kwaivgi/kling-video-o3-std/image-to-video

Kling Omni Video O3 (Standard) Image-to-Video transforms static images into dynamic cinematic videos using MVL technology. Supports first/last frame control and audio generation.

IMAGE-TO-VIDEONEW
首頁
探索
Kling Video Models
Kling 3.0 Video Models
kwaivgi/kling-video-o3-std/image-to-video
Kling Video O3 Std Image-to-Video
圖生影片

Kling Omni Video O3 (Standard) Image-to-Video transforms static images into dynamic cinematic videos using MVL technology. Supports first/last frame control and audio generation.

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 0.071。$10 可執行約 140 次。

你可以繼續:

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": "kwaivgi/kling-video-o3-std/image-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": "kwaivgi/kling-video-o3-std/image-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": "kwaivgi/kling-video-o3-std/image-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

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

Kling Video O3 Std Image-to-Video

Kling Video O3 Standard is Kuaishou's cost-efficient image-to-video model in the O3 generation, balancing strong visual quality with affordable pricing. Upload a reference image and describe the scene — the model generates smooth, natural video with optional start-to-end frame guidance and synchronized sound. Supports flexible duration from 3 to 15 seconds.

Why Choose This?

O3 generation quality at Standard pricing High-quality motion and visuals from the latest O3 architecture at a fraction of Pro cost.

Flexible duration Generate videos from 3 to 15 seconds — any length you need.

Start-end frame guidance Optional end image for controlled transitions between two frames.

Sound generation Optional synchronized sound effects generated alongside the video.

Prompt Enhancer Built-in tool to automatically improve your motion descriptions for better results.

Parameters

ParameterRequiredDescription
promptYesText description of the desired motion and action
imageYesStart frame image to animate (URL or upload)
end_imageNoEnd frame image for guided transitions
durationNoVideo length: 3–15 seconds (default: 5)
soundNoGenerate synchronized sound (default: disabled)

How to Use

  1. Run — submit and download your video.
  2. Enable sound (optional) — generate synchronized audio with the video.
  3. Set duration — choose any length from 3 to 15 seconds.
  4. Upload end image (optional) — provide an end frame for guided transitions.
  5. Write your prompt — describe the motion, camera movement, and action.
  6. Upload your image — provide the reference image to animate.

Best Use Cases

  • E-commerce — Bring product images to life with motion and environmental audio.
  • Prototyping — Quickly test visual ideas before committing to Pro-tier production.
  • Scene Transitions — Use start and end frames for smooth cinematic transitions.
  • Social Media — Produce short-form animated content at scale without breaking the budget.
  • Content Creation — Animate product shots, portraits, or concept art into engaging video clips.

Pro Tips

  • Use high-quality source images for the best video output.
  • Use shorter durations (3–5 s) for rapid iteration, longer (10–15 s) for final output.
  • Enable sound for environmental audio like rain, city ambience, or mechanical effects.
  • Add an end_image for controlled transitions between two visual states.
  • Use detailed, cinematic prompts for best results — include lighting, camera angles, and motion descriptions.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Duration supports any value from 3 to 15 seconds.
  • Both prompt and image are required fields.
  • Kling Video O3 Pro Reference-to-Video — Create videos guided by reference images for consistent character and style.
  • Kling Video O3 Pro Video Edit — Edit existing videos with natural-language instructions.
  • Kling Video O3 Std Text-to-Video — Standard tier text-to-video generation.
  • Kling Video O3 Pro Image-to-Video — Maximum visual quality with O3 Pro tier.

300+ 模型,即刻開啟,

探索全部模型