For the problem of inaccurate AI-generated results, Malette Art workflows provide multi-level optimization strategies:
- Cue word engineering::
- Adopting the structure of "subject + environment + style + details" (e.g. "young girl in Chinese dress under cherry blossom tree, cyberpunk style, 4K HD")
- Using the platform's built-in word association function (typing "sunset" automatically suggests related matching words)
- parameterization::
- Basic settings: resolution recommended 768 x 1024 or higher to avoid loss of detail
- Advanced Options: CFG to 7-12 Balancing Creativity and Controllability
- Seed fixation function: fine-tuning of fixed SEED values for satisfactory results
- Iterative optimization::
- Multiple rounds of corrections using the Graph to Graph workflow
- Combined with the Mask tool to locally redraw the problem area
Advanced Tips: Save parameter combinations of successful cases and create a library of personal style templates for batch processing.
This answer comes from the articleMalette Art: an AI-based authoring platform for workflow-generated images and videosThe
May not be reproduced without permission:AI productivity tools " How to improve the match between AI-generated images and the desired effect?
