alibaba/wan-2.5/image-edit

圖生圖

Wan 2.5 Image Edit API by Alibaba

alibaba/wan-2.5/image-edit

Image-edit

Open and Advanced Large-Scale Image Generative Models.

輸入

正在載入參數設定...

輸出

閒置

生成的圖片將在這裡顯示

設定參數後點擊執行開始生成

每次執行將花費 $0.021。$10 可執行約 476 次。

你可以繼續：

圖生影片圖生圖

參數

程式碼範例
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/wan-2.5/image-edit",
    "prompt": "A beautiful landscape with mountains and lake",
    "width": 512,
    "height": 512,
    "steps": 20,
    "guidance_scale": 7.5,
}

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"] == "completed":
            print("Generated image:", 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)

image_url = check_status()

安裝

安裝所需的相依套件。

pip install requests

驗證

所有 API 請求都需要透過 API Key 進行認證。您可以在 Atlas Cloud 控制台取得 API Key。

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

HTTP 標頭

import os

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

保護好您的 API Key

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

提交請求

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
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

提交一個非同步生成請求。API 會傳回一個 prediction ID，您可以用它來檢查狀態與取得結果。

POST/api/v1/model/generateImage

請求主體

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "alibaba/wan-2.5/image-edit",
    "prompt": "A beautiful landscape with mountains and lake"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

回應

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

檢查狀態

輪詢 prediction 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，輸出可用。

succeeded生成成功，輸出可用。

failed生成失敗，請檢查 error 欄位。

完成回應

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

上傳檔案

將檔案上傳到 Atlas Cloud 儲存空間，取得可在 API 請求中使用的 URL。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
  }
}

Input Schema

以下參數在請求主體中被接受。

總計: 0必填: 0選填: 0

暫無可用參數。

範例請求主體

{
  "model": "alibaba/wan-2.5/image-edit"
}

Output Schema

API 傳回包含生成輸出 URL 的 prediction 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 image 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

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills 將 300+ AI 模型直接整合到您的 AI 程式碼助手中。一條命令安裝，即可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

npx skills add AtlasCloudAI/atlas-cloud-skills

設定 API Key

從 Atlas Cloud 控制台取得 API Key，並將其設定為環境變數。

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生影片工作流程。

MCP Server

Atlas Cloud MCP Server 透過 Model Context Protocol 將您的 IDE 與 300+ AI 模型連接。支援任何相容 MCP 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

npx -y atlascloud-mcp

設定

將以下設定新增到您的 IDE 的 MCP 設定檔中。

{
  "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+ 可用 AI 模型。

atlas_quick_generate一步式內容創建，自動選擇最佳模型。

atlas_upload_media上傳本機檔案用於 API 工作流程。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

Schema 不可用

暫無可用範例

載入中...

