfen und das Ergebnis abrufen können.

POST/api/v1/model/generateVideo

Anfragekörper

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-pro/image-to-video",
    "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['data']['id']}")
print(f"Status: {result['data']['status']}")

Antwort

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Status prüfen

Fragen Sie den Vorhersage-Endpunkt ab, um den aktuellen Status Ihrer Anfrage zu überprüfen.

GET/api/v1/model/prediction/{prediction_id}

Abfrage-Beispiel

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)

Statuswerte

processingDie Anfrage wird noch verarbeitet.

completedDie Generierung ist abgeschlossen. Ergebnisse sind verfügbar.

succeededDie Generierung war erfolgreich. Ergebnisse sind verfügbar.

failedDie Generierung ist fehlgeschlagen. Überprüfen Sie das Fehlerfeld.

Abgeschlossene Antwort

{
  "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"
  }
}

Dateien hochladen

Laden Sie Dateien in den Atlas Cloud Speicher hoch und erhalten Sie eine URL, die Sie in Ihren API-Anfragen verwenden können. Verwenden Sie multipart/form-data zum Hochladen.

POST/api/v1/model/uploadMedia

Upload-Beispiel

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}")

Antwort

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Eingabe-Schema

Die folgenden Parameter werden im Anfragekörper akzeptiert.

Gesamt: 9Erforderlich: 3Optional: 6

modelstringrequired

model name

Default: "vidu/q2-pro/image-to-video"

imagestringrequired

The URL of the image to generate an image from.

promptstringrequired

The positive prompt for the generation. Max 5000 characters.

durationnumber

The duration of the generated media in seconds.

Default: 5Min: 1Max: 10

resolutionstring

The resolution of the generated media.

Default: "720p"

540p720p1080p

movement_amplitudestring

The movement amplitude of objects in the frame.

Default: "auto"

autosmallmediumlarge

generate_audioboolean

Whether to generate audio for the video.

Default: true

bgmboolean

Whether to add background music to the generated video.

Default: false

seedinteger

The random seed to use for the generation. -1 means a random seed will be used.

Beispiel-Anfragekörper

{
  "model": "vidu/q2-pro/image-to-video",
  "image": "example_image",
  "prompt": "A beautiful landscape",
  "duration": 5,
  "resolution": "720p",
  "movement_amplitude": "auto",
  "generate_audio": true,
  "bgm": false
}

Ausgabe-Schema

Die API gibt eine Vorhersage-Antwort mit den generierten Ausgabe-URLs zurück.

created_atstring

ISO timestamp of when the request was created.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content (empty when status is not completed).

statusstring

Status of the task: created, processing, completed, or failed.

Beispielantwort

{
  "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 integriert über 400 KI-Modelle direkt in Ihren KI-Programmierassistenten. Ein Befehl zur Installation, dann generieren Sie per natürlicher Sprache Bilder und Videos und chatten mit LLMs.

Unterstützte Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ unterstützte clients

Installieren

npx skills add AtlasCloudAI/atlas-cloud-skills

API-Schlüssel einrichten

Erhalten Sie Ihren API-Schlüssel über das Atlas Cloud Dashboard und setzen Sie ihn als Umgebungsvariable.

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

Funktionen

Nach der Installation können Sie natürliche Sprache in Ihrem KI-Assistenten verwenden, um auf alle Atlas Cloud Modelle zuzugreifen.

BildgenerierungGenerieren Sie Bilder mit Modellen wie Nano Banana 2, Z-Image und mehr.

VideoerstellungErstellen Sie Videos aus Text oder Bildern mit Kling, Vidu, Veo usw.

LLM-ChatChatten Sie mit Qwen, DeepSeek und anderen großen Sprachmodellen.

