简介

一个某扩散模型的图像生成API，可以输入图像提示词，然后返回图像生成结果，适合生成二刺螈图像。

参数说明

输入参数

prompt（画图提示词）

类型：string

说明：用户输入的主要提示词，用于指导 AI 生成图像的内容（示例：_mika_blue_archive, bikini skirt, beach,{teranekosu,gin00,ciloranko},{goldowl}）。

model（图像生成模型）

类型：string

说明：用于生成图像的 AI 模型。该值目前只能是nd-imagine-v3，请确保您的APIKey已经勾选此模型的权限。

size（生成图像大小）

类型：string

说明：指定生成图像的大小。目前接受且仅接受以下几种尺寸：'832x1216', '1024x1024', '1216x832', '512x768', '768x512', '640x640', '1024x1536', '1536x1024', '1472x1472', '1088x1920', '1920x1088'。

negative_prompt（负向提示词） （可选）

类型：string

说明：用于指定 AI 在生成图像时应避免的元素或主题。

seed（随机种子） （可选）

类型：int

说明：用于初始化 AI 生成图像时随机过程的种子，确保结果的可复现性，缺省或者填-1表示随机，填一个整数（例如： 2794977878）表示指定特定的seed生成，相同的参数+seed会返回完全相同的生成结果。

输出参数

示例：

{
  "created": 1589478378,
  "data": [
    {
      "url": "data:image/jpeg;base64,iVBORw0KGgoAA...."
    }
  ]
}

其中data.url是生成图像的Base64字符串。

注意事项

其中size参数目前只可以选择如下几种大小：

"832x1216", "1024x1024", "1216x832", "512x768", "768x512", "640x640", "1024x1536", "1536x1024", "1472x1472", "1088x1920", "1920x1088"

定价

'832x1216', '1024x1024', '1216x832', '512x768', '768x512', '640x640'

成功请求生成一次以上这些尺寸的图像，扣费6000代币（大约0.17元

'1024x1536, '1536x1024', '1472x1472', '1088x1920', '1920x1088'

成功请求生成一次以上这些尺寸的图像，扣费30000代币（大约0.88元

（大尺寸图像较为昂贵，谨慎使用，因为成本价差不多就这么多，~~并不是因为太黑心~~

请求参数

Authorization

在 Header 添加参数

Authorization

，其值为在 Bearer 之后拼接 Token

示例：

Authorization: Bearer ********************

Body 参数application/x-www-form-urlencoded

prompt

string

必需

示例值:

_mika_blue_archive, bikini skirt, beach,{teranekosu,gin00,ciloranko},{goldowl}

model

string

必需

示例值:

nd-imagine-v3

size

string

必需

示例值:

1024x1024

示例代码

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

返回响应

🟢200成功

application/json

Body

object {0}

示例

{
    "created": 1706362191,
    "data": [
        {
            "url": "data:image/jpeg;base64,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

ND图像生成 API

简介#

参数说明#

输入参数#

输出参数#

注意事项#

定价#

请求参数

示例代码

返回响应

简介

参数说明

输入参数

输出参数

注意事项

定价