curl --request POST \
--url https://api.apimart.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1/images/generations";
const payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1/images/generations"
payload := map[string]interface{}{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String payload = """
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.apimart.ai/v1/images/generations"))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
System.out.println(client.send(request,
HttpResponse.BodyHandlers.ofString()).body());
}
}
<?php
$url = "https://api.apimart.ai/v1/images/generations";
$payload = [
"model" => "wan2.7-image-pro",
"prompt" => "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1/images/generations")
payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
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 = payload.to_json
response = http.request(request)
puts response.body
import Foundation
let url = URL(string: "https://api.apimart.ai/v1/images/generations")!
let payload: [String: Any] = [
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
]
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let error = error { print("Error: \(error)"); return }
if let data = data, let str = String(data: data, encoding: .utf8) { print(str) }
}
task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
class Program
{
static async Task Main(string[] args)
{
var payload = @"{
""model"": ""wan2.7-image-pro"",
""prompt"": ""A flower shop with exquisite windows, beautiful wooden door, flowers on display""
}";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var response = await client.PostAsync(
"https://api.apimart.ai/v1/images/generations", content);
Console.WriteLine(await response.Content.ReadAsStringAsync());
}
}
{
"code": "success",
"data": [
{
"task_id": "task_01HX...",
"status": "processing"
}
]
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed. Please check your API key.",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance. Please top up your account.",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "Too many requests. Please try again later.",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "Internal server error. Please try again later.",
"type": "server_error"
}
}
wan2.7-image
wan2.7 Bildgenerierung und -bearbeitung
- Wan2.7-Bildserie: unterstützt Text-zu-Bild, Bildbearbeitung, interaktive Bearbeitung, sequenzielle Generierung und mehrere Referenzbilder
- Asynchroner Verarbeitungsmodus — Aufgabe einreichen und Ergebnisse mit der zurückgegebenen task_id abfragen
- Unterstützt 1K- / 2K- / 4K-Auflösung; wan2.7-image-pro unterstützt bis zu 4K für Text-zu-Bild
- Die Abrechnung basiert auf der Anzahl der erfolgreich generierten Bilder, unabhängig von Auflösung oder Seitenverhältnis
POST
/
v1
/
images
/
generations
curl --request POST \
--url https://api.apimart.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1/images/generations";
const payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1/images/generations"
payload := map[string]interface{}{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String payload = """
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.apimart.ai/v1/images/generations"))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
System.out.println(client.send(request,
HttpResponse.BodyHandlers.ofString()).body());
}
}
<?php
$url = "https://api.apimart.ai/v1/images/generations";
$payload = [
"model" => "wan2.7-image-pro",
"prompt" => "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1/images/generations")
payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
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 = payload.to_json
response = http.request(request)
puts response.body
import Foundation
let url = URL(string: "https://api.apimart.ai/v1/images/generations")!
let payload: [String: Any] = [
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
]
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let error = error { print("Error: \(error)"); return }
if let data = data, let str = String(data: data, encoding: .utf8) { print(str) }
}
task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
class Program
{
static async Task Main(string[] args)
{
var payload = @"{
""model"": ""wan2.7-image-pro"",
""prompt"": ""A flower shop with exquisite windows, beautiful wooden door, flowers on display""
}";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var response = await client.PostAsync(
"https://api.apimart.ai/v1/images/generations", content);
Console.WriteLine(await response.Content.ReadAsStringAsync());
}
}
{
"code": "success",
"data": [
{
"task_id": "task_01HX...",
"status": "processing"
}
]
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed. Please check your API key.",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance. Please top up your account.",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "Too many requests. Please try again later.",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "Internal server error. Please try again later.",
"type": "server_error"
}
}
curl --request POST \
--url https://api.apimart.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1/images/generations";
const payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1/images/generations"
payload := map[string]interface{}{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String payload = """
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.apimart.ai/v1/images/generations"))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
System.out.println(client.send(request,
HttpResponse.BodyHandlers.ofString()).body());
}
}
<?php
$url = "https://api.apimart.ai/v1/images/generations";
$payload = [
"model" => "wan2.7-image-pro",
"prompt" => "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1/images/generations")
payload = {
model: "wan2.7-image-pro",
prompt: "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
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 = payload.to_json
response = http.request(request)
puts response.body
import Foundation
let url = URL(string: "https://api.apimart.ai/v1/images/generations")!
