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1047290 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | # Sample data — NBA (100 scenes)
A **tiny smoke-test subset** so you can verify the code runs end-to-end before wiring up the
full datasets. **Not** for reproducing any reported number.
```
sample_data/nba/original/nba_train.npy # (100, 30, 11, 2) float32, 258 KB
sample_data/nba/original/nba_test.npy # (100, 30, 11, 2) float32, 258 KB
```
* Layout: `(scenes, frames, agents, xy)` — 30 frames @ 5 Hz = 10 past + 20 future (4.0 s),
11 agents (10 players + ball, ball = index 10), absolute court coordinates.
* Each file is the **exact first-100 prefix** of the corresponding full split
(`trajs[:100]`), which is the same slice the loaders take — so scene indices line up
with the full dataset.
* Full splits are 32 500 train / 12 500 test scenes.
## Use it
`--data_dir` must point at the **parent** of `original/` (the loader appends `original/` itself):
```bash
cd MoFlow
CUDA_VISIBLE_DEVICES=0 python fm_nba_graph_v6.py \
--cfg cfg/nba/cor_fm.yml --exp smoke \
--data_dir ../sample_data/nba \
--n_train 100 --n_test 100 \
--batch_size 8 --epochs 1 \
--fm_in_scaling --tied_noise --top_n_neighbors 5 --uncertainty_weight 0.01
```
Verified to load and collate:
```
past_traj (B, 11, 10, 6)
past_traj_original_scale (B, 11, 10, 6)
fut_traj_original_scale (B, 11, 20, 2)
```
> With only 100 scenes the model cannot learn anything meaningful — expect high ADE/FDE.
> This subset exists purely to confirm the data path, model construction, training step and
> evaluation loop all execute.
## Provenance
Derived from the NBA player-tracking (SportVU) movement data as preprocessed by prior
trajectory-prediction work. Redistributed here only as a minimal fixture for code testing;
please refer to the original data source for licensing and terms of use.
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