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const axios = require('axios');
const fs = require('fs');
const path = require('path');
async function toB64(imgPath) {
const data = fs.readFileSync(path.resolve(imgPath));
return Buffer.from(data).toString('base64');
}
const api_key = "YOUR API-KEY";
const url = "https://api.segmind.com/v1/qwen-image-edit";
const data = {
"image": "toB64('https://segmind-resources.s3.amazonaws.com/input/32e99b1e-d3b6-4a59-a588-9cfae0675b9d-qwen_display.png')",
"prompt": "replace the text on sign board with 'STOP Qwen Image Edit is on Segmind'",
"negative_prompt": "low quality, noise, extra elements",
"steps": 30,
"guidance": 3.5,
"seed": 760941192,
"image_format": "png",
"quality": 90,
"base64": false
};
(async function() {
try {
const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } });
console.log(response.data);
} catch (error) {
console.error('Error:', error.response.data);
}
})();Attributes
Input Image URL or file reference.
Describes what to edit in the image
Avoid specific traits. 'Avoid noise' removes unwanted noise.
Number of steps for generating the image
min : 1,
max : 100
Influence of prompt. Use 4 for stronger control.
min : 1,
max : 25
Seed stabilizes output. Try -1 for randomness.
min : -1,
max : 999999999999999
Choose format for image storage. 'jpeg' for compact files, 'png' for clarity.
Allowed values:
Sets image detail level. Use 80 for web content, 100 for high-quality prints.
min : 10,
max : 100
Outputs base64. True if image as text needed.
To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.
Qwen Image edit - The latest Image Editing Model
Last Updated 19 Aug 2025 By Segmind Team
What is Qwen-Image-Edit?
It is the latest image editing model, built upon the original image generation of Qwen Image , this extends all the capabilities of the original model including high quality text rendering to editing related tasks with precise control even over text elements. It can be used for a range of use cases including adding, removing or changing existing elements of an image while maintaining consistency. This model can also be used to swap styles and update on-image text. Qwen Image Edit handles both high-level semantic transformations and pixel-perfect local tweaks.
Key Features
- Text Editing: Edit text (supports English and Chinese) in images; maintains original font, size, and style.
- Semantic Editing: Modify objects or image context. Example: change weather, swap art styles, reposition elements.
- Appearance Editing: Precisely adjust local pixels (color, texture, shape) without altering the rest of the scene.
Best Use Cases
- UI/UX Mockups: Update on-screen text, switch languages, refine interface elements.
- E-commerce & Packaging: Swap product labels, rotate packaging, adapt promotional banners for different markets.
- Creative IP Generation: Generate brand-consistent assets by transferring painting or photography styles.
Prompt Tips and Output Quality
- Clear Semantic Prompts
E.g., “Rotate the car 30° clockwise,” or “Change background to night sky.” - Negative Prompting
Usenegative_prompt="low quality, noise, extra elements"to suppress unwanted artifacts. - Adjust Steps
Defaultsteps=40; increase to 70 for ultra-detailed results, or lower for faster iterations. - Tweak Guidance Scale
Defaultguidance_scale=4; raise to 8 for stronger adherence to the prompt. - Set Seed
Useseed=760941192for reproducible outputs, orseed=-1for full randomness. - High-Resolution Inputs
Supply images ≥512×512 px to maximize detail and minimize artifacts.
FAQs
Q: How do I choose between semantic and appearance editing?
A: Describe high-level changes (e.g., style, position) for semantic editing. Specify local pixel tweaks (color or texture) for appearance editing.
Q: Can I edit text in both Chinese and English?
A: Yes. Qwen-Image-Edit preserves the original font, size, and style during bilingual text modifications.
Q: Which parameters most affect output quality?
A: steps, guidance_scale, and seed directly influence detail, fidelity, and reproducibility.
Q: How do I avoid unwanted elements?
A: Include a negative_prompt listing traits to exclude (e.g., “noise,” “blurriness,” “extra objects”).
Q: Is there a limit to image size?
A: For optimal performance, use images at or above 512×512 px. Larger inputs improve detail retention.
Q: What file formats are supported?
A: Standard image formats (JPEG, PNG) are fully supported via URL or direct upload.
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