let payload: [String: Any] = [
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
]
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let error = error { print("Error: \(error)"); return }
if let data = data, let str = String(data: data, encoding: .utf8) { print(str) }
}
task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
class Program
{
static async Task Main(string[] args)
{
var payload = @"{
""model"": ""wan2.7-image-pro"",
""prompt"": ""A flower shop with exquisite windows, beautiful wooden door, flowers on display""
}";
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var response = await client.PostAsync(
"https://api.apimart.ai/v1/images/generations", content);
Console.WriteLine(await response.Content.ReadAsStringAsync());
}
}
{
"code": "success",
"data": [
{
"task_id": "task_01HX...",
"status": "processing"
}
]
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed. Please check your API key.",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance. Please top up your account.",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "Too many requests. Please try again later.",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "Internal server error. Please try again later.",
"type": "server_error"
}
}
Autorisierung
string
erforderlich
Alle Anfragen erfordern eine Bearer-Token-Authentifizierung.Besuchen Sie die API-Key-Verwaltungsseite, um Ihren API-Key zu erhalten, und fügen Sie ihn dann dem Request-Header hinzu:
Authorization: Bearer YOUR_API_KEY
Verfügbare Modelle
| Modell | Beschreibung | Max. Auflösung (Text-zu-Bild) | Max. Auflösung (Bearbeitung / Sequenziell) | Preis |
|---|---|---|---|---|
wan2.7-image-pro | Professional Edition, bessere Details, unterstützt 4K | 4K | 2K | ¥0,50 / Bild |
wan2.7-image | Standard Edition, schnellere Generierung | 2K | 2K | ¥0,20 / Bild |
Die Abrechnung erfolgt nach erfolgreich generierte Bilder × Stückpreis. Eingaben werden nicht abgerechnet. Auflösung und Seitenverhältnis beeinflussen den Preis nicht. Fehlgeschlagene Anfragen werden nicht berechnet.
Body
string
erforderlich
Name des Bildgenerierungsmodells.
wan2.7-image-pro— Professional Edition, bis zu 4K für Text-zu-Bildwan2.7-image— Standard Edition, schneller, bis zu 2K
boolean
Standard:"false"
Legt fest, ob der Inhalt vor dem Absenden des Bildauftrags moderiert wird.
true: Prompts und Eingabebilder mitomni-moderation-latestprüfenfalseoder nicht angegeben: keine Moderationsanfrage und damit keine zusätzlichen Moderationskosten oder Verzögerung (Standard)
string
Textbeschreibung für die Bildgenerierung, bis zu 5000 Zeichen.
- Text-zu-Bild (ohne
image_urls): erforderlich - Bildbearbeitung (mit
image_urls): optional, aber empfohlen
"A flower shop with exquisite windows, beautiful wooden door, flowers on display"array<string>
Array von Eingabebild-URLs für Bearbeitung und Mehrbild-Referenzszenarien.Die Angabe dieses Feldes schaltet die Anfrage in den Bildbearbeitungsmodus.Unterstützte Formate: HTTP/HTTPS-URLs;
data:image/...;base64,... Base64Einschränkungen: Bis zu 9 Bilder; JPEG / PNG / WEBP / BMP; 240–8000 px, Seitenverhältnis 1:8 ~ 8:1; ≤ 20 MB pro BildDas Ausgabe-Seitenverhältnis entspricht automatisch dem letzten Eingabebild. Der Bearbeitungsmodus unterstützt nur bis zu 2K — 4K ist nicht verfügbar.
integer
Standard:"1"
Anzahl der zu generierenden Bilder.
- Standardmodus: 1–4 (Standard 1)
- Sequenzieller Modus (
enable_sequential: true): 1–12 (Standard 1)
Abrechnung pro erfolgreich generiertem Bild. Vorausberechnung basierend auf
n.string
Ausgabeauflösung oder Seitenverhältnis. Unterstützt drei Formate:① Auflösungsschlüsselwort (empfohlen):
1K / 2K (Standard) / 4K (nur Text-zu-Bild für wan2.7-image-pro)② Seitenverhältnis: 1:1 / 16:9 / 9:16 / 4:3 / 3:4 / 3:2 / 2:3 (standardmäßig 2K-Stufe)③ Pixelmaße: 1024x1024 oder 1024*1024string
Schlüsselwort für die Auflösungsstufe:
1K / 2K / 4K. Kann mit size (Seitenverhältnis) kombiniert werden.| Modell | Szenario | Unterstützte Stufen | Pixelbereich |
|---|---|---|---|
wan2.7-image-pro | Text-zu-Bild (nicht sequenziell) | 1K / 2K / 4K | 768×768 ~ 4096×4096 |
wan2.7-image-pro | Bearbeitung / Sequenziell | 1K / 2K | 768×768 ~ 2048×2048 |
wan2.7-image | Alle Szenarien | 1K / 2K | 768×768 ~ 2048×2048 |
string
Negativer Prompt, der zu vermeidende Elemente beschreibt. Beispiel:
"blurry, distorted, low quality"boolean
Standard:"false"
Ob ein “AI Generated”-Wasserzeichen in der unteren rechten Ecke hinzugefügt werden soll.
integer
Zufallsseed, Bereich 0–2147483647. Derselbe Seed mit identischen Parametern erzeugt visuell konsistente Ergebnisse.
boolean
Standard:"true"
Aktiviert den erweiterten Reasoning-Modus, um die Bildqualität auf Kosten einer längeren Generierungszeit zu verbessern.
