caiyiyi1998/FloodDiffusion2-Data

FloodDiffusion 2 Prepared Motion Data

Prepared representations, captions, and dataset splits used by the FloodDiffusion 2 code. Model weights are distributed separately.

Archive	Representation	Motion sequences	Extraction directory
HumanML3D-263.zip	HumanML3D, 263D	29,228	data/HumanML3D/HumanML3D263/
BABEL-263.zip	BABEL, 263D	5,341	data/BABEL/HumanML3D263/
SEED-138.zip	SEED, 138D	142,220	data/SEED/MEI138/

All archives are created with zip -0 (stored without compression). Extract them from the code repository's root directory, or install everything with:

python setup_project.py --with-data

The setup command verifies SHA-256 checksums and extracts each archive to its configured location. Use python setup_project.py --check --with-data to verify the installed files. data_manifest.json pins the archive revision and checksums; each dataset includes a release_manifest.json with per-file checksums.

data/
├── HumanML3D/HumanML3D263/
│   ├── new_joint_vecs/
│   ├── texts/
│   ├── TOKENS_20260113_233726_vae_wan_z4_2250000/
│   ├── Mean.npy, Std.npy
│   └── split and token-statistics files
├── BABEL/HumanML3D263/
│   ├── new_joint_vecs/
│   ├── texts/
│   ├── TOKENS_20260113_233726_vae_wan_z4_2250000/
│   ├── Mean.npy, Std.npy
│   └── split and token-statistics files
└── SEED/MEI138/
    ├── new_joint_vecs_uni/
    ├── texts/
    ├── Mean_uni.npy, Std_uni.npy
    └── split files

The HumanML3D and BABEL archives include tokens from the released 2,250,000-step VAE for LDF training. Caption lines preserve the caption#tokens#start#end format; BABEL frame-level annotations are placed alongside the 263D motion features in texts/. Original split memberships are retained. HumanML3D's two original non-finite test sequences, 007975 and M007975, are retained in the archive and skipped by the data loader.

Source datasets and their annotations retain their original terms. Cite the corresponding source datasets as well as FloodDiffusion 2 when using these files.