Add the instruments used to diagnose whether the model follows the tracks:
- track_sensitivity.py: per-checkpoint swap-sensitivity (relative velocity shift
when only the tracks / first-frame / text change) -- intrinsic input attribution.
- control_sensitivity metric: intervention-diff (generate twice, same conditioning,
different control) scored in the moving ROI, so a static background can't dilute it.
- gen_eval_artifacts.py + app_viewer.py: pre-generate counterfactual videos
(input vs re-extracted tracks, EPE heatmap) and browse them with no GPU.
- app_action.py: mouse-draw a motion and hot-swap checkpoints.
- test_controllability.py / cotracker_epe / app.py: clip_feature + minor updates.
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