bytedance/seedream-v4/edit

图生图

Seedream v4 Edit API by ByteDance

bytedance/seedream-v4/edit

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 $0.027。$10 可运行约 370 次。

你可以继续：

图生视频图生图

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": "bytedance/seedream-v4/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。

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。

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

HTTP 请求头

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": "bytedance/seedream-v4/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']}")

响应

{
  "code": 200,
  "data": {
    "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

{
  "model": "bytedance/seedream-v4/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

{
  "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

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。

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

npx -y atlascloud-mcp

配置

将以下配置添加到您的 IDE 的 MCP 设置文件中。

{
  "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。

了解更多

github.com/AtlasCloudAI/mcp-server

API Schema

Schema 不可用

暂无可用示例

加载中...

模型亮点

具备五大核心能力:精准指令编辑、高特征保留、深度意图理解、多图输入输出和超高清分辨率。覆盖多样化创作场景,让每一个灵感瞬间高质量呈现。

精准指令编辑

只需用通俗语言描述需求,即可精准执行增删改换操作。支持商业设计、艺术创作和娱乐等领域应用。

高特征保留

角色一致性:在不同创作风格(插画/3D/摄影)下高度保持角色特征,让创作始终可控

场景保留:最大化保留原始图像细节,不用担心编辑后的「AI 油腻感」,实现无损编辑

深度意图理解

知识升级:专家级知识库,文本理解能力更上一层

灵感具象:从抽象到具体,把「天马行空」的灵感变成现实

预测推理:更强的推理能力,模拟跨时空的预测,让看不见的变得可见

自适应比例:开启后自动为您的图像匹配最佳宽高比

多图输入输出

一次性输入多张图像,支持组合、迁移、替换、衍生等复杂编辑操作,实现高难度合成

超高清分辨率

分辨率再次升级,支持超高清输出,专业级图像质量

应用场景

🎨

商业设计

🖼️

艺术创作

📸

照片编辑

🎮

游戏资源

👤

角色设计

🏗️

建筑可视化

📱

社交媒体

🎬

影视动画

Precision Editing

Perspective & Composition Control

Transform camera angles, adjust scene distance, and modify aspect ratios with precision

Prompt Template

Change the camera angle from eye-level to bird's-eye view, adjust the scene from close-up to medium shot, and convert the image aspect ratio to 16:9. Maintain all original elements and lighting while adapting the composition for the new perspective and format.

Text & Formula Generation

Mathematical Whiteboard Creation

Generate clean whiteboard with precise mathematical formulas and equations

Prompt Template

Create a clean white whiteboard with the following mathematical equations written in clear, professional handwriting: E=mc², √(9)=3, and the quadratic formula (-b±√(b²-4ac))/2a. Use black or dark blue marker style, with proper spacing and mathematical notation.

Deep Intent Understanding

Sketch to Reality Transformation

Transform rough sketches into detailed realistic objects - bringing wild imagination to life

Prompt Template

Based on this rough sketch, generate a vintage television set from the 1950s-60s era. Transform the abstract lines and shapes into a realistic, detailed old-style TV with wooden cabinet, rounded screen, control knobs, and period-appropriate design elements. Make the vague concept concrete and lifelike.

High Feature Preservation

Lossless Detail Enhancement

Maximize original image detail retention, avoiding AI-generated artifacts for truly lossless editing

Prompt Template

Enhance this image while maximizing the preservation of original details. Avoid any AI-generated 'plastic' or 'oily' artifacts. Maintain authentic textures, natural lighting, and original image characteristics. Focus on clean, lossless enhancement that respects the source material's integrity.

Text Transformation

Creative Font Styling

Transform plain text into artistic, creative typography while maintaining readability

Prompt Template

Transform all the text in this image into creative, artistic fonts. Replace the standard typography with stylized lettering that matches the image's aesthetic - use decorative fonts, calligraphy styles, or artistic text treatments. Maintain the same text content and layout while making the typography more visually appealing and creative.

核心能力

生成

文生图创作

先进的文本理解和图像生成能力,支持各种艺术风格和专业需求,从概念到成品一步到位。

编辑

智能图像编辑

基于自然语言的编辑命令,支持对象添加/移除、风格迁移、背景替换等更复杂的编辑操作。

合成

多图组合

革命性的多图输入能力,实现复杂的图像合成、风格迁移和创意组合,控制力前所未有。

为什么选择 Seedream 4.0?

🚀

一体化解决方案

单一模型处理生成、编辑和合成 - 无需在不同工具间切换

🎯

专业品质

商业级输出质量,对每个细节精确控制

🔄

一致的风格

在多次生成和编辑中保持角色和风格的一致性

技术规格

模型架构:由 ByteDance 豆包 AI 提供支持

核心特性:生成 + 编辑集成

分辨率支持:超高清输出

输入支持:文本、单图/多图

输出格式:PNG、JPEG、WebP

API 集成:RESTful API 与 SDK 支持

体验 Seedream 4.0 的强大功能

加入全球创作者行列,用 ByteDance 最先进的集成图像 AI 模型革新视觉内容创作。

✨专业工具

⚡闪电般快速

🌐一体化平台

Seedream 4: A next-generation multimodal image generation system developed by ByteDance Seed

Model Card Overview

Field	Description
Model Name	Seedream 4
Developed by	ByteDance Seed Team
Release Date	September 9, 2025
Model Type	Multimodal Image Generation
Related Links	Official Website, Technical Report (arXiv), GitHub Organization (ByteDance-Seed)

Introduction

Seedream 4 is a powerful, efficient, and high-performance multimodal image generation system that unifies text-to-image (T2I) synthesis, image editing, and multi-image composition within a single, integrated framework. Engineered for scalability and efficiency, the model introduces a novel diffusion transformer (DiT) architecture combined with a powerful Variational Autoencoder (VAE). This design enables the fast generation of native high-resolution images up to 4K, while significantly reducing computational requirements compared to its predecessors.

