计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
draggan-ui【效率与协作】Guides DragGAN desktop and Gradio point-based image manipulation, checkpoint selection, masks, latent-space controls, and UI troubleshooting.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this route for desktop visualizer or Gradio tasks: launch the app, load a StyleGAN checkpoint, choose a seed, place source/target point pairs, constrain edits with masks, or debug UI/model-loading failures.
scripts/check_environment.py with the local checkout and confirm CUDA for real drag optimization.scripts/check_model_assets.py --checkpoint-dir <dir>.The bundled launch helpers are dry-run by default:
python sub-skills/draggan-ui/scripts/launch_draggan_gui.py \
--repo-root /path/to/DragGAN --checkpoint-dir checkpoints
python sub-skills/draggan-ui/scripts/launch_gradio_demo.py \
--repo-root /path/to/DragGAN --cache-dir checkpoints --listen
Pass --execute only after the printed command and preflight output are correct. The desktop helper scans existing .pkl files and supports --pkl, --capture-dir, and --browse-dir. The Gradio helper requires at least one checkpoint and supports --cache-dir, --listen, and --share.
w optimization is faster/more global; w+ is slower but usually gives finer local control.r1, and r2 affect stability and locality. Change one parameter at a time.