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norm_stats dict |
|---|
{
"state": {
"mean": [
-0.6252827048301697,
0.05113311856985092,
0.22688305377960205,
0.46718865633010864,
-0.9767469763755798,
1.7550376653671265,
3.2193922996520996,
-1.5446810722351074,
-2.239225149154663,
0.1927366852760315,
1.6434968709945679,... |
Block Into Box PI0.5 Dataset
LeRobot v2.1 training dataset for PI0.5 LoRA fine-tuning.
Contents
- 36 source Dataset v3 episodes recorded at 30 Hz
- 23,060 source frames
- 128 continuity-safe LeRobot episodes at 15 Hz
- 11,541 converted frames
- 256 video files and 128 Parquet files
- 9,749 valid anchors with a complete 15-action horizon
The conversion split discontinuous source trajectories into independent
episodes and dropped five segments that were too short for training. The
repository also includes the validated project transforms, normalization
statistics, and a SenseCore four-GPU launcher under training_bundle/.
Validation
- all metadata, state, action, and video contracts passed
- 384 sampled frames decoded with the expected RGB and tensor dimensions
- all sampled numeric values were finite
- one-step PI0.5 LoRA smoke training completed with finite loss and gradient norm
This dataset contains real robot camera recordings and is publicly accessible. Review privacy and redistribution requirements before adding new recordings.
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