Medien-UploadLaden Sie lokale Dateien für Bildbearbeitung und Bild-zu-Video-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/atlas-cloud-skills

MCP-Server

Der Atlas Cloud MCP-Server verbindet Ihre IDE mit über 400 KI-Modellen über das Model Context Protocol. Funktioniert mit jedem MCP-kompatiblen Client.

Unterstützte Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ unterstützte clients

Installieren

npx -y atlascloud-mcp

Konfiguration

Fügen Sie die folgende Konfiguration zur MCP-Einstellungsdatei Ihrer IDE hinzu.

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

Verfügbare Werkzeuge

atlas_generate_imageGenerieren Sie Bilder aus Textbeschreibungen.

atlas_generate_videoErstellen Sie Videos aus Text oder Bildern.

atlas_chatChatten Sie mit großen Sprachmodellen.

atlas_list_modelsDurchsuchen Sie über 400 verfügbare KI-Modelle.

atlas_quick_generateInhaltserstellung in einem Schritt mit automatischer Modellauswahl.

atlas_upload_mediaLaden Sie lokale Dateien für API-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/mcp-server

API-Schema

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "vidu/q2-pro/image-to-video"
          },
          "image": {
            "description": "The URL of the image to generate an image from.",
            "type": "string"
          },
          "prompt": {
            "description": "The positive prompt for the generation. Max 5000 characters.",
            "type": "string"
          },
          "duration": {
            "default": 5,
            "description": "The duration of the generated media in seconds.",
            "maximum": 10,
            "minimum": 1,
            "step": 1,
            "type": "number",
            "x-ui-component": "slider"
          },
          "resolution": {
            "default": "720p",
            "description": "The resolution of the generated media.",
            "enum": [
              "540p",
              "720p",
              "1080p"
            ],
            "type": "string"
          },
          "movement_amplitude": {
            "default": "auto",
            "description": "The movement amplitude of objects in the frame.",
            "enum": [
              "auto",
              "small",
              "medium",
              "large"
            ],
            "type": "string"
          },
          "generate_audio": {
            "default": true,
            "description": "Whether to generate audio for the video.",
            "type": "boolean"
          },
          "bgm": {
            "default": false,
            "description": "Whether to add background music to the generated video.",
            "type": "boolean"
          },
          "seed": {
            "description": "The random seed to use for the generation. -1 means a random seed will be used.",
            "type": "integer"
          }
        },
        "required": [
          "model",
          "prompt",
          "image"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "image",
          "resolution",
          "duration",
          "movement_amplitude",
          "seed",
          "generate_audio",
          "bgm"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created.",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content (empty when status is not completed).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    },
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM-freundliche Prompt-Vorlage

# vidu/q2-pro/image-to-video

> Vidu Q2-Pro Image-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.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `vidu/q2-pro/image-to-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"vidu/q2-pro/image-to-video"`

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation. Max 5000 characters.

- **`image`** (`string`, _required_):
  The URL of the image to generate an image from.

- **`resolution`** (`string`, _optional_):
  The resolution of the generated media.
  - Default: `"720p"`
  - Options: "540p", "720p", "1080p"

- **`duration`** (`number`, _optional_):
  The duration of the generated media in seconds.
  - Default: `5`
  - Min: 1
  - Max: 10

- **`movement_amplitude`** (`string`, _optional_):
  The movement amplitude of objects in the frame.
  - Default: `"auto"`
  - Options: "auto", "small", "medium", "large"

- **`seed`** (`integer`, _optional_):
  The random seed to use for the generation. -1 means a random seed will be used.

