Problem analysis
Common problems with AI image generation include style deviations, detail distortion, etc., which need to be resolved through precise cue word engineering and parameter control.
Key Optimization Steps
- three-tier cue word structure::
- Subject description: "Silk textured hanbok" (avoid abstract words)
- Style Limit: "New Chinese Ink Style, Whiteout 40%"
- Tech specs: "8k resolution, OC renderer"
- Seed value lock: Record the seed number after generating a satisfactory sketch and keep the same seed when fine-tuning.
- Gradual generation method1. first generate the composition with 512px 2. local redrawing correction 3. finally zoom to the target resolution
Style Control Techniques
- Use the platform's built-in "style strength" slider (recommended for 60-80%)
- Upload 3-5 reference images to create a style matrix
- For commercial designs, check the "Enhanced Consistency" box.
Exception handling
When distortion occurs, use the local redraw function with the "Structure Hold" option to correct details without affecting the overall composition.
This answer comes from the articleWeights: a voice-imitation cover song and text-to-speech authoring platformThe
May not be reproduced without permission:AI productivity tools " How can I optimize the AI image generation results of the Weights platform to avoid an art style that doesn't meet expectations?
