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MODEL ZOO IMPLEMENTATION KNOWLEDGE BASE

OVERVIEW

This directory is the algorithm zoo. Each file usually contributes one BaseModel subclass selected by model_cfg.model.

WHERE TO LOOK

Task Location Notes
Baseline pattern baseline.py minimal template for silhouette models
Scoliosis pipeline sconet.py label remapping + screening-specific head
Large-model fusion BiggerGait_DINOv2.py, BigGait.py external pretrained dependencies
Diffusion/noise handling denoisinggait.py, diffgait_utils/ high-complexity flow/feature fusion
Skeleton variants skeletongait++.py, gaitgraph1.py, gaitgraph2.py pose-map/graph assumptions

CONVENTIONS

  • Most models follow: preprocess input -> backbone -> temporal pooling -> horizontal pooling -> neck/head -> contract dict.
  • Input modality assumptions differ by model (silhouette / RGB / pose / multimodal); config and preprocess script must match.
  • Many models rely on utilities from modeling/modules.py; shared changes there are high blast-radius.

ANTI-PATTERNS

  • Dont mix modality assumptions silently (e.g., pose tensor layout vs silhouette layout).
  • Dont rename classes without updating model_cfg.model references in configs.
  • Dont treat BigGait_utils/diffgait_utils as generic utilities; they are model-family specific.