Nur wirksam, wenn der sequenzielle Modus deaktiviert ist und keine Bildeingabe bereitgestellt wird.
boolean
Standard:"false"
Aktiviert den sequenziellen Bildgenerierungsmodus — generiert mehrere thematisch zusammenhängende Bilder in einer Anfrage. Ideal für Storyboards und Serien.
- Maximum
nist 12 bei Aktivierung thinking_modeundcolor_palettewerden im sequenziellen Modus ignoriertwan2.7-image-prounterstützt im sequenziellen Modus bis zu 2K (4K nicht unterstützt)
array
Begrenzungsrahmen für interaktive Bearbeitung — gibt genaue Bereiche zum Bearbeiten oder Einfügen von Inhalten an.Struktur:
[[[x1, y1, x2, y2], ...], ...]- Die Länge des äußeren Arrays muss der Länge von
image_urlsentsprechen - Übergeben Sie
[]für Bilder ohne Begrenzungsrahmen - Maximal 2 Rahmen pro Bild; Koordinaten sind absolute Pixelwerte, Ursprung (0,0) oben links
[[], [[989, 515, 1138, 681]]]array<object>
Benutzerdefiniertes Farbthema. Nur Standardmodus (nicht sequenzieller Modus).
- 3–10 Einträge (8 empfohlen); jeder Eintrag erfordert
hexundratio - Die Summe aller
ratio-Werte muss genau100.00%ergeben
[
{ "hex": "#C2D1E6", "ratio": "23.51%" },
{ "hex": "#636574", "ratio": "76.49%" }
]
Response
string
Antwortstatus. Gibt bei Erfolg
"success" zurück.array
Beispiele
Text-zu-Bild (minimal)
{
"model": "wan2.7-image-pro",
"prompt": "A flower shop with exquisite windows, beautiful wooden door, flowers on display"
}
Text-zu-Bild (mit Auflösung)
{
"model": "wan2.7-image-pro",
"prompt": "Summer beach, blue sky and white clouds, 4K ultra HD",
"size": "4K",
"thinking_mode": true
}
Text-zu-Bild (benutzerdefinierte Farbpalette)
{
"model": "wan2.7-image-pro",
"prompt": "Minimalist modern living room",
"size": "2K",
"color_palette": [
{ "hex": "#C2D1E6", "ratio": "23.51%" },
{ "hex": "#CDD8E9", "ratio": "20.13%" },
{ "hex": "#B5C8DB", "ratio": "15.88%" },
{ "hex": "#C0B5B4", "ratio": "13.27%" },
{ "hex": "#DAE0EC", "ratio": "10.11%" },
{ "hex": "#636574", "ratio": "8.93%" },
{ "hex": "#CACAD2", "ratio": "5.55%" },
{ "hex": "#CBD4E4", "ratio": "2.62%" }
]
}
Sequenzielle Bildgenerierung
{
"model": "wan2.7-image-pro",
"prompt": "Cinematic series: the same stray orange cat, consistent features. First: under cherry blossoms in spring. Second: old street shade in summer. Third: fallen leaves in autumn. Fourth: snow footprints in winter.",
"enable_sequential": true,
"n": 4,
"size": "2K"
}
Einzelbildbearbeitung
{
"model": "wan2.7-image",
"prompt": "Replace the background with a sunset scene, warm color tones",
"image_urls": ["https://example.com/portrait.jpg"],
"size": "2K"
}
Mehrbild-Referenz / Elementfusion
{
"model": "wan2.7-image-pro",
"prompt": "Apply the graffiti from image 2 onto the car in image 1",
"image_urls": [
"https://example.com/car.webp",
"https://example.com/paint.webp"
],
"size": "2K"
}
Interaktive Bearbeitung (Begrenzungsrahmen)
bbox_list entspricht 1:1 dem image_urls. Übergeben Sie [] für Bilder ohne Auswahl.
{
"model": "wan2.7-image-pro",
"prompt": "Place the alarm clock from image 1 into the selected area of image 2, blending naturally",
"image_urls": [
"https://example.com/clock.webp",
"https://example.com/desk.webp"
],
"bbox_list": [
[],
[[989, 515, 1138, 681]]
],
"size": "2K"
}
Ergebnisse abfragenDie Bildgenerierung erfolgt asynchron. Fragen Sie den Aufgabenstatus-Endpunkt mit der zurückgegebenen
task_id ab, bis status == completed.