Back to Nodes
Qwen Image

Qwen Image

Official

An advanced image generation model that excels at rendering complex text within images and offers precise image editing capabilities.

Nodespell AI
AI / Image / Alibaba

An advanced image generation model that excels at rendering complex text within images and offers precise image editing capabilities.

Model Overview

A sophisticated image generation and editing foundation model from the Qwen series, showcasing significant advancements in complex text rendering and precise image manipulation.

Best At

  • High-fidelity text rendering: Excels at integrating alphabetic and logographic text into images with remarkable accuracy in typography, layout, and context.
  • Versatile image generation: Capable of producing a wide range of artistic styles, from photorealism to anime and minimalist designs.
  • Advanced image editing: Supports complex operations like style transfer, object insertion/removal, detail enhancement, text editing within images, and human pose manipulation.
  • Image understanding tasks: Can perform object detection, semantic segmentation, depth/edge estimation, novel view synthesis, and super-resolution.

Limitations / Not Good At

  • While not explicitly stated, complex image editing tasks may require very detailed and specific prompts for optimal results.
  • Performance on extremely long or convoluted text within images might require careful prompt engineering.

Ideal Use Cases

  • Creating marketing materials with integrated slogans or product names.
  • Generating illustrations for articles that require specific textual elements.
  • Designing social media graphics with layered text and imagery.
  • Prototyping UI elements or infographics.
  • Artistic exploration across various styles with text integration.
  • Advanced photo editing and manipulation.

Input & Output Format

  • Input: Text prompts, optional input images (for img2img pipeline), LoRA weights, and various control parameters (e.g., aspect_ratio, image_size, num_inference_steps, guidance, seed).
  • Output: An array of URIs pointing to the generated image files.

Performance Notes

  • Offers a go_fast option for quicker predictions with optimizations.
  • num_inference_steps can be adjusted: lower steps produce faster results with potentially lower quality, while higher steps yield better quality at the cost of speed.
Inputs (1)

Prompt

String

Prompt for generated image

Multi InputMin: 0Max: 100
Parameters (10)

Seed

Number

Random seed. Set for reproducible generation

Default: -1

Prompt

String

Prompt for generated image

Default:

Go Fast

Boolean

Run faster predictions with additional optimizations.

Default: true

Guidance

Number

Guidance for generated image. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5

Default: 4

Aspect Ratio

String

Aspect ratio for the generated image

Default: 16:9

Output Format

String

Format of the output images

Default: webp

Enhance Prompt

Boolean

Enhance the prompt with positive magic.

Default: false

Output Quality

Number

Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

Default: 80

Num Inference Steps

Number

Number of denoising steps. Recommended range is 28-50, and lower number of steps produce lower quality outputs, faster.

Default: 50

Disable Safety Checker

Boolean

Disable safety checker for generated images.

Default: false
Outputs (1)

Output

Inferred

Output

Used in Snippets (1)

Fashion Print Design
Snippet
# Fashion Print Design ## Overview This Fashion Print Design workflow turns your fabric motifs and reference photos into production-ready dress visuals and motion previews. It combines multiple image models to apply prints to cotton garments with realistic studio lighting and consistent color. ## What You'll Build - High‑resolution **1:1 garment mockups** with your print applied across the full dress. - 2K **fabric texture tiles** suitable for textile sampling or e‑commerce. - Short **5‑second fashion clips** that showcase the dress and print in motion. - Iterative concept boards that stay aligned to your fashion print moodboard. ## How It Works 1. A moodboard image input (e.g., `fashion_print_moodboard`) anchors the overall style, palette, and motif direction. 2. Multiple **Seedream 4** nodes (25 total, key ones like `seedream9`, `seedream11`, `seedream13`) generate 2048×2048, 2K print swatches and fabric renders at a **1:1 aspect ratio**, optimized for color consistency where Nano Banana struggles with flower tones. 3. **googleNanoBanana** nodes (7 total, JPG output, 1:1) support fast ideation passes, while sticky notes guide prompts such as changing the dress material to match the reference and ensuring the print pattern wraps cleanly across the garment. 4. A dedicated instruction note drives photorealism: applying the print texture to **cotton fabric** under clear, realistic studio lighting. 5. **qwenImageEditPlus** and **qwenImage** refine fit, fabric details, and print placement, while **reveCreate** and `hailuo23Fast` assist with stylistic variations and composition. 6. **kling25ImageToVideo** nodes transform key frames into **5‑second videos** (CFG scale 0.5, negative prompt to avoid blur, distortion, and low quality), giving you animated fashion previews. ## Best For - Fashion and textile designers developing new print collections. - Apparel brands needing fast dress and fabric mockups from reference art. - Surface pattern designers pitching prints to clothing labels. - E‑commerce teams creating on‑model visuals and motion previews without a full photoshoot. - Creative studios prototyping AI‑assisted fashion print design workflows. Try this Fashion Print Design snippet in Nodespell to turn flat print references into polished, motion‑ready fashion visuals in a few guided steps.
NTNodespell Team
Recent
Nodespell

Nodespell

📍 London

Building the future. Join us!

Type

Node

Status

Official

Package

Nodespell AI

Category

AI / Image / Alibaba

Input

TextImage

Output

Image

Keywords (11)

Image GenerationImage EditText GenerationStructured OutputAspect ControlResolution Control
Use in Workflow