Wan-2.5 Image Edit
图生图

Wan 2.5 Image Edit API by Alibaba

alibaba/wan-2.5/image-edit
Image-edit

Open and Advanced Large-Scale Image Generative Models.

输入

正在加载参数配置...

输出

空闲
生成的图片将在这里显示
配置参数后点击运行开始生成

每次运行将花费 $0.021。$10 可运行约 476 次。

你可以继续:

参数

代码示例

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/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/generateImage

请求体

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",
    "input": {
        "prompt": "A beautiful landscape with mountains and lake"
    }
}

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.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "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": "alibaba/wan-2.5/image-edit"
}

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 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

响应示例

json
{
  "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 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

请登录以查看请求历史

您需要登录才能访问模型请求历史记录。

登录

Wan 2.5 - 智能视频创作者的选择

热门

一体化音视频同步生成

Wan 2.5 是一款革命性的 AI 视频生成模型,一步创建同步的音视频内容。无需单独录制语音或手动对口型 - 只需提供清晰、结构化的提示词,即可即时生成带有音频/配音和口型同步的完整视频。

为什么选择 Wan 2.5?

更实惠

尽管 Google 最近降价,但 Veo 3 整体仍然昂贵。Wan 2.5 轻量且性价比高,为创作者提供更多选择,同时大幅降低制作成本。

一步生成,端到端同步

使用 Wan 2.5,无需单独录制语音或手动对齐口型。只需提供清晰、结构化的提示词,一次性生成带有音频/配音和口型同步的完整视频 - 更快更简单。

多语言友好

当提示词为中文时,Wan 2.5 可靠地生成音视频同步视频。相比之下,Veo 3 对中文提示词经常显示「未知语言」。

精准角色还原

Wan 2.5 擅长角色特征还原,准确呈现角色外观、表情和动作风格,让生成的视频角色更具辨识度和个性化,增强叙事性和沉浸感。

艺术风格渲染

支持吉卜力风格渲染,创造手绘水彩质感和动画效果。带来温暖、梦幻的视觉体验,增强艺术感染力和叙事深度。

谁能受益?

营销团队

无论是产品发布、促销活动还是品牌营销,Wan 2.5 帮助您快速生成高质量视频,让创作变得简单高效。

  • 产品演示和教程,无需协调烦恼
  • 社交媒体营销,多语言字幕和口型同步
  • AI 生成内容让团队专注于策略和创意
Bottom line: 总结:创作从未如此简单、快速和智能 - Wan 2.5 是您营销的秘密武器!

全球企业

为跨国公司提供理想的内容本地化解决方案,让创作更轻松、更高效。

  • 多语言视频支持,提示词识别
  • 一键生成口型同步的字幕和配音
  • 快速内容本地化,面向全球市场
Bottom line: 总结:跨境内容创作从未如此简单、快速和智能。

故事创作者 / YouTuber

创作者可以利用 Wan 2.5 提高视频制作效率,同时确保高质量输出。

  • 沉浸式叙事,精准的角色动作和表情
  • 更高的发布效率,减少编辑和后期制作时间
  • 从短视频到动画故事片段的多样化内容

企业培训团队

Wan 2.5 让企业培训更高效、更引人入胜。

  • 专业视频取代枯燥的文本文档
  • 快速创建操作演示和培训教程
  • 一致的风格和标准化输出,便于全球推广

自由创意人 / 小型工作室

Wan 2.5 让创意自由流动,无需昂贵的设备或演员 - AI 高效生成一切。

  • 尝试从短片到社交媒体内容的多样化作品
  • 从灵感到完成,「一键生成」
  • 无需昂贵设备或专业演员的高质量内容
Bottom line: 总结:Wan 2.5 让创作更轻松、更自由、更精彩,每次尝试都令人惊艳!

教育机构 / 在线课程创作者

将创意转化为现实,无需高成本 - Wan 2.5 让优质内容制作变得简单经济。

  • 尝试从短片到宣传视频的各种风格
  • 从概念到成品的更高制作效率
  • 无需昂贵设备或专业人才的优质内容
Bottom line: 总结:Wan 2.5 让创作轻松、高效、自由 - 每次尝试都精彩纷呈!

核心特性

一步音视频生成

在单一流程中生成带有同步音频、配音和口型同步的完整视频

双角色同步

支持同时生成两个角色,动作、表情和口型同步,自然互动

专业品质

高质量视频输出,逼真的角色表情和精确的口型同步

多语言支持

对中文提示词的出色支持,可靠生成多语言内容

性价比高

与竞品相比成本大幅降低,同时保持专业品质

角色特征还原

精准还原角色外观、表情和动作风格,高保真度和个性化

艺术风格渲染

支持包括吉卜力风格手绘水彩质感在内的各种艺术风格

沉浸式场景

非常适合对话场景、访谈或双人短片,自然的音视频一致性

Wan 2.5 Prompt Showcase

Discover the power of Wan 2.5 through these curated examples. From digital human lip-sync to dual character scenes, artistic rendering to character restoration - experience the possibilities.

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.

使用场景

🎬
视频制作
📢
营销内容
🎓
教育视频
📱
社交媒体
🌐
多语言内容
💼
企业培训
🎭
娱乐
💃
表演艺术
🎨
动画与番剧
📚
故事讲述
👥
双角色视频
🎙️
访谈
📺
广播媒体

技术规格

模型类型:音视频同步生成
核心特性:音视频同步、角色还原、艺术渲染、多语言
语言支持:中文、英文等
输出质量:专业高清视频带音频
生成速度:快速一步生成
API 集成:RESTful API 与完整文档

体验 Wan 2.5 - 您的视频创作革命

加入数千名创作者和企业,用同步音视频生成技术改变您的视频内容创作。

🎬一步音视频同步
🌍多语言支持
性价比高

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

  1. Provide the image you want to refine. (Image dimensions must be in (384, 5000))
  2. Describe the desired adjustments in the prompt.
  3. Choose the target resolution and submit.
  4. 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.


Aspect RatioExact (W×H)Exact PixelsRounded (W×H, ÷64)Rounded Pixels
1:11448 × 14482,096,7041408 × 14081,982,464
3:21773 × 11822,095,6861728 × 11521,990,656
4:31672 × 12542,096,6881664 × 12162,023,424
16:91936 × 10892,108,3041920 × 10882,088,960
21:92212 × 9482,096,9762176 × 9602,088,960
1:11024 × 10241,048,5761024 × 10241,048,576
3:21254 × 8361,048,3441216 × 8321,011,712
4:31182 × 8871,048,4341152 × 8961,032,192
16:91365 × 7681,048,3201344 × 7681,032,192
21:91564 × 6701,047,8801536 × 640983,040
1:1323 × 323104,329320 × 320102,400
3:2397 × 264104,808384 × 25698,304
4:3374 × 280104,720448 × 320143,360
16:9432 × 243104,976448 × 256114,688
21:9495 × 212104,940576 × 256147,456

300+ 模型,即刻开启,

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