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Image Manipulation

Qwen Shirt Design

Put designs, graphics, or logos on people's shirts using Qwen Image Edit Plus with LoRA

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Inputs

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Execution Steps

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Overview

Qwen Shirt Design applies a design, graphic, or logo image onto a shirt worn by a person in another image using Qwen Image Edit Plus with LoRA. Use it for apparel mockups, merch concepts, influencer creative, and campaign visuals when you need to preview a shirt design on a person.

Use cases

  • Preview a logo or graphic on a shirt before producing merch or campaign samples.
  • Create apparel mockups for landing pages, ads, or social concepts.
  • Test several shirt-design placements from the same person and design images.
  • Use seed and image size controls when repeatable apparel exploration matters.

Input tips

  • Provide exactly two public image_urls: first the person wearing a shirt, second the design or logo image.
  • Use the prompt to describe how the design should appear on the shirt.
  • Choose num_images from 1-4 when you want multiple apparel options.
  • Use image_size presets or custom dimensions only when the output canvas matters.
  • Set output_format to png, jpeg, or webp based on the final handoff need.
  • Adjust lora_scale, guidance_scale, inference steps, negative_prompt, safety checker, or seed only when needed.

Expected output

The AI Tool returns one or more edited images with downloadable URLs and optional content type, file name, file size, width, and height, plus the seed used and cost metadata. The shared image output view renders a single image or gallery and shows seed, image count, and model metadata.

Caveats

  • Both image URLs must be public and reachable.
  • The first image should clearly show a person wearing a shirt; the second should clearly show the design or logo.
  • Design placement, scale, folds, fabric texture, and shirt boundaries may vary across outputs.
  • Generated logos, text, faces, and apparel details should be reviewed before use.
  • Safety filtering may block or alter requests that violate model rules.

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