Push-T diffusion policy checkpoints

Two Push-T diffusion policy checkpoints with a minimal inference script.

Files

  • original.ckpt โ€” original checkpoint
  • edited.pt โ€” edited checkpoint
  • stats_sfp.npz โ€” normalization stats (obs / action min/max)
  • inference.py โ€” inference script

Quick start

pip install torch diffusers pygame pymunk shapely scikit-image imageio gym numpy
git clone https://github.com/columbia-ai-robotics/streaming_flow_policy.git

python inference.py --ckpt original.ckpt --stats stats_sfp.npz \
    --sfp-repo streaming_flow_policy/ --n-seeds 50

python inference.py --ckpt edited.pt    --stats stats_sfp.npz \
    --sfp-repo streaming_flow_policy/ --n-seeds 50 --save-mp4 rollout.mp4

Prints success rate and mode distribution; optional --save-mp4 renders the first successful rollout.

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