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POST
/
v1
/
images
/
generations
mj-v7-upload-paint 接口
curl --request POST \
  --url https://api.evolink.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "mj-v7-upload-paint",
  "prompt": "美丽的山景背景",
  "image_urls": [
    "https://example.com/photo.jpg"
  ],
  "model_params": {
    "mask": {
      "areas": [
        {
          "width": 100,
          "height": 100,
          "points": [
            10,
            10,
            10,
            100,
            100,
            100,
            100,
            10
          ]
        }
      ]
    },
    "canvas": {
      "width": 1024,
      "height": 1024
    },
    "img_pos": {
      "width": 512,
      "height": 512,
      "x": 256,
      "y": 256
    },
    "speed": "fast"
  }
}
'
import requests

url = "https://api.evolink.ai/v1/images/generations"

payload = {
    "model": "mj-v7-upload-paint",
    "prompt": "美丽的山景背景",
    "image_urls": ["https://example.com/photo.jpg"],
    "model_params": {
        "mask": { "areas": [
                {
                    "width": 100,
                    "height": 100,
                    "points": [10, 10, 10, 100, 100, 100, 100, 10]
                }
            ] },
        "canvas": {
            "width": 1024,
            "height": 1024
        },
        "img_pos": {
            "width": 512,
            "height": 512,
            "x": 256,
            "y": 256
        },
        "speed": "fast"
    }
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: 'mj-v7-upload-paint',
    prompt: '美丽的山景背景',
    image_urls: ['https://example.com/photo.jpg'],
    model_params: {
      mask: {
        areas: [{width: 100, height: 100, points: [10, 10, 10, 100, 100, 100, 100, 10]}]
      },
      canvas: {width: 1024, height: 1024},
      img_pos: {width: 512, height: 512, x: 256, y: 256},
      speed: 'fast'
    }
  })
};

fetch('https://api.evolink.ai/v1/images/generations', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.evolink.ai/v1/images/generations",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'model' => 'mj-v7-upload-paint',
    'prompt' => '美丽的山景背景',
    'image_urls' => [
        'https://example.com/photo.jpg'
    ],
    'model_params' => [
        'mask' => [
                'areas' => [
                                [
                                                                'width' => 100,
                                                                'height' => 100,
                                                                'points' => [
                                                                                                                                10,
                                                                                                                                10,
                                                                                                                                10,
                                                                                                                                100,
                                                                                                                                100,
                                                                                                                                100,
                                                                                                                                100,
                                                                                                                                10
                                                                ]
                                ]
                ]
        ],
        'canvas' => [
                'width' => 1024,
                'height' => 1024
        ],
        'img_pos' => [
                'width' => 512,
                'height' => 512,
                'x' => 256,
                'y' => 256
        ],
        'speed' => 'fast'
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}
package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.evolink.ai/v1/images/generations"

	payload := strings.NewReader("{\n  \"model\": \"mj-v7-upload-paint\",\n  \"prompt\": \"美丽的山景背景\",\n  \"image_urls\": [\n    \"https://example.com/photo.jpg\"\n  ],\n  \"model_params\": {\n    \"mask\": {\n      \"areas\": [\n        {\n          \"width\": 100,\n          \"height\": 100,\n          \"points\": [\n            10,\n            10,\n            10,\n            100,\n            100,\n            100,\n            100,\n            10\n          ]\n        }\n      ]\n    },\n    \"canvas\": {\n      \"width\": 1024,\n      \"height\": 1024\n    },\n    \"img_pos\": {\n      \"width\": 512,\n      \"height\": 512,\n      \"x\": 256,\n      \"y\": 256\n    },\n    \"speed\": \"fast\"\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}
HttpResponse<String> response = Unirest.post("https://api.evolink.ai/v1/images/generations")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"mj-v7-upload-paint\",\n  \"prompt\": \"美丽的山景背景\",\n  \"image_urls\": [\n    \"https://example.com/photo.jpg\"\n  ],\n  \"model_params\": {\n    \"mask\": {\n      \"areas\": [\n        {\n          \"width\": 100,\n          \"height\": 100,\n          \"points\": [\n            10,\n            10,\n            10,\n            100,\n            100,\n            100,\n            100,\n            10\n          ]\n        }\n      ]\n    },\n    \"canvas\": {\n      \"width\": 1024,\n      \"height\": 1024\n    },\n    \"img_pos\": {\n      \"width\": 512,\n      \"height\": 512,\n      \"x\": 256,\n      \"y\": 256\n    },\n    \"speed\": \"fast\"\n  }\n}")
  .asString();
require 'uri'
require 'net/http'