The primary goal of Seedream 4 is to extend traditional T2I systems into a more interactive and multidimensional creative tool. It is designed to handle complex tasks involving precise image editing, in-context reasoning, and multi-image referencing, pushing the boundaries of generative AI for both creative and professional applications.

Key Features & Innovations

Seedream 4 introduces several key advancements in image generation technology:

Unified Multimodal Architecture: It integrates T2I generation, image editing, and multi-image composition into a single model, allowing for seamless transitions between different creative workflows.
Efficient and Scalable Design: The model features a highly efficient DiT backbone and a high-compression VAE, achieving over 10x inference acceleration compared to Seedream 3.0 while delivering superior performance. This architecture is hardware-friendly and easily scalable.
Ultra-Fast, High-Resolution Output: Seedream 4 can generate native high-resolution images (from 1K to 4K) in as little as 1.4 to 1.8 seconds for a 2K image, greatly enhancing user interaction and production efficiency.
Advanced Multimodal Capabilities: The model excels at complex tasks such as precise, instruction-based image editing, in-context reasoning, and generating new images by blending elements from multiple reference images.
Professional and Knowledge-Based Content Generation: Beyond artistic imagery, Seedream 4 can generate structured and knowledge-based content, including charts, mathematical formulas, and professional design materials, bridging the gap between creative expression and practical application.
Advanced Training and Acceleration: The model is pre-trained on billions of text-image pairs and utilizes a multi-stage post-training process (CT, SFT, RLHF) to enhance its capabilities. Inference is accelerated through a combination of adversarial distillation, quantization, and speculative decoding.

Model Architecture & Technical Details

Seedream 4's architecture is a significant leap forward, focusing on efficiency and power. The core components are a diffusion transformer (DiT) and a Variational Autoencoder (VAE).

Pre-training Data: Billions of text-image pairs, including a specialized pipeline for knowledge-related data like instructional images and formulas.
Training Strategy: A multi-stage approach, starting at a 512x512 resolution and fine-tuning at higher resolutions up to 4K.
Post-training: A joint multi-task process involving Continuing Training (CT), Supervised Fine-Tuning (SFT), and Reinforcement Learning from Human Feedback (RLHF) to enhance instruction following and alignment.
Inference Acceleration: A holistic system combining an adversarial learning framework, hardware-aware quantization (adaptive 4/8-bit), and speculative decoding.

Intended Use & Applications

Seedream 4 is designed for a wide range of creative and professional applications, moving beyond simple image generation to become a comprehensive visual content creation tool.

Creative Content Generation: Creating high-quality, artistic images, illustrations, and concept art from text prompts.
Advanced Image Editing: Performing complex edits on existing images using natural language instructions, such as adding or removing objects, changing styles, and modifying backgrounds.
Design and Marketing: Generating professional design materials, product mockups, and marketing visuals with precise control over text and branding elements.
Educational and Technical Content: Creating structured, knowledge-based visuals like diagrams, charts, and mathematical formulas for educational or technical documentation.
Multi-Image Composition: Blending elements from multiple source images to create new compositions, such as virtual try-ons for fashion or combining characters with new scenes.

Performance

Seedream 4 has demonstrated state-of-the-art performance on both internal and public benchmarks as of September 18, often outperforming other leading models in text-to-image and image editing tasks.

MagicBench (Internal Benchmark)

Task	Performance Summary
Text-to-Image	Achieved high scores in prompt following, aesthetics, and text-rendering.
Single-Image Editing	Showed a good balance between prompt following and alignment with the source image.

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GPT Image 2 Developer Text-to-Image generates polished visuals from natural-language prompts, with common aspect ratios and 1k, 2k, or supported 4k output tiers. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

From$0.009/张

$0.004/张

-50%

一个 API，畅享全模态 AI。

探索全部模型

Seedream v4 Edit API by ByteDance

输入

输出

参数

代码示例

安装

认证

HTTP 请求头

提交请求

提交请求

请求体

响应

检查状态

轮询示例

状态值

完成响应

上传文件

上传示例

响应

Input Schema

请求体示例

Output Schema

响应示例

Atlas Cloud Skills

支持的客户端

安装

设置 API Key

功能

MCP Server

支持的客户端

安装

配置

可用工具

API Schema

Seedream 4.0 - ByteDance 一体化视觉创作模型

模型亮点

精准指令编辑

高特征保留

深度意图理解

多图输入输出

超高清分辨率

应用场景

Prompt Examples & Creative Templates

Perspective & Composition Control

Mathematical Whiteboard Creation

Sketch to Reality Transformation

Lossless Detail Enhancement

Creative Font Styling

核心能力

为什么选择 Seedream 4.0?

一体化解决方案

专业品质

一致的风格

技术规格

体验 Seedream 4.0 的强大功能

Seedream 4: A next-generation multimodal image generation system developed by ByteDance Seed

Model Card Overview

Introduction

Key Features & Innovations

Model Architecture & Technical Details

Intended Use & Applications

Performance

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Seedream v4.5 Sequential

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Seedream v4

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Seedream v4 Edit Sequential

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GPT Image 2 Developer Text-to-Image

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