Vidu Q1 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.
输入
正在加载参数配置...
输出
空闲生成的视频将在这里显示
配置参数后点击运行开始生成
每次运行将花费 $0.34。$10 可运行约 29 次。
代码示例
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/q1/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()安装
安装所需的依赖包。
bash
pip install requests认证
所有 API 请求需要通过 API Key 进行认证。您可以在 Atlas Cloud 控制台获取 API Key。
bash
export ATLASCLOUD_API_KEY="your-api-key-here"HTTP 请求头
python
import os
API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {API_KEY}"
}保护好您的 API Key
切勿在客户端代码或公开仓库中暴露您的 API Key。请使用环境变量或后端代理。
提交请求
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())提交请求
提交一个异步生成请求。API 返回一个 prediction ID，您可以用它来检查状态和获取结果。
POST
/api/v1/model/generateVideo请求体
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/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']}")响应
{
"id": "pred_abc123",
"status": "processing",
"model": "model-name",
"created_at": "2025-01-01T00:00:00Z"
}检查状态
轮询 prediction 端点以检查请求的当前状态。
GET
/api/v1/model/prediction/{prediction_id}轮询示例
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)状态值
processing请求仍在处理中。completed生成完成，输出可用。succeeded生成成功，输出可用。failed生成失败，请检查 error 字段。完成响应
{
"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"
}
}上传文件
将文件上传到 Atlas Cloud 存储，获取可在 API 请求中使用的 URL。使用 multipart/form-data 上传。
POST
/api/v1/model/uploadMedia上传示例
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}")响应
{
"data": {
"download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
"file_name": "image.png",
"content_type": "image/png",
"size": 1024000
}
}Input Schema
以下参数在请求体中被接受。
总计: 0必填: 0可选: 0
暂无可用参数。
请求体示例
json
{
"model": "vidu/q1/reference-to-video"
}Output Schema
API 返回包含生成输出 URL 的 prediction 响应。
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.
completed_atstring
ISO 8601 timestamp when the prediction was completed.
响应示例
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 将 300+ AI 模型直接集成到您的 AI 编程助手中。一条命令安装，即可用自然语言生成图像、视频和与 LLM 对话。
支持的客户端
Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ 支持的客户端
安装
bash
npx skills add AtlasCloudAI/atlas-cloud-skills设置 API Key
从 Atlas Cloud 控制台获取 API Key，并将其设置为环境变量。
bash
export ATLASCLOUD_API_KEY="your-api-key-here"功能
安装后，您可以在 AI 助手中使用自然语言访问所有 Atlas Cloud 模型。
图像生成使用 Nano Banana 2、Z-Image 等模型生成图像。
视频创作使用 Kling、Vidu、Veo 等模型从文本或图像创建视频。
LLM 对话与 Qwen、DeepSeek 等大语言模型对话。
媒体上传上传本地文件用于图像编辑和图生视频工作流。
MCP Server
Atlas Cloud MCP Server 通过 Model Context Protocol 将您的 IDE 与 300+ AI 模型连接。支持任何兼容 MCP 的客户端。
支持的客户端
Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ 支持的客户端
安装
bash
npx -y atlascloud-mcp配置
将以下配置添加到您的 IDE 的 MCP 设置文件中。
json
{
"mcpServers": {
"atlascloud": {
"command": "npx",
"args": [
"-y",
"atlascloud-mcp"
],
"env": {
"ATLASCLOUD_API_KEY": "your-api-key-here"
}
}
}
}可用工具
atlas_generate_image从文本提示生成图像。
atlas_generate_video从文本或图像创建视频。
atlas_chat与大语言模型对话。
atlas_list_models浏览 300+ 可用 AI 模型。
atlas_quick_generate一步式内容创建，自动选择最佳模型。
atlas_upload_media上传本地文件用于 API 工作流。
API Schema
Schema 不可用Vidu Q1 Reference-to-Video
Vidu Q1 Reference-to-Video is an efficient AI video generation model that generates video featuring specific subjects. Provide subject images alongside a motion prompt, and the model generates a 5-second 1080p video that faithfully preserves each subject's appearance, style, and identity — fast and at an accessible price point.
Why Choose This?
-
Fast generation Optimized for quick turnaround with minimal wait time.
-
Subject-driven generation Feature specific characters or objects with consistent appearance across the generated video.
-
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 audio with configurable type: full audio, speech only, or sound effects only.
-
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 |
| subjects | Yes | One or more subject images to feature in the video (URL or upload) |
| resolution | No | Output quality: 1080p |
| duration | No | Fixed video length of 5 seconds |
| aspect_ratio | No | Aspect ratio of the output: 16:9 (default), 9:16, 1:1, 4:3, 3:4 |
| movement_amplitude | No | Motion intensity: auto (default), small, medium, large |
| generate_audio | No | Whether to generate audio for the video (default: true) |
| audio_type | No | Audio type when generate_audio is true: all (default), speech_only, sound_effect_only |
| seed | No | Seed for generation (default: 0); use -1 for a random seed |
How to Use
- Upload your subject images — provide one or more images of the subjects to feature in the video.
- Write your prompt — describe the motion, camera movement, and desired action.
- Configure audio (optional) — enable audio and select the audio type: all, speech_only, or sound_effect_only.
- Set motion intensity (optional) — adjust movement_amplitude for subtle or dynamic animations.
- Run — submit and download your video.
Pricing
| Resolution | Cost |
|---|---|
| 1080p | $0.4 |
Best Use Cases
- Character Consistency — Generate video featuring a specific character or subject across scenes.
- Product Videos — Animate product photos while preserving brand appearance.
- Style-Consistent Content — Produce video that matches the visual aesthetic of existing assets.
- Social Media Content — Create engaging animated clips based on your existing image library.
- Rapid Prototyping — Quickly explore reference-guided video concepts before committing to higher-quality generation.
Pro Tips
- Use the Prompt Enhancer to refine your motion descriptions.
- Provide clear, well-lit subject images for the most consistent visual output.
- Be specific about movement direction, speed, and camera angles in your prompt.
- Use multiple subject images when the scene involves more than one character or object.
- Set audio_type to speech_only when the scene involves dialogue, or sound_effect_only for purely ambient audio.
- Describe environmental elements (lighting, background) in the prompt to guide the scene composition.
Notes
- Both prompt and subjects are required fields.
- Video duration is fixed at 5 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.
Related Models
- Vidu Q1 Image-to-Video — Animate a single reference image with text-guided motion.
- Vidu Q2-Pro-Fast Reference-to-Video — Higher quality reference-to-video with adjustable duration and resolution.
