vidu/q2-pro/reference-to-video

Vidu Q2-Pro 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.

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vidu/q2-pro/reference-to-video
Vidu Q2-Pro Reference-to-video
參考生影片
PRO

Vidu Q2-Pro 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.

輸入

正在載入參數設定...

輸出

閒置
生成的影片將在這裡顯示
設定參數後點擊執行開始生成

每次執行將花費 $0.085。$10 可執行約 117 次。

參數

程式碼範例

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/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()

安裝

為您的程式語言安裝所需的套件。

bash
pip install requests

驗證

所有 API 請求都需要透過 API 金鑰進行驗證。您可以從 Atlas Cloud 儀表板取得 API 金鑰。

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

HTTP 標頭

python
import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}
請妥善保管您的 API 金鑰

切勿在客戶端程式碼或公開儲存庫中暴露您的 API 金鑰。請改用環境變數或後端代理。

提交請求

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())

提交請求

提交非同步生成請求。API 會傳回一個預測 ID,您可以用它來檢查狀態並取得結果。

POST/api/v1/model/generateVideo

請求主體

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/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']}")

回應

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

檢查狀態

輪詢預測端點以檢查請求的當前狀態。

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

輪詢範例

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)

狀態值

processing請求仍在處理中。
completed生成完成。輸出已可取得。
succeeded生成成功。輸出已可取得。
failed生成失敗。請檢查錯誤欄位。

完成回應

{
  "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"
  }
}

上傳檔案

上傳檔案至 Atlas Cloud 儲存空間並取得 URL,可用於您的 API 請求。使用 multipart/form-data 上傳。

POST/api/v1/model/uploadMedia

上傳範例

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}")

回應

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

輸入 Schema

以下參數可在請求主體中使用。

總計: 0必填: 0選填: 0

無可用參數。

範例請求主體

json
{
  "model": "vidu/q2-pro/reference-to-video"
}

輸出 Schema

API 傳回包含生成輸出 URL 的預測回應。

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

範例回應

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 將 300 多個 AI 模型直接整合至您的 AI 程式碼助手。一鍵安裝,即可使用自然語言生成圖片、影片,以及與 LLM 對話。

支援的客戶端

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ 支援的客戶端

安裝

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

設定 API 金鑰

從 Atlas Cloud 儀表板取得 API 金鑰,並設為環境變數。

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

功能

安裝完成後,您可以在 AI 助手中使用自然語言存取所有 Atlas Cloud 模型。

圖片生成使用 Nano Banana 2、Z-Image 等模型生成圖片。
影片創作使用 Kling、Vidu、Veo 等從文字或圖片創建影片。
LLM 對話與 Qwen、DeepSeek 及其他大型語言模型對話。
媒體上傳上傳本機檔案,用於圖片編輯和圖片轉影片工作流程。

MCP Server

Atlas Cloud MCP Server 透過 Model Context Protocol 將您的 IDE 與 300 多個 AI 模型連接。支援任何 MCP 相容的客戶端。

支援的客戶端

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ 支援的客戶端

安裝

bash
npx -y atlascloud-mcp

設定

將以下設定新增至您 IDE 的 MCP 設定檔中。

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

可用工具

atlas_generate_image根據文字提示生成圖片。
atlas_generate_video從文字或圖片創建影片。
atlas_chat與大型語言模型對話。
atlas_list_models瀏覽 300 多個可用的 AI 模型。
atlas_quick_generate一步完成內容創建,自動選擇模型。
atlas_upload_media上傳本機檔案用於 API 工作流程。

API Schema

Schema 不可用

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Vidu Q2-Pro Reference-to-Video

Vidu Q2-Pro Reference-to-Video is a professional-grade AI video generation model that generates video featuring specific subjects with cinematic precision. Provide subject images alongside a motion prompt, and the model delivers up to 1080p video with rich detail, strict subject fidelity, and smooth natural motion — ideal for high-end creative, brand, and production workflows.

Why Choose This?

  • Professional quality Cinematic detail and smooth motion with faithful subject preservation at up to 1080p.

  • Subject-driven generation Feature specific characters or objects with strict visual fidelity throughout the video.

  • Flexible duration Create videos up to 10 seconds in length.

  • Audio generation Optional audio with configurable type: full audio, speech only, or sound effects only.

  • Motion control Adjust movement amplitude for subtle or dynamic animations.

  • Prompt Enhancer Built-in tool to automatically improve your motion descriptions.

Parameters

ParameterRequiredDescription
promptYesText description of the desired motion and action
subjectsYesOne or more subject images to feature in the video (URL or upload)
resolutionNoOutput quality: 540p, 720p (default), 1080p
durationNoVideo length in seconds (1-10, default: 5)
aspect_ratioNoAspect ratio of the output: 16:9 (default), 9:16, 1:1, 4:3, 3:4
movement_amplitudeNoMotion intensity: auto (default), small, medium, large
generate_audioNoWhether to generate audio for the video (default: true)
audio_typeNoAudio type when generate_audio is true: all (default), speech_only, sound_effect_only
seedNoSeed for generation (default: 0); use -1 for a random seed

How to Use

  1. Upload your subject images — provide one or more images of the subjects to feature in the video.
  2. Write your prompt — describe the motion, camera movement, and desired action.
  3. Set resolution — higher resolution for better quality, lower for faster processing.
  4. Adjust duration — set video length up to 10 seconds.
  5. Configure audio (optional) — enable audio and select the audio type: all, speech_only, or sound_effect_only.
  6. Set motion intensity (optional) — adjust movement_amplitude for subtle or dynamic animations.
  7. Run — submit and download your video.

Pricing

ResolutionCost
540pStarts at 0.1000,+0.1000, +0.0250/sec
720pStarts at 0.1500,+0.1500, +0.0250/sec
1080pStarts at 0.4250,+0.4250, +0.0500/sec

Best Use Cases

  • Character Consistency — Generate high-quality video featuring a specific character or subject with strict visual fidelity.
  • Brand & Product Videos — Produce professional-grade product animations while preserving brand identity.
  • Film & Narrative Production — Animate reference imagery for previs, concept reels, or final narrative content.
  • Style-Consistent Campaigns — Create multiple video assets that maintain a unified visual style across a campaign.
  • Premium Social Media Content — Publish cinematic, reference-guided video for high-visibility channels.

Pro Tips

  • Use the Prompt Enhancer to refine your motion descriptions.
  • Provide high-resolution, well-composed subject images for the strongest visual consistency.
  • Be specific about movement direction, speed, camera angles, and framing in your prompt.
  • Use multiple subject images to define different characters or scene elements independently.
  • Set movement_amplitude to "small" for precise, controlled motion or "large" for expressive action.
  • Set audio_type to speech_only when the scene involves dialogue, or sound_effect_only for purely ambient audio.
  • Describe lighting, atmosphere, and environmental effects in the prompt for richer scene quality.

Notes

  • Both prompt and subjects are required fields.
  • Maximum video duration is 10 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.

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