Update README for train/eval layout
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README.md
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@@ -10,7 +10,9 @@ Human demonstration videos and simulated robot trajectories for 10 manipulation
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```
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human_demos/
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{
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depths.h5
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egocentric.mp4 front.mp4 left.mp4 right.mp4
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robot_trajectories/
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## Episode counts
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| `bowl_in_plate` | 100 | 100 | 100 | 100 |
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| `close_drawer` | 100 | 100 | 50 | 100 |
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| `empty_basket` | 100 | 100 | 100 | 100 |
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| `open_lid` | 100 | 100 | 100 | 100 |
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| `pick_cube` | 100 | 100 | 110 | 100 |
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| `press_toaster` | 100 | 100 | 100 | 100 |
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| `push_cube` | 100 | 100 | 100 | 100 |
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| `stack_cups` | 100 | 100 | 100 | 100 |
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| `toys_in_basket` | 100 | 100 | 100 | 100 |
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| `toys_in_drawer` | 100 | 100 | 100 (as `toy_drawer_close`) | 100 |
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`human_demos/pose_defined/push_cube` contains the same recordings as
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`human_demos/no_distraction/push_cube`.
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`
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## Train and evaluation split
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are used for
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## Human demonstrations
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@@ -74,7 +79,7 @@ Depth is compressed with Bitshuffle and zstd, so `hdf5plugin` must be imported b
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import hdf5plugin # registers the compression filter
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import h5py
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with h5py.File("human_demos/no_distraction/push_cube/0000/depths.h5", "r") as f:
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cam = f["front"]
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depth_m = cam["depth/frames"][0] * cam["depth/depth_scale"][()]
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timestamps = cam["timestamps"][()]
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```
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human_demos/
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train/{no_distraction,with_distraction,pose_defined}/<task>/<episode>/
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eval/{no_distraction,with_distraction}/<task>/<episode>/
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excluded_human_demos_with_distraction/<task>/<episode>/
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depths.h5
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egocentric.mp4 front.mp4 left.mp4 right.mp4
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robot_trajectories/
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## Episode counts
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Human demos, per task:
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| Task | `train/no_distraction` | `train/with_distraction` | `train/pose_defined` | `eval/no_distraction` | `eval/with_distraction` |
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| `bowl_in_plate` | 80 | 80 | 100 | 20 | 20 |
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| `close_drawer` | 80 | 80 | 50 | 20 | 20 |
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| `empty_basket` | 80 | 80 | 100 | 20 | 20 |
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| `open_lid` | 80 | 80 | 100 | 20 | 20 |
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| `pick_cube` | 80 | 80 | 110 | 20 | 20 |
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| `press_toaster` | 80 | 80 | 100 | 20 | 20 |
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| `push_cube` | 80 | 80 | 100 | 20 | 20 |
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| `stack_cups` | 80 | 80 | 100 | 20 | 20 |
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| `toys_in_basket` | 80 | 80 | 100 | 20 | 20 |
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| `toys_in_drawer` | 80 | 80 | 100 (as `toy_drawer_close`) | 20 | 20 |
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Robot trajectories: 100 episodes per task in each of `no_distraction` and `with_distraction`.
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## Train and evaluation split
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In `no_distraction` and `with_distraction`, episodes `0000`-`0079` are in `train` and episodes
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`0080`-`0099` are in `eval`. All `pose_defined` demos are used for training only.
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`human_demos/train/pose_defined/push_cube` contains the same recordings as `no_distraction/push_cube`,
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including the episodes in `eval/no_distraction/push_cube`.
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`human_demos/excluded_human_demos_with_distraction` holds 20 further with-distraction episodes
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per task (200 in total), numbered `0100`-`0119`. They are not part of `train` or `eval`.
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## Human demonstrations
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import hdf5plugin # registers the compression filter
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import h5py
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with h5py.File("human_demos/train/no_distraction/push_cube/0000/depths.h5", "r") as f:
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cam = f["front"]
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depth_m = cam["depth/frames"][0] * cam["depth/depth_scale"][()]
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timestamps = cam["timestamps"][()]
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