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const fs = require('fs');
const path = require('path');
const main = async () => {
const response = await fetch('https://api.ai.cc/v1/images/generations', {
method: 'POST',
headers: {
Authorization: 'Bearer ',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'alibaba/qwen-image-edit',
prompt: 'Make the bubbles heart-shaped',
image: 'https://ark-doc.tos-ap-southeast-1.bytepluses.com/seededit_i2i.jpeg',
size: 'adaptive',
}),
}).then((res) => res.json());
console.log('Generation:', response);
};
main();
import requests
def main():
response = requests.post(
"https://api.ai.cc/v1/images/generations",
headers={
"Authorization": "Bearer ",
"Content-Type": "application/json",
},
json={
"prompt": "A jellyfish in the ocean",
"model": "alibaba/qwen-image-edit",
"image": "https://ark-doc.tos-ap-southeast-1.bytepluses.com/seededit_i2i.jpeg",
"size": "adaptive",
},
)
response.raise_for_status()
data = response.json()
print("Generation:", data)
if __name__ == "__main__":
main()
-
AI Playground
Test all API models in the sandbox environment before you integrate.
We provide more than 300 models to integrate into your app.
Product Detail
✨ Introducing Qwen-Image Edit by Alibaba Cloud: A groundbreaking AI model engineered for precise and adaptable image editing. It masterfully combines sophisticated image comprehension with context-aware manipulation, allowing users to modify visuals effortlessly through natural language commands or guided prompts.
This powerful tool excels across a spectrum of editing operations including object removal, smart replacement, style transfer, background adjustments, and intricate detail enhancement, all while preserving an impeccable photorealistic output. Licensed under the Apache 2.0 open-source license, Qwen-Image Edit is primed for scalable deployment in creative, commercial, and research endeavors.
🚀 Technical Specifications
- • Max Image Resolution: Up to 2048x2048 pixels for high-fidelity edits.
- • Architecture: Advanced Vision-language transformer with cross-attention mechanisms for deep understanding.
- • Licensing: Fully open-source under Apache 2.0, promoting broad accessibility.
- • Supported Languages: Comprehensive understanding of English and Chinese editing commands, with broader multilingual text processing capabilities.
📈 Performance Benchmarks
- • Object Manipulation: Achieves superior accuracy in modifying objects and attributes while preserving overall image realism.
- • Image Inpainting: Demonstrates excellent performance with minimal artifacts in restorative tasks.
- • Text-Conditioned Editing: Ensures precise alignment of edits with input textual instructions.
- • Efficiency: Optimized low-latency editing pipeline, ideal for megapixel-scale images.
- • Robustness: Highly resilient in complex scenes featuring multiple objects and layered visual elements.
💰 API Pricing
$0.04725 / image
💡 Key Capabilities
- • Intelligent Content Editing: Seamless object addition, removal, and replacement with context awareness.
- • Style & Color Transfer: Apply new styles and colors while retaining the original image context and mood.
- • Background Manipulation: Modify or entirely replace backgrounds with semantic coherence.
- • Fine Detail Refinement: Enhance minute details, including texture adjustments and shadow corrections.
- • Iterative Editing: Supports multi-turn textual interactions for progressive and refined improvements.
✅ Optimal Use Cases
- • Creative Design: Accelerate workflows for advertising, marketing, and digital art creation.
- • Photo Restoration: Services for enhancing and restoring old or damaged photographs.
- • E-commerce: Automated product visual customization for online retail.
- • Content Moderation: Tools for automated image adjustment and compliance.
- • Interactive Applications: Seamless integration into creative software and applications for real-time editing.
💻 Code Sample
<snippet data-name="image.bytedance-image-to-image" data-model="alibaba/qwen-image-edit"></snippet>↔️ Comparison with Other Leading Models
Qwen-Image Edit vs. Adobe Firefly
Qwen-Image Edit distinguishes itself as an open-source solution, offering extensive customization options for integration into diverse workflows. In contrast, Adobe Firefly is geared towards commercial users, providing a user-friendly suite of tools rich with artistic filters and proprietary brand assets.
Qwen-Image Edit vs. Stable Diffusion
Qwen-Image Edit delivers cleaner edges and fewer artifacts in object removal scenarios, alongside robust support for complex multi-turn editing. Stable Diffusion offers faster generation speeds but often with less precise editing fidelity on challenging images.
Qwen-Image Edit vs. Midjourney
Qwen-Image Edit supports high-resolution images and offers detailed textual refinement with superior open-source accessibility. Midjourney is a popular choice for artistic style exploration and rapid prototyping, though it features more limited direct editing controls.
❓ Frequently Asked Questions (FAQ)
1. What architecture underpins Qwen-Image Edit's intelligent image manipulation?
Qwen-Image Edit utilizes a conditional inpainting and outpainting architecture with deep semantic understanding. It employs cross-modal attention mechanisms to align textual instructions with visual regions, ensuring context-aware edits and structural integrity during object manipulation. Advanced segmentation capabilities enable precise localization of edit targets for seamless integration.
2. How does the model maintain visual coherence during precise object manipulation?
The model implements sophisticated object persistence tracking to preserve visual characteristics, lighting consistency, and spatial relationships. It incorporates geometric transformation networks and texture propagation algorithms, alongside shadow casting models, to ensure edited elements interact realistically within the scene, maintaining overall visual coherence.
3. What image editing tasks does Qwen-Image Edit handle most effectively?
Qwen-Image Edit excels at semantic object removal and replacement, intelligent background modification, precise attribute editing (color, texture, style), creative element addition, photo restoration, and style transfer. It particularly shines in scenarios requiring an understanding of scene semantics and object relationships for natural-looking modifications.
4. How does the model manage complex multi-step editing instructions?
The system features sequential instruction processing with memory mechanisms that track previous modifications. It supports conditional editing, progressive refinement through iterative adjustments, and advanced instruction parsing to break down complex workflows into logical steps, ensuring consistent and coherent results across multiple operations.
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