Three core strategies for AI mapping quality control
Problems such as hand distortion and logical errors that tend to occur when generating images from text can be effectively prevented with MyEdit's intelligent adjustment system:
- Cue word engineering - Adopt the 'Layered Description Method': ① main structure (e.g. 'man in a suit') ② detail constraints ('hands in pockets, right hand wearing a watch') ③ style constraints ('realistic style, Octane rendering') ④ negative hints (enter 'extra fingers, mutated hands' to exclude common mistakes) ') ③ style constraints ('realistic style, Octane rendering') ④ negative hints (enter 'extra fingers, mutated hands' to rule out common mistakes)
- parameter optimization - Key setting combinations: ①Steps value recommended 35-50 ②CFG Scale kept between 7-9 ③Enable 'HD Repair' option ④Seed value fixed and then fine-tuned (for batch generation)
- post-processing amendment - Modify problem areas using the 'Local Redraw' function, supplemented by the 'Detail Enhancement' tool to enhance textures (especially for clothing folds and material representation).
Advanced Solution: Paid users can train customized models and upload 10-20 reference drawings to build a style library, which significantly improves the accuracy of generating specific domains (e.g. industrial design drawings).
This answer comes from the articleMyEdit: free online AI image and audio editing toolThe
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