bytedance/seedance-v1-pro-i2v-1080p

Seedance Pro’s image-to-video mode transforms still visuals into cinematic motion, maintaining visual consistency and expressive animation across frames.

IMAGE-TO-VIDEONEW
Seedance v1 Pro i2v 1080p
圖生影片
PRO

Seedance Pro’s image-to-video mode transforms still visuals into cinematic motion, maintaining visual consistency and expressive animation across frames.

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 $0.108。$10 可執行約 92 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": "bytedance/seedance-v1-pro-i2v-1080p",
    "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": "bytedance/seedance-v1-pro-i2v-1080p",
    "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": "bytedance/seedance-v1-pro-i2v-1080p"
}

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

請登入以檢視請求歷史

您需要登入才能存取模型請求歷史記錄。

登入

ByteDance Seedance Pro I2V 1080p

ByteDance Seedance Pro I2V 1080p is a revolutionary AI image-to-video generation model developed by ByteDance, now exclusively available on WaveSpeedAI as a global premiere launch. This cutting-edge model transforms static images into dynamic 5-second videos at 1080p resolution with lightning-fast processing speed, offering high-quality visual outputs with enhanced motion and semantic understanding. Part of the Dreamina model family, this SOTA-level model delivers unprecedented performance in image-to-video synthesis.

Key Features

  • Ultra-Fast Video Generation: Lightning-speed processing creates 5-second videos at 1080p resolution with vivid details and smooth motion in seconds, not minutes.
  • SOTA Motion Rendering: State-of-the-art dynamic rendering techniques create natural and realistic movements that bring images to life.
  • Advanced Semantic Understanding: Industry-leading AI excels in interpreting complex user prompts to generate coherent and dynamic scenes with professional quality.
  • Realistic Physical Simulation: SOTA physics engine simulates realistic physical properties and movements for lifelike video generation.
  • Blazing-Fast Processing: Optimized for maximum speed efficiency, allowing instant creation of high-quality videos for real-time workflows.
  • Flexible Parameter Control: Customizable settings offer duration and style adjustments for complete creative control.
  • Professional Quality Output: SOTA image-to-video technology ensures broadcast-ready results with smooth temporal consistency.
  • Instant Creative Enhancement: Transform ordinary photos into engaging, dynamic content perfect for social media marketing in seconds.

Global Premiere

  • Exclusive Launch: WaveSpeedAI is the first platform globally to offer ByteDance's latest I2V technology from the Dreamina series.
  • Cutting-Edge Access: Be among the first worldwide to experience SOTA image-to-video generation capabilities.
  • Premium Integration: Seamless API access to ByteDance's most advanced video synthesis technology.
  • Pioneer Advantage: Early access to breakthrough AI technology before wider market availability.

Technical Excellence & Speed Optimization

  • SOTA Architecture: Built on breakthrough research delivering state-of-the-art image-to-video generation performance.
  • Optimized Processing: Native ByteDance technology delivers superior generation speed compared to standard I2V solutions.
  • Real-Time Processing: Ultra-fast video synthesis enables immediate creative workflows and instant content creation.
  • High-Performance Computing: Enterprise-grade infrastructure supports rapid, high-volume video generation at scale.

Perfect for Fast-Paced Creative Work

  • Content Creators: Instantly transform static photography into engaging video content for social platforms with lightning-fast speed.
  • Marketing Professionals: Create dynamic promotional materials from product images in seconds, not hours.
  • Social Media Managers: Convert photos into shareable, dynamic content that captures attention with lightning-fast turnaround.
  • E-commerce Teams: Bring product photos to life with subtle motion effects using SOTA I2V technology.
  • Digital Agencies: Deliver client projects faster with instant video generation capabilities from the Dreamina model family.

Performance & Speed Advantages

  • Instant Results: Generate professional videos in seconds with SOTA processing speed.
  • Real-Time Workflow: Advanced AI enables immediate creative iteration and rapid content production.
  • Scalable Speed: Handle multiple image-to-video conversions simultaneously without performance degradation.
  • Optimized Efficiency: Advanced algorithms maximize speed while maintaining SOTA quality standards.

Limitations

  • Creative Focus: Designed primarily for creative video synthesis; not intended for generating factually accurate content.
  • Inherent Biases: Outputs may reflect biases present in the training data, typical of current SOTA models.
  • Input Sensitivity: The quality and consistency of generated videos depend significantly on the quality of the input image; subtle variations may lead to output variability.
  • Resolution Limitation: This model is optimized for 480p video generation and does not support higher resolutions.
  • Speed vs Quality Trade-off: While optimized for speed, extremely complex scenes may require additional processing time.

Out-of-Scope Use

The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:

  • Exploiting, harming, or attempting to exploit or harm minors, including solicitation, creation, acquisition, or dissemination of child exploitative content.
  • Generating or disseminating verifiably false information with the intent to harm others.
  • Creating or distributing personal identifiable information that could be used to harm an individual.
  • Harassing, abusing, threatening, stalking, or bullying individuals or groups.
  • Producing non-consensual nudity or illegal pornographic content.
  • Making fully automated decisions that adversely affect an individual's legal rights or create binding obligations.
  • Facilitating large-scale disinformation campaigns.

300+ 模型,即刻開啟,

探索全部模型