url = URI("https://api.evolink.ai/v1/images/generations")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"mj-v7-upload-paint\",\n  \"prompt\": \"美丽的山景背景\",\n  \"image_urls\": [\n    \"https://example.com/photo.jpg\"\n  ],\n  \"model_params\": {\n    \"mask\": {\n      \"areas\": [\n        {\n          \"width\": 100,\n          \"height\": 100,\n          \"points\": [\n            10,\n            10,\n            10,\n            100,\n            100,\n            100,\n            100,\n            10\n          ]\n        }\n      ]\n    },\n    \"canvas\": {\n      \"width\": 1024,\n      \"height\": 1024\n    },\n    \"img_pos\": {\n      \"width\": 512,\n      \"height\": 512,\n      \"x\": 256,\n      \"y\": 256\n    },\n    \"speed\": \"fast\"\n  }\n}"

response = http.request(request)
puts response.read_body
{
  "created": 1757165031,
  "id": "task-unified-1757165031-mjv7",
  "model": "<string>",
  "object": "image.generation.task",
  "progress": 0,
  "status": "pending",
  "task_info": {
    "can_cancel": true,
    "estimated_time": 45
  },
  "type": "image",
  "usage": {
    "billing_rule": "per_call",
    "credits_reserved": 1.8,
    "user_group": "default"
  }
}
{
  "error": {
    "code": "invalid_request",
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": "unauthorized",
    "message": "Invalid or expired token",
    "type": "authentication_error"
  }
}
{
  "error": {
    "code": "insufficient_quota",
    "message": "Insufficient quota. Please top up your account.",
    "type": "insufficient_quota"
  }
}
{
  "error": {
    "code": "model_access_denied",
    "message": "Token does not have access to model: mj-v7-upload-paint",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": "rate_limit_exceeded",
    "message": "Too many requests, please try again later",
    "type": "rate_limit_error"
  }
}
{
  "error": {
    "code": "internal_error",
    "message": "Internal server error",
    "type": "api_error"
  }
}
Midjourney 内置内容审核机制。如果生成的部分图像触发了审核过滤，该次请求已消耗的积分将无法退还，请留意提示词的内容合规性。

授权

​
Authorization
string
header
必填

##所有接口均需要使用Bearer Token进行认证##

获取 API Key ：

访问 API Key 管理页面 获取您的 API Key

使用时在请求头中添加：

Authorization: Bearer YOUR_API_KEY

请求体

application/json
​
model
enum<string>
默认值:mj-v7-upload-paint
必填

模型名称

可用选项:
mj-v7-upload-paint
示例:

"mj-v7-upload-paint"

​
prompt
string
必填

编辑提示词

示例:

"美丽的山景背景"

​
image_urls
string<uri>[]
必填

输入图片URL（取第一个）

Maximum array length: 1
示例:
["https://example.com/photo.jpg"]
​
model_params
object
必填

高级编辑参数

​
callback_url
string<uri>

任务完成后的HTTPS回调地址

回调时机：

  • 任务完成（completed）、失败（failed）或取消（cancelled）时触发
  • 在计费确认完成后发送

安全限制：

  • 仅支持HTTPS协议
  • 禁止回调到内网IP地址（127.0.0.1、10.x.x.x、172.16-31.x.x、192.168.x.x等）
  • URL长度不超过2048字符

回调机制：

  • 超时时间：10秒
  • 失败后最多重试3次（会分别在失败的1秒/2秒/4秒后进行重试）
  • 回调响应体格式与任务查询接口返回的格式一致
  • 回调地址若返回2xx状态码视为成功，其他状态码会触发重试
示例:

"https://your-domain.com/webhooks/image-task-completed"

响应

图像生成任务创建成功

​
created
integer

任务创建时间戳

示例:

1757165031

​
id
string

任务ID

示例:

"task-unified-1757165031-mjv7"

​
model
string

实际使用的模型名称

​
object
enum<string>

任务的具体类型

可用选项:
image.generation.task
​
progress
integer

任务进度百分比 (0-100)

必填范围: 0 <= x <= 100
示例:

0

​
status
enum<string>

任务状态

可用选项:
pending,
processing,
completed,
failed
示例:

"pending"

​
task_info
object
​
type
enum<string>
可用选项:
text,
image,
audio,
video
示例:

"image"

​
usage
object