為什麼選擇 Wan 2.5？

更實惠

儘管 Google 近期降價，但 Veo 3 整體仍然昂貴。Wan 2.5 輕量且性價比高，為創作者提供更多選擇，同時大幅降低製作成本。

一步生成，端到端同步

使用 Wan 2.5，無需單獨錄製語音或手動對齊口型。只需提供清晰、結構化的提示詞，即可一次性生成帶有音訊／配音及口型同步的完整影片，更快更簡單。

多語言友好

提示詞為中文時，Wan 2.5 能可靠地生成音視訊同步影片。相較之下，Veo 3 對中文提示詞經常顯示「未知語言」。

精準角色還原

Wan 2.5 擅長角色特徵還原，精確呈現角色外觀、表情與動作風格，讓生成的影片角色更具辨識度與個性化，增強敘事性與沉浸感。

藝術風格渲染

支援吉卜力風格渲染，創造手繪水彩質感和動畫效果。帶來溫暖、夢幻的視覺體驗，增強藝術感染力和敘事深度。

誰能受益？

行銷團隊

無論是產品發布、促銷活動還是品牌行銷，Wan 2.5 幫助您快速生成高品質影片，讓創作變得簡單高效。

產品演示和教學，無需協調煩惱
社群媒體行銷，多語言字幕和口型同步
AI 生成內容讓團隊專注於策略和創意

Bottom line: 總結：創作從未如此簡單、快速和智慧——Wan 2.5 是您行銷的祕密武器！

全球企業

為跨國公司提供理想的內容本地化解決方案，讓創作更輕鬆、更高效。

多語言影片支援，提示詞識別
一鍵生成口型同步的字幕和配音
快速內容本地化，面向全球市場

Bottom line: 總結：跨境內容創作從未如此簡單、快速和智慧。

故事創作者 / YouTuber

創作者可以利用 Wan 2.5 提高影片製作效率，同時確保高品質輸出。

沉浸式敘事，精準的角色動作和表情
更高的發布效率，減少剪輯和後期製作時間
從短影片到動畫故事片段的多樣化內容

企業培訓團隊

Wan 2.5 讓企業培訓更高效、更引人入勝。

專業影片取代枯燥的文字文件
快速建立操作演示和培訓教學
一致的風格和標準化輸出，便於全球推廣

自由創意人 / 小型工作室

Wan 2.5 讓創意自由流動，無需昂貴的設備或演員——AI 高效生成一切。

嘗試從短片到社群媒體內容的多樣化作品
從靈感到完成，「一鍵生成」
無需昂貴設備或專業演員的高品質內容

Bottom line: 總結：Wan 2.5 讓創作更輕鬆、更自由、更精彩，每次嘗試都令人驚艷！

教育機構 / 線上課程創作者

將創意轉化為現實，無需高成本——Wan 2.5 讓優質內容製作變得簡單經濟。

嘗試從短片到宣傳影片的各種風格
從概念到成品的更高製作效率
無需昂貴設備或專業人才的優質內容

Bottom line: 總結：Wan 2.5 讓創作輕鬆、高效、自由——每次嘗試都精彩紛呈！

核心特性

一步音視訊生成

在單一流程中生成帶有同步音訊、配音與口型同步的完整影片

雙角色同步

支援同時生成兩個角色，動作、表情和口型同步，自然互動

專業品質

高品質影片輸出，逼真的角色表情和精確的口型同步

多語言支援

對中文提示詞的出色支援，可靠生成多語言內容

性價比高

與競品相比成本大幅降低，同時保持專業品質

角色特徵還原

精準還原角色外觀、表情和動作風格，高保真度和個性化

藝術風格渲染

支援包括吉卜力風格手繪水彩質感在內的各種藝術風格

沉浸式場景

非常適合對話場景、訪談或雙人短片，自然的音視訊一致性

Digital Human Sync

Study Room Scholar

Middle-aged man reading with perfect lip-sync in a warm study environment

Lip-sync with audioEnvironmental soundsCharacter emotion

Prompt

A middle-aged man sitting at a wooden desk in a cozy study room, surrounded by bookshelves and a warm lamp glow. He opens an old book and reads aloud with a calm, deep voice: 'History teaches us more than just facts… it shows us who we are.' The room has subtle background sounds: pages turning, the faint ticking of a clock, and distant rain against the window.

Dual Character Scene

Park Sunset Romance

Couple interaction with synchronized dual character actions and expressions

Dual character syncNatural interactionAmbient soundscape

Prompt

A young couple sitting on a park bench during sunset. The woman leans her head on the man's shoulder. He whispers softly: 'No matter where we go, I'll always be here with you.' The sound includes the rustling of leaves, distant laughter of children playing, and the gentle hum of cicadas in the evening air.

Character Restoration

Ballet Performance Art

Precise character trait restoration with artistic movement and expression

Character trait restorationMovement precisionArtistic lighting

Prompt

A graceful ballerina with her hair in a messy bun, performing a powerful and emotional contemporary ballet routine. She is in a minimalist, dark art studio. Abstract patterns of light and shadow, projected from a hidden source, dance across her body and the surrounding walls, constantly shifting with her movements. The camera focuses on the tension in her muscles and the expressive gestures of her hands. A single, dramatic slow-motion shot captures her mid-air leap, with the light patterns swirling around her like a galaxy. Moody, artistic, high contrast.

