alibaba/qwen-image/edit

Supports multiple image inputs and outputs, allowing for precise modification of text within images, addition, deletion, or movement of objects, alteration of subject actions, transfer of image styles, and enhancement of image details.

IMAGE-TO-IMAGEHOTNEW
Qwen-Image Edit
Beeld-naar-Beeld

Supports multiple image inputs and outputs, allowing for precise modification of text within images, addition, deletion, or movement of objects, alteration of subject actions, transfer of image styles, and enhancement of image details.

Invoer

Parameterconfiguratie laden...

Uitvoer

Inactief
Uw gegenereerde afbeeldingen verschijnen hier
Configureer parameters en klik op Uitvoeren om te beginnen met genereren

Elke uitvoering kost 0.032. Voor $10 kunt u ongeveer 312 keer uitvoeren.

Parameters

Codevoorbeeld

import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/qwen-image/edit",
    "prompt": "A beautiful landscape with mountains and lake",
    "width": 512,
    "height": 512,
    "steps": 20,
    "guidance_scale": 7.5,
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

Installeren

Installeer het vereiste pakket voor uw programmeertaal.

bash
pip install requests

Authenticatie

Alle API-verzoeken vereisen authenticatie via een API-sleutel. U kunt uw API-sleutel ophalen via het Atlas Cloud dashboard.

bash
export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP-headers

python
import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}
Bescherm uw API-sleutel

Stel uw API-sleutel nooit bloot in client-side code of openbare repositories. Gebruik in plaats daarvan omgevingsvariabelen of een backend-proxy.

Een verzoek indienen

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Een verzoek indienen

Dien een asynchroon generatieverzoek in. De API retourneert een voorspellings-ID waarmee u de status kunt controleren en het resultaat kunt ophalen.

POST/api/v1/model/generateImage

Verzoekinhoud

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "alibaba/qwen-image/edit",
    "input": {
        "prompt": "A beautiful landscape with mountains and lake"
    }
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")

Antwoord

{
  "id": "pred_abc123",
  "status": "processing",
  "model": "model-name",
  "created_at": "2025-01-01T00:00:00Z"
}

Status controleren

Bevraag het voorspellings-eindpunt om de huidige status van uw verzoek te controleren.

GET/api/v1/model/prediction/{prediction_id}

Polling-voorbeeld

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Statuswaarden

processingHet verzoek wordt nog verwerkt.
completedDe generatie is voltooid. Resultaten zijn beschikbaar.
succeededDe generatie is geslaagd. Resultaten zijn beschikbaar.
failedDe generatie is mislukt. Controleer het foutveld.

Voltooid antwoord

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Bestanden uploaden

Upload bestanden naar Atlas Cloud opslag en ontvang een URL die u kunt gebruiken in uw API-verzoeken. Gebruik multipart/form-data om te uploaden.

POST/api/v1/model/uploadMedia

Upload-voorbeeld

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Antwoord

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Invoer-Schema

De volgende parameters worden geaccepteerd in de verzoekinhoud.

Totaal: 0Vereist: 0Optioneel: 0

Geen parameters beschikbaar.

Voorbeeld verzoekinhoud

json
{
  "model": "alibaba/qwen-image/edit"
}

Uitvoer-Schema

De API retourneert een voorspellingsantwoord met de gegenereerde uitvoer-URL's.

idstringrequired
Unique identifier for the prediction.
statusstringrequired
Current status of the prediction.
processingcompletedsucceededfailed
modelstringrequired
The model used for generation.
outputsarray[string]
Array of output URLs. Available when status is "completed".
errorstring
Error message if status is "failed".
metricsobject
Performance metrics.
predict_timenumber
Time taken for image generation in seconds.
created_atstringrequired
ISO 8601 timestamp when the prediction was created.
Format: date-time
completed_atstring
ISO 8601 timestamp when the prediction was completed.
Format: date-time

Voorbeeldantwoord

json
{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integreert meer dan 300 AI-modellen rechtstreeks in uw AI-codeerassistent. Eén commando om te installeren, gebruik daarna natuurlijke taal om afbeeldingen, video's te genereren en te chatten met LLMs.

Ondersteunde clients

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ ondersteunde clients

Installeren

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

API-sleutel instellen

Haal uw API-sleutel op via het Atlas Cloud dashboard en stel deze in als omgevingsvariabele.

bash
export ATLASCLOUD_API_KEY="your-api-key-here"

Mogelijkheden

Eenmaal geïnstalleerd kunt u natuurlijke taal gebruiken in uw AI-assistent om toegang te krijgen tot alle Atlas Cloud modellen.

