Midjourney V7 Outpaint
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-outpaint",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 1,
"scale": 1.5
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-outpaint",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 1,
"scale": 1.5
}
}
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-outpaint',
model_params: {task_id: 'task-unified-xxx', image_number: 1, scale: 1.5}
})
};
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-outpaint',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 1,
'scale' => 1.5
]
]),
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-outpaint\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 1,\n \"scale\": 1.5\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-outpaint\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 1,\n \"scale\": 1.5\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-outpaint\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 1,\n \"scale\": 1.5\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 Erweiterung
POST
/
v1
/
images
/
generations
Midjourney V7 Outpaint
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-outpaint",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 1,
"scale": 1.5
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-outpaint",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 1,
"scale": 1.5
}
}
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-outpaint',
model_params: {task_id: 'task-unified-xxx', image_number: 1, scale: 1.5}
})
};
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-outpaint',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 1,
'scale' => 1.5
]
]),
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-outpaint\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 1,\n \"scale\": 1.5\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-outpaint\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 1,\n \"scale\": 1.5\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-outpaint\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 1,\n \"scale\": 1.5\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 verfügt über ein integriertes Moderationssystem. Wenn einige generierte Bilder durch die Moderation gefiltert werden, können die für diese Anfrage verbrauchten Credits nicht erstattet werden. Bitte achten Sie darauf, dass Ihre Prompts den Inhaltsrichtlinien entsprechen.
Autorisierungen
Alle Endpunkte erfordern Bearer Token Authentifizierung
API Key erhalten:
Besuchen Sie die API Key Verwaltungsseite um Ihren API Key zu erhalten
Zum Request-Header hinzufuegen:
Authorization: Bearer YOUR_API_KEY
Body
application/json
Antwort
Aufgabe erfolgreich erstellt
Zeitstempel der Aufgabenerstellung
Beispiel:
1757165031
Aufgaben-ID
Beispiel:
"task-unified-1757165031-mjv7"
Tatsaechlich verwendeter Modellname
Aufgabenobjekttyp
Verfügbare Optionen:
image.generation.task Aufgabenfortschritt in Prozent (0-100)
Erforderlicher Bereich:
0 <= x <= 100Beispiel:
0
Aufgabenstatus
Verfügbare Optionen:
pending, processing, completed, failed Beispiel:
"pending"
Show child attributes
Show child attributes
Verfügbare Optionen:
text, image, audio, video Beispiel:
"image"
Show child attributes
Show child attributes