Artistic Style Rendering

Ghibli Forest Magic

Studio Ghibli-inspired animation with hand-painted watercolor texture

Ghibli art styleHand-painted textureMagical atmosphere

Prompt

Studio Ghibli-inspired anime style. A young girl with a straw hat lies peacefully in a sun-dappled magical forest, surrounded by friendly, glowing forest spirits (Kodama). A gentle breeze rustles the leaves of the giant, ancient trees. The air is filled with sparkling dust motes, illuminated by shafts of sunlight. The art style is soft, with a hand-painted watercolor texture. The scene feels serene, magical, and heartwarming.

使用場景

🎬

影片製作

📢

行銷內容

🎓

教育影片

📱

社群媒體

🌐

多語言內容

💼

企業培訓

🎭

娛樂

💃

表演藝術

🎨

動畫與番劇

📚

故事講述

👥

雙角色影片

🎙️

訪談

📺

廣播媒體

技術規格

模型類型：音視訊同步生成

核心特性：音視訊同步、角色還原、藝術渲染、多語言

語言支援：中文、英文等

輸出品質：專業高清影片帶音訊

生成速度：快速一步生成

API 整合：RESTful API 與完整文檔

體驗 Wan 2.5 - 您的影片創作革命

加入數千名創作者和企業，用同步音視訊生成技術改變您的影片內容創作。

🎬一步音視訊同步

🌍多語言支援

⚡性價比高

Alibaba WAN 2.5 Image Edit

Alibaba WAN 2.5 Image Edit enables you to upload an existing visual and specify the desired adjustments. The model preserves layout and subject structure while implementing high-quality updates based on natural language.

Why creators love it

Structure-preserving edits: Make lighting, color, or object changes without breaking composition.
Text-guided styling: Reimagine materials, moods, or art styles with concise prompts.
Prompt expansion on demand: Enable automatic prompt enrichment when you need extra detail.
Flexible output sizes: Pick the resolution that best matches your downstream workflow.

Perfect for

Marketing and design teams refining campaign visuals.
E-commerce sellers upgrading product imagery.
Content creators polishing thumbnails, covers, and posts.
Artists experimenting with variations of their original work.

Billing rules

Minimum charge: 1 image.
Total cost = number of images × price per resolution.

How to use

Provide the image you want to refine. (Image dimensions must be in (384, 5000))
Describe the desired adjustments in the prompt.
Choose the target resolution and submit.
Review the enhanced output and download the version you like best.

Pro tips

Start with clear instructions about colors, lighting, or objects to adjust.
Pair positive and negative prompts to control what should or should not appear.
Keep source images at or above your target resolution for optimal fidelity.

Note

If you did not upload the image locally, please ensure that the image URL is accessible! A successfully accessible image will display a preview in the interface.

Recommended Resolutions

Aspect Ratio	Exact (W×H)	Exact Pixels	Rounded (W×H, ÷64)	Rounded Pixels
1:1	1448 × 1448	2,096,704	1408 × 1408	1,982,464
3:2	1773 × 1182	2,095,686	1728 × 1152	1,990,656
4:3	1672 × 1254	2,096,688	1664 × 1216	2,023,424
16:9	1936 × 1089	2,108,304	1920 × 1088	2,088,960
21:9	2212 × 948	2,096,976	2176 × 960	2,088,960
1:1	1024 × 1024	1,048,576	1024 × 1024	1,048,576
3:2	1254 × 836	1,048,344	1216 × 832	1,011,712
4:3	1182 × 887	1,048,434	1152 × 896	1,032,192
16:9	1365 × 768	1,048,320	1344 × 768	1,032,192
21:9	1564 × 670	1,047,880	1536 × 640	983,040
1:1	323 × 323	104,329	320 × 320	102,400
3:2	397 × 264	104,808	384 × 256	98,304
4:3	374 × 280	104,720	448 × 320	143,360
16:9	432 × 243	104,976	448 × 256	114,688
21:9	495 × 212	104,940	576 × 256	147,456

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