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Image Manipulation

Qwen Lighting Restoration

Restore natural lighting by removing harsh shadows and light spots from images using Qwen Image Edit Plus with LoRA

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Inputs

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Execution Steps

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Overview

Qwen Lighting Restoration edits one or more images to restore more natural lighting by reducing harsh shadows, uneven illumination, and light spots using Qwen Image Edit Plus with LoRA. Use it for product photos, portraits, campaign visuals, and social assets that need cleaner lighting before review.

Use cases

  • Improve a product image with harsh shadows before testing it in an ad layout.
  • Clean up uneven lighting on a portrait or founder image.
  • Generate several lighting-restoration options from the same source image.
  • Use seed and image size controls when repeatable cleanup exploration matters.

Input tips

  • Provide one or more public image_urls that can be fetched without login.
  • Choose num_images from 1-4 when you want multiple lighting-cleanup 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 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 the Qwen Lighting Restoration model label.

Caveats

  • Image URLs must be public and reachable.
  • This AI Tool uses a fixed lighting-restoration prompt; it is not a free-form image editor.
  • Lighting cleanup can change mood, contrast, color, texture, or small visual details.
  • Generated product details, faces, logos, and text should be reviewed before use.
  • Safety filtering may block or alter requests that violate model rules.

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