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What is krea2-research?

wlejon/krea2-research — explained in plain English

Analysis updated 2026-05-18

0PythonAudience · researcherComplexity · 4/5Setup · hard

In one sentence

A research lab and Gradio interface for exploring real-time image controls inside the Krea 2 AI image model, documented with findings and demo sweeps.

Mindmap

mindmap
  root((krea2 research))
    Findings
      PLAN.md
      FINDINGS.md
    Gradio lab
      Perceptual axis sliders
      Literal vs stylized dial
      Custom axis slots
    Sweep tool
      Full range gif render
      Per axis exploration
    Spatial tab
      Region masked control
    Audience
      AI researchers
      Model interpretability enthusiasts

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Explore how adjusting internal sliders changes a Krea 2 generated image in real time.

USE CASE 2

Read the findings document to understand which image controls behave predictably.

USE CASE 3

Generate a gif sweep showing the full effect of a single slider across its range.

USE CASE 4

Create a custom control slider from a pair of text descriptions or images.

What is it built with?

PythonGradioCUDA

How does it compare?

wlejon/krea2-research0xallam/my-recipe0xhassaan/nn-from-scratch
Stars00
LanguagePythonPythonPython
Last pushed2022-11-22
MaintenanceDormant
Setup difficultyhardmoderatemoderate
Complexity4/52/54/5
Audienceresearchergeneraldeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Requires a CUDA-capable GPU and the frozen Krea-2-Turbo engine already set up to run the Gradio lab.

So what is it?

This repository is a research artifact rather than a finished product. It documents an investigation into Krea 2, an AI image generation model, looking for internal controls that can be adjusted in real time to change the resulting image within a couple of seconds, instead of having to write a new text prompt and regenerate from scratch. The full write up of what was tried and what was found lives in two documents in the repository, one covering the plan and one covering the findings. To explore this, the project includes a small local web interface built with Gradio, a Python tool for building quick interactive demos. It gives you sliders for things like composition, color, lighting, rendering style, and mood, plus a dial to shift an image between a literal, photographic look and a more stylized, painterly one. There are also slots for creating your own custom sliders from a pair of text descriptions or a pair of images. Every slider updates the generated image when you let go of it, usually within a few seconds at a small image size. A separate tab lets you apply one of these adjustments to just part of an image rather than the whole thing, using a mask. Each slider also has a small button that automatically sweeps it across its entire range, regenerating the image at each step and stitching the results into an animated gif so you can see the full effect of that control at a glance. The repository includes a few example videos and gif sweeps generated this way. Overall, this is a lab notebook for people studying how these image models can be steered, rather than a tool meant for general end users.

Copy-paste prompts

Prompt 1
Summarize the findings in FINDINGS.md about which control surfaces work best in Krea 2.
Prompt 2
Walk me through running the Gradio UI in this repo and generating a sweep gif for one axis.
Prompt 3
Explain what the Spatial tab does and how the per-region mask works.
Prompt 4
Help me understand the difference between the literal and stylized dial and the AdaLN detail dials.

Frequently asked questions

What is krea2-research?

A research lab and Gradio interface for exploring real-time image controls inside the Krea 2 AI image model, documented with findings and demo sweeps.

What language is krea2-research written in?

Mainly Python. The stack also includes Python, Gradio, CUDA.

How hard is krea2-research to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is krea2-research for?

Mainly researcher.

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