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README.md

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+---
+license: mit
+task_categories:
+- robotics
+tags:
+- LeRobot
+- robotics
+- preference-learning
+- reward-modelling
+- rlhf
+- manipulation
+- franka
+configs:
+- config_name: default
+  data_files: data/*/*.parquet
+---
+
+# setup_table — pairwise preferences on a Franka Panda
+
+Real-robot trajectories for **"set up the table"** with **human pairwise preference
+labels on multiple judgment axes**. Built for reward-model / preference-learning
+research: every label is a comparison of two trajectories on one named axis, not a
+scalar score.
+
+The trajectory data is a standard [LeRobot](https://github.com/huggingface/lerobot)
+v2.1 dataset, so it also loads directly as an imitation-learning dataset.
+
+## Contents
+
+| | |
+|---|---|
+| Episodes | **467** |
+| Frames | **197,896** (~3.7 h at 15 fps) |
+| Preference pairs | **1648** |
+| Preference labels (pair x axis) | **4432** |
+| Judgment axes | **9** |
+| Distinct instructions | **1** |
+| Cameras | `agent_view` (third-person), `wrist` — both 224x224 |
+| Robot | Franka Panda, 7-DoF joint control + gripper |
+
+### Episodes by kind
+
+| kind | episodes | frames |
+|---|---|---|
+| rollout | 316 | 133031 |
+| demo | 151 | 64865 |
+
+`demo` episodes are human teleoperated demonstrations. `rollout` episodes are policy
+rollouts recorded in preference-collection sessions; those are the ones that vary in
+quality, which is what makes the comparisons informative.
+
+## Preference labels
+
+`preferences/pairs.parquet` — one row per (pair, axis):
+
+| column | meaning |
+|---|---|
+| `pair_id` | unique id of the comparison |
+| `episode_index_a`, `episode_index_b` | index into this LeRobot dataset |
+| `episode_id_a`, `episode_id_b` | original source trajectory id |
+| `axis` | the judgment axis being compared |
+| `winner` | `A`, `B`, or `Equal` |
+| `source` | `in_session` (the two rollouts of one session) or `cross` (arbitrary pair) |
+| `source_dir`, `source_file` | provenance of the annotation |
+| `annotator` | which annotator's label set this row comes from |
+| `axis_set` | `fixed` (curated rubric reused across sessions) or `freeform` (annotator-invented axis names) |
+| `overall_score_a/b` | 1–4 Likert quality rating, where the annotator gave one (else null) |
+| `succeeded_a/b` | task-success flag recorded at collection time, where available (else null) |
+| `instruction` | instruction string logged with the comparison |
+
+`preferences/pairs.jsonl` is the same data with the axes nested per pair.
+`preferences/episodes.parquet` maps `episode_index` to the source trajectory.
+
+Winner distribution: **B** 1894, **A** 1790, **Equal** 748.
+
+### Axes
+
+| axis | labels |
+|---|---|
+| `Overall quality` | 1648 |
+| `Quality of placement of big plate` | 348 |
+| `Quality of placement of small plate` | 348 |
+| `Quality of placement of cup` | 348 |
+| `Quality of placement of cutlery` | 348 |
+| `Smoothness / carefulness` | 348 |
+| `Speed` | 348 |
+| `Formality of setup` | 348 |
+| `Damage to environment` | 348 |
+
+### Pairs by source
+
+| source | directory | axis set | pairs |
+|---|---|---|---|
+| cross | `abhijnya/cross_preferences_setup` | fixed | 800 |
+| cross | `am208/cross_preferences_setup` | fixed | 690 |
+| in_session | `am208/preferences_setup` | fixed | 158 |
+
+## Usage
+
+```python
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+ds = LeRobotDataset("MarcelTorne/setup_table_preferences")
+print(ds[0].keys())
+```
+
+```python
+# train a reward model on the pairwise labels
+import pandas as pd
+from huggingface_hub import hf_hub_download
+prefs = pd.read_parquet(hf_hub_download("MarcelTorne/setup_table_preferences", "preferences/pairs.parquet",
+                                        repo_type="dataset"))
+decisive = prefs[prefs.winner != "Equal"]           # drop ties
+overall  = decisive[decisive.axis.str.lower().str.contains("overall")]
+```
+
+Both cameras are `dtype: video`. `observation.state` is
+`[joint_0..joint_6, gripper]`, `observation.ee` is `[x, y, z, roll, pitch, yaw]`,
+and `action` is the commanded `[joint_position(7), gripper_position(1)]`.
+
+## Caveats
+
+- **Frames are h264 (crf 16), not bit-exact.** The source HDF5 held raw uint8
+  frames; re-encoding at the same 224x224 resolution shrinks the release ~100x at
+  41.8 dB PSNR (mean absolute error 1.1/255, 99th pct 7/255), measured on
+  fold_pants cloth texture. Do not expect byte-level reproduction of the originals.
+- **`Equal` is common on some axes.** Annotators used it freely; filter deliberately.
+- **`freeform` axis names are not a closed vocabulary.** They were invented per
+  session, so the same idea appears under several names (`fast` / `speed`,
+  `smooth` / `smoothness`). Normalise before aggregating across sessions.
+- **A pair can be labelled by more than one annotator.** The two annotators' cross-pair
+  sets are near-disjoint, but not perfectly; group by `pair_id` if you need unique pairs.
+- **Instructions on `rollout` episodes sometimes carry reward conditioning** (e.g.
+  `"set up the table, fast: 1.0, ..."`) because the policy that produced them was
+  reward-conditioned. The LeRobot task string is the plain instruction; the logged
+  string is kept in `preferences/episodes.parquet`.
+- **No success labels on `demo` episodes** — they are demonstrations, assumed good.
+
+## Related datasets
+
+Same robot, same collection pipeline, same schema — four tasks released together:
+
+- [`MarcelTorne/fold_pants_preferences`](https://huggingface.co/datasets/MarcelTorne/fold_pants_preferences) — fold the shorts
+- **`MarcelTorne/setup_table_preferences`** (set up the table) — this dataset
+- [`MarcelTorne/put_cube_in_bowl_preferences`](https://huggingface.co/datasets/MarcelTorne/put_cube_in_bowl_preferences) — put the cube in the bowl
+- [`MarcelTorne/plate_toast_preferences`](https://huggingface.co/datasets/MarcelTorne/plate_toast_preferences) — put the toast in the plate
+
+## License
+
+MIT.

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+  "repo_id": "MarcelTorne/setup_table_preferences",
+  "out": "/hai/scratch/marcelto/hf_export/setup_table",
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+  "frames": 197896,
+  "pairs": 1648,
+  "labels": 4432,
+  "axes": 9,
+  "dropped_pairs": 1,
+  "dropped_ids": [
+    "am208/preferences_setup/2026_05_06_17:25:50/rollout_A",
+    "am208/preferences_setup/2026_05_06_17:25:50/rollout_B"
+  ],
+  "failed": 0,
+  "skipped": 2,
+  "size_gb": 1.06
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