- **`generate_audio`** (`boolean`, _optional_):
  Whether to generate audio for the video.
  - Default: `true`

- **`bgm`** (`boolean`, _optional_):
  Whether to add background music to the generated video.
  - Default: `false`



**Required Parameters Example**:

```json
{
  "model": "vidu/q2-pro/image-to-video",
  "prompt": "",
  "image": ""
}
```


**Full Example**:

```json
{
  "model": "vidu/q2-pro/image-to-video",
  "prompt": "",
  "image": "",
  "resolution": "720p",
  "duration": 5,
  "movement_amplitude": "auto",
  "seed": 0,
  "generate_audio": true,
  "bgm": false
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content (empty when status is not completed).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "vidu/q2-pro/image-to-video",
  "prompt": "",
  "image": "",
  "resolution": "720p",
  "duration": 5,
  "movement_amplitude": "auto",
  "seed": 0,
  "generate_audio": true,
  "bgm": false
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/vidu/q2-pro/image-to-video)

Endless desert sand dunes slowly flowing and reshaping under the wind, fine sand drifting across the ridges, warm sunlight casting long shadows, cinematic wide shot.

Wird geladen...

Vidu Q2-Pro Image-to-Video

Vidu Q2-Pro Image-to-Video is a professional-grade AI video generation model that brings static images to life. Upload a reference image, describe the motion, and the model generates high-quality video up to 1080p with smooth animation, rich detail, and optional audio — delivering cinematic results for demanding creative and commercial use cases.

Why Choose This?

Professional quality Rich detail, smooth motion, and cinematic output at up to 1080p.
Image-driven generation Transform any image into dynamic video with natural, expressive motion.
Flexible duration Create videos up to 10 seconds in length.
Audio generation Optional synchronized audio and background music.
Motion control Adjust movement amplitude for subtle or dynamic animations.
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
image	Yes	Reference image to animate (URL or upload)
resolution	No	Output quality: 540p, 720p (default), 1080p
duration	No	Video length in seconds (1-10, default: 5)
movement_amplitude	No	Motion intensity: auto (default), small, medium, large
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 image — provide the reference image to animate.
Write your prompt — describe the motion, camera movement, and action.
Set resolution — higher resolution for better quality, lower for faster processing.
Adjust duration — set video length up to 10 seconds.
Configure audio (optional) — enable/disable audio generation and background music.
Set motion intensity (optional) — control how dynamic the movement is.
Run — submit and download your video.

Pricing

Resolution	Cost
540p	Starts at $0.0400, +$ 0.0250/sec
720p	Starts at $0.0750, +$ 0.0500/sec
1080p	Starts at $0.2750, +$ 0.0750/sec

Best Use Cases

Photo Animation — Bring portraits, landscapes, and product images to life with cinematic quality.
Marketing & Ads — Generate high-quality promotional videos from product or brand photography.
Social Media Content — Create visually polished video content for professional channels.
Storytelling — Animate illustrations and artwork with rich, expressive motion.
Film Previs — Explore shot compositions and motion concepts from storyboard images.

Pro Tips

Use the Prompt Enhancer to refine your motion descriptions.
Be specific about movement direction, speed, camera angles, and framing.
Set movement_amplitude to "small" for subtle, cinematic motion or "large" for dramatic action.
Enable generate_audio for realistic sound effects matching the animated scene.
Use high-quality, well-composed source images for the best video output.
Describe environmental effects (wind, water, light shifts) for more immersive results.

Notes

Both prompt and image are required fields.
Maximum video duration is 10 seconds.
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.

Vidu Q2-Pro-Fast Image-to-Video — Pro quality image animation with faster generation speed.
