Analysis updated 2026-05-18
Turn a rough or messy prompt into a cleaner one for Krea 2 or FLUX.
Build a comic story or meme with its own dedicated correction workflow.
Batch correct many prompts at once from a CSV file.
Review a generated image against your prompt in the Workbench mode.
| slasher006/image-prompt-corrector | 0-bingwu-0/live-interpreter | 010zx00x1/faresnipe | |
|---|---|---|---|
| Stars | 2 | 2 | 2 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | moderate | easy |
| Complexity | 3/5 | 2/5 | 2/5 |
| Audience | designer | general | general |
Figures from each repo's GitHub metadata at analysis time.
Requires a local LM Studio or Ollama server running with a compatible model already downloaded.
Image Prompt Corrector is a desktop application, built with Python and Qt, that helps you turn a rough or messy image generation prompt into a clean, faithful one for Krea 2 or FLUX.2 Klein 9B. Instead of calling out to a cloud AI service, it talks to a chat model you already have running locally through LM Studio or Ollama, and uses that model to clean up spelling, tighten wording, and reorganize your prompt so that details about an object stay grouped with its own attributes and actions. The app is organized into separate modes: a main Prompt Corrector for general image prompts, a Comic Story mode, a Meme Creator with its own caption and layout tools, a Model Chat mode for talking directly to your local model, and a Workbench that closes the loop by letting you review the actual generated image against your prompt. Several correction styles are offered, ranging from an Exact mode that prioritizes staying faithful to your original wording, to Explore and Improve modes that allow more creative rewriting. It includes a number of built in checks meant to catch problems before you spend time generating an image, such as verifying object counts, catching contradictions or unclear actions, translating vague or slang phrasing into concrete visual language, and turning abstract feelings into concrete visual cues like posture, lighting, and framing. There is also an optional feature for grounded web verification and reference image analysis, plus batch correction from a CSV file. To run it you need Python 3.10 or newer, the PySide6 library, and either LM Studio with its local server turned on or a running Ollama installation with a compatible model downloaded. After installing the Python dependencies in a virtual environment, you launch the GUI with a provided shell script or by running the main Python file directly. The full README is longer than what was shown.
A desktop app that uses your own local LM Studio or Ollama model to clean up and correct image generation prompts for Krea 2 or FLUX.
Mainly Python. The stack also includes Python, PySide6, LM Studio.
The README excerpt does not state license terms.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly designer.
This repo across BitVibe Labs
Verify against the repo before relying on details.