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README.md
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---
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license: mit
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library_name: pytorch
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---
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# Push-T diffusion policy checkpoints
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Two Push-T diffusion policy checkpoints with a minimal inference script.
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## Files
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- `original.ckpt` — original checkpoint
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- `edited.pt` — edited checkpoint
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- `stats_sfp.npz` — normalization stats (obs / action min/max)
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- `inference.py` — inference script
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## Quick start
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```bash
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pip install torch diffusers pygame pymunk shapely scikit-image imageio gym numpy
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git clone https://github.com/columbia-ai-robotics/streaming_flow_policy.git
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python inference.py --ckpt original.ckpt --stats stats_sfp.npz \
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--sfp-repo streaming_flow_policy/ --n-seeds 50
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python inference.py --ckpt edited.pt --stats stats_sfp.npz \
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--sfp-repo streaming_flow_policy/ --n-seeds 50 --save-mp4 rollout.mp4
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```
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Prints success rate and mode distribution; optional `--save-mp4` renders the first successful rollout.
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