BeeldgeneratieGenereer afbeeldingen met modellen zoals Nano Banana 2, Z-Image en meer.
VideocreatieMaak video's van tekst of afbeeldingen met Kling, Vidu, Veo, enz.
LLM-chatChat met Qwen, DeepSeek en andere grote taalmodellen.
Media uploadenUpload lokale bestanden voor beeldbewerking en afbeelding-naar-video workflows.

MCP-server

De Atlas Cloud MCP-server verbindt uw IDE met meer dan 300 AI-modellen via het Model Context Protocol. Werkt met elke MCP-compatibele client.

Ondersteunde clients

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ ondersteunde clients

Installeren

bash
npx -y atlascloud-mcp

Configuratie

Voeg de volgende configuratie toe aan het MCP-instellingenbestand van uw IDE.

json
{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Beschikbare tools

atlas_generate_imageGenereer afbeeldingen op basis van tekstprompts.
atlas_generate_videoMaak video's van tekst of afbeeldingen.
atlas_chatChat met grote taalmodellen.
atlas_list_modelsBlader door meer dan 300 beschikbare AI-modellen.
atlas_quick_generateContentcreatie in één stap met automatische modelselectie.
atlas_upload_mediaUpload lokale bestanden voor API-workflows.

API Schema

Schema niet beschikbaar

Inloggen om aanvraaggeschiedenis te bekijken

U moet ingelogd zijn om toegang te krijgen tot uw modelaanvraaggeschiedenis.

Inloggen

Alibaba Qwen-Image Edit

An advanced image editing model from Alibaba Cloud, offering precise control and high-quality results. Qwen-Image Edit is designed to handle common editing tasks, allowing users to modify images with natural language prompts. It supports single-image editing and multi-image blending.

Overview

  • Purpose: Perform image edits using text instructions.
  • Core Capability: Supports single-image editing and multi-image blending.
  • Foundation: Powered by Alibaba's advanced multi-modal generative AI technology.
  • Typical Output: High-quality edited image (1 per request) that blends changes with the original content.
  • Use Cases: Social media content adjustment, basic photo retouching, and creative experimentation.

Key Features

  • Multi-image Blending:
    • Example: Combine a girl from Image 1, wearing a skirt from Image 2, sitting in a pose from Image 3.
    • Example: Combine a girl from Image 1, a necklace from Image 2, and a bag from Image 3.
  • Single-image Editing:
    • Generate depth-compliant images.
    • Replace text (e.g., "HEALTH INSURANCE" -> "明天会更好").
    • Replace shirt color.
    • Change background (e.g., to Antarctica).
  • High Fidelity: Preserves the quality of the original image while applying edits.
  • Smart Inpainting: Fills gaps or replaces objects based on the surrounding context.

Designed For

  • Content Creators: Quickly adjust visuals for social platforms.
  • General Users: Easily modify personal photos or creative projects.
  • Developers: Integrate image editing capabilities into applications.

Input Requirements

To achieve the best results, follow these guidelines:

Inputs

  • Structure:
    • messages array with role: user.
    • content array: 1-3 images ({"image": "..."}) + 1 text instruction ({"text": "..."}).
  • Image Format: JPG, JPEG, PNG, BMP, TIFF, WEBP, GIF (first frame).
  • Resolution: Recommended 384px - 3072px.
  • Size Limit: Max 10MB per image.
  • Text Limit: Max 800 characters.

Parameters

  • n: Number of output images. Fixed at 1.
  • negative_prompt: Description of content to exclude (max 500 characters).
  • size: Not customizable. Output resolution maintains the aspect ratio of the input (or last input image), typically around 1024x1024.
  • watermark: Boolean to add "Qwen-Image" watermark. Default is false.
  • seed: Integer for reproducibility.

Pricing

  • Billing Logic: Pay-as-you-go based on the number of successful output images.
  • Tier: Standard tier offering a balance of performance and cost.

Limitations & FAQ

  • Conversation: Does not support multi-turn conversation (single turn only).
  • Languages: Chinese and English are supported; other languages are unverified.
  • Aspect Ratio: Output follows the aspect ratio of the input image (or the last image if multiple are provided).
  • Resolution: Does not support custom output resolution.
  • Output Quantity: Only supports generating 1 image per request.

Version

  • Model: Alibaba Qwen-Image Edit
  • Family: Qwen-Image
  • Technical Context: Standard version with essential editing capabilities.

Begin met 300+ Modellen,

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