Practical ways to resolve images that don't match their descriptions
The following step-by-step optimization scheme can be used when encountering AI-generated images that do not match expectations:
- Enhanced description specificity: Adopt the structure of "Subject + Scene + Style + Details", e.g. change "A cat" to "Orange tabby cat under a purple starry sky, cyberpunk style, with neon light effects".
- Add style keywords: Specify stylistic terms such as "oil painting", "pixel art", or "pencil sketch" in the description.
- Adjustment using qualifiers: Control generation details by adding modifiers such as "minimalist", "highly detailed" or "8K resolution".
- Iterative Optimization Process: first generate base image → analyze deviation points → add targeted adjustments (e.g., "more blue tones") in second round of descriptions
If multiple adjustments are still unsatisfactory, try the following advanced program:
1. Refer to the community case study on Discord's #showcase channel to learn the success description template
2. Combined use of negative descriptions, such as "no shadows" or "non-realistic" to exclude unwanted elements
This answer comes from the articleCraiyon: a free tool for generating AI art imagesThe
May not be reproduced without permission:AI productivity tools " How to solve the problem that Craiyon generates images that do not match the expected description?
