Instructions to use omkarpatil/push-tape-right-dp-wrist-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use omkarpatil/push-tape-right-dp-wrist-diffusion with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Diffusion Policy β push-tape-right (wrist cameras only)
LeRobot Diffusion Policy trained on push-tape-right for the ROBOTIS FFW SG2 Rev1, using
shared-norm statistics pooled across its composition group.
Cameras
cam_left_wrist, cam_right_wrist β native resolution (both wrist cameras are 424x240).
Diffusion Policy requires every camera to share one resolution, and this robot's do not (head 376x672, wrist 424x240). The wrist-only variant is uniform as recorded; the 3-camera variant required re-encoding all views to a common size.
Composition group A
Members: push-tape-left, push-tape-right. Normalization statistics were pooled over 5,768 frames of all group members and written identically into each member's dataset:
sha256(observation.state + action, normalization fields)[:12] = 839f172565ff
Only compose models reporting this same hash.
Note on cross-architecture composition: the GR00T policies for these same tasks share
the same pooled statistics file but consume different fields β GR00T uses q01/q99
min-max (use_percentiles=True), Diffusion Policy uses min/max (STATE/ACTION
default to MIN_MAX). So diffusion composes with diffusion and GR00T with GR00T, but
not across the two.
Training β LeRobot defaults
| Policy | diffusion (LeRobot 0.6.1, ROBOTIS lerobot-cyclo fork) |
| Steps | 100 000 |
| Batch size | 8 |
| Optimizer | lr 1e-4, betas (0.95, 0.999), weight decay 1e-6 |
| Noise scheduler | DDPM |
| Params | 274472400 |
| Data rate | 15 fps |
| Final train loss | 0.003 |
Dataset in LeRobot v3.0 format (converted from v2.1, with pooled statistics restored after conversion β the v2.1βv3.0 converter regenerates stats and would otherwise have replaced the group-pooled values with per-task ones).
- Downloads last month
- 36