Midjourney V7 パン拡張
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-pan",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"direction": "right",
"scale": 2
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-pan",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"direction": "right",
"scale": 2
}
}
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-pan',
model_params: {task_id: 'task-unified-xxx', image_number: 0, direction: 'right', scale: 2}
})
};
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-pan',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 0,
'direction' => 'right',
'scale' => 2
]
]),
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-pan\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"direction\": \"right\",\n \"scale\": 2\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-pan\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"direction\": \"right\",\n \"scale\": 2\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-pan\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"direction\": \"right\",\n \"scale\": 2\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": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}Midjourney V7
Midjourney V7 パン
- 指定した方向に画像キャンバスを拡張し、元の画像とシームレスに繋がる新しいコンテンツを生成します
- 上下左右の4方向をサポート
- outpaintとの違い:panは一方向に拡張、outpaintは四方向に同時に拡張
- 非同期処理モード、返されたタスクIDで照会を実行
POST
/
v1
/
images
/
generations
Midjourney V7 パン拡張
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-pan",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"direction": "right",
"scale": 2
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-pan",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"direction": "right",
"scale": 2
}
}
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-pan',
model_params: {task_id: 'task-unified-xxx', image_number: 0, direction: 'right', scale: 2}
})
};
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-pan',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 0,
'direction' => 'right',
'scale' => 2
]
]),
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-pan\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"direction\": \"right\",\n \"scale\": 2\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-pan\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"direction\": \"right\",\n \"scale\": 2\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-pan\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"direction\": \"right\",\n \"scale\": 2\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": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}Midjourneyにはコンテンツ審査機能が組み込まれています。生成された画像の一部が審査でフィルタリングされた場合、そのリクエストで消費されたクレジットは返金されません。プロンプトの内容がガイドラインに準拠しているかご確認ください。
承認
##全てのインターフェースはBearer Token認証が必要です##
API Keyの取得:
API Key管理ページにアクセスしてAPI Keyを取得してください
リクエストヘッダーに追加:
Authorization: Bearer YOUR_API_KEYボディ
application/json
レスポンス
タスク作成成功
タスク作成タイムスタンプ
例:
1757165031
タスクID
例:
"task-unified-1757165031-mjv7"
実際に使用されたモデル名
タスクタイプ
利用可能なオプション:
image.generation.task タスク進捗率 (0-100)
必須範囲:
0 <= x <= 100例:
0
タスクステータス
利用可能なオプション:
pending, processing, completed, failed 例:
"pending"
Show child attributes
Show child attributes
利用可能なオプション:
text, image, audio, video 例:
"image"
Show child attributes
Show child attributes
⌘I