Vidu Q2-Pro Reference-to-Video — Animate scenes using multiple reference images for visual consistency.
Vidu Q3-Pro Image-to-Video — The highest quality image-to-video generation available.

Vidu Q3-Mix Reference to Video

Vidu Q3-Mix Reference-to-Video generates videos from 1-4 reference images with consistent subjects. Offers strong visual quality with intelligent scene transitions, smooth dynamic effects, and audio support up to 1080p.

Vidu Q3 Reference to Video

Vidu Q3 Reference-to-Video generates videos from 1-4 reference images with consistent subjects. Features intelligent camera switching with better consistency across multiple camera positions, audio support, and resolutions up to 1080p.

Vidu Q3-Pro Start-end-to-video

Vidu Q3-Pro 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.

Vidu Q3-Turbo Image-to-video

Vidu Q3-Turbo Image-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.

Vidu Q3-Turbo Start-end-to-video

Vidu Q3-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.

Vidu Q3-Turbo Text-to-video

Vidu Q3-Turbo Text-to-Video is an advanced AI video generation model that creates high-quality videos directly from text descriptions. With support for multiple styles, resolutions up to 1080p, and optional audio generation, it delivers cinematic results with smooth motion and rich detail.

Vidu Q3-Pro Image-to-video

Vidu Q3-Pro Image-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.

Vidu Q3-Pro Text-to-video

Vidu Q3-Pro Text-to-Video is an advanced AI video generation model that creates high-quality videos directly from text descriptions. With support for multiple styles, resolutions up to 1080p, and optional audio generation, it delivers cinematic results with smooth motion and rich detail.

Vidu Reference-to-Video Q1

Open and Advanced Large-Scale Video Generative Models.

Vidu Reference-to-Video 2.0

Open and Advanced Large-Scale Video Generative Models.

Vidu Start-End-to-Video 2.0

Open and Advanced Large-Scale Video Generative Models.

Image-to-video-2.0

Open and Advanced Large-Scale Video Generative Models.

Vidu Q2-Turbo Start-end-to-video

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.

Vidu Q2-Pro Start-end-to-video

Vidu Q2-Pro 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.

Vidu Q2-Pro-Fast Start-end-to-video

Vidu Q2-Pro-Fast 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.

Vidu Q2 Reference-to-video

Vidu Q2 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.

From$0.075/SEK

$0.064/SEK

-15%

Eine API für alle Media-KI.

Alle Modelle erkunden

Vidu Q2 Pro Image-to-Video API by Vidu

Eingabe

Ausgabe

Parameter

Codebeispiel

Installieren

Authentifizierung

HTTP-Header

Anfrage senden

Anfrage senden

Anfragekörper

Antwort

Status prüfen

Abfrage-Beispiel

Statuswerte

Abgeschlossene Antwort

Dateien hochladen

Upload-Beispiel

Antwort

Eingabe-Schema

Beispiel-Anfragekörper

Ausgabe-Schema

Beispielantwort

Atlas Cloud Skills

Unterstützte Clients

Installieren

API-Schlüssel einrichten

Funktionen

MCP-Server

Unterstützte Clients

Installieren

Konfiguration

Verfügbare Werkzeuge

API-Schema

LLM-freundliche Prompt-Vorlage

Vidu Q2-Pro Image-to-Video

Why Choose This?

Parameters

How to Use

Pricing

Best Use Cases

Pro Tips

Notes

Related Models

Ähnliche Modelle Erkunden

Vidu Q3-Mix Reference to Video

Vidu Q3 Reference to Video

Vidu Q3-Pro Start-end-to-video

Vidu Q3-Turbo Image-to-video

Vidu Q3-Turbo Start-end-to-video

Vidu Q3-Turbo Text-to-video

Vidu Q3-Pro Image-to-video

Vidu Q3-Pro Text-to-video

Vidu Reference-to-Video Q1

Vidu Reference-to-Video 2.0

Vidu Start-End-to-Video 2.0

Image-to-video-2.0

Vidu Q2-Turbo Start-end-to-video

Vidu Q2-Pro Start-end-to-video

Vidu Q2-Pro-Fast Start-end-to-video

Vidu Q2 Reference-to-video

Eine API für alle Media-KI.

Eingabe

Ausgabe

Parameter

Codebeispiel

Installieren

Authentifizierung

HTTP-Header

Anfrage senden

Anfrage senden

Anfragekörper

Antwort

Status prüfen

Abfrage-Beispiel

Statuswerte

Abgeschlossene Antwort

Dateien hochladen

Upload-Beispiel

Antwort