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QwenEdit2509-FlatLogColor

10

45

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1

Updated: Nov 20, 2025

conceptflatcolorqwen

Verified:

SafeTensor

Type

LoRA

Stats

45

0

Reviews

Published

Nov 20, 2025

Base Model

Qwen

Usage Tips

Strength: 1

Trigger Words

flatcolor Desaturate the image and lower the contrast to create a flat, ungraded look similar to a camera's log profile. Preserve details in the highlights and shadows.

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AutoV2
532B7090B7
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TL_'s Avatar

TL_

QwenEdit2509-FlatLogColor is a specialized LoRA designed to bridge the gap between AI image generation and professional creative workflows.

A common challenge for professionals using AI-generated content is that most images are created as "finished" products. They come with fully applied color, contrast, and saturation, much like a JPEG straight out of a consumer camera. This leaves little room for creative manipulation, such as color grading, which is a crucial step in film, photography, and multimedia production.

This model solves that problem. It takes a standard AI-generated image and converts it into a FLAT or LOG color profile.

What is a FLAT/LOG Profile?

In professional photography and videography, cameras can capture images in a "raw" or "logarithmic" (LOG) format. Instead of producing a vibrant, high-contrast image ready for immediate sharing, a LOG profile preserves the maximum amount of detail captured by the camera's sensor.

It achieves this by creating an image that appears:

  • Low-contrast: The difference between light and dark areas is reduced.

  • Desaturated: The colors are muted and less vibrant.

  • Detail-rich: Information in the deepest shadows and brightest highlights is retained, not "crushed" to pure black or "clipped" to pure white. See this example from youtuber Evan Schneider

image

This "flat" image is the perfect digital negative, providing a flexible foundation for colorists and editors to apply their own creative vision and ensure consistency across different shots and sources. This LoRA brings that same professional capability to your AI-generated content.


To see a breakdown of the analysis on this trained LORA, see this Civitai article here:
https://civitai.com/articles/22717