Add Parquet dataset tiers

.claude/settings.json

@@ -0,0 +1,8 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(python inspect_tiers.py --root .)",
+      "Bash(python convert_to_parquet.py --root . --output parquet --overwrite)"
+    ]
+  }
+}

README.md

@@ -25,10 +25,10 @@ configs:
     data_files:
       - split: train
         path: "parquet/human/*.parquet"
-  - config_name: augmented
+  - config_name: human_augmented
     data_files:
       - split: train
-        path: "parquet/augmented/*.parquet"
+        path: "parquet/human_augmented/*.parquet"
   - config_name: synthetic
     default: true
     data_files:
@@ -38,15 +38,15 @@ configs:
 
 # KlaskTron
 
-KlaskTron is a Klask imitation-learning dataset with three tiers: real human play, augmented human data, and large-scale synthetic rollouts.
+KlaskTron is a Klask imitation-learning dataset with three tiers: real human play, axis-mirror-augmented human data, and large-scale synthetic rollouts.
 
 | Tier | Episodes | Steps | Source |
 | --- | ---: | ---: | --- |
-| `human` | 106 | 81,455 | reconstructed from recorded human play |
-| `augmented` | 424 | 325,820 | augmented from the human tier |
+| `human` | 111 | 80,591 | reconstructed from recorded human play |
+| `human_augmented` | 444 | 322,364 | axis-mirror augmentation of the human tier (none, x, y, xy) |
 | `synthetic` | 34,649 | 5,000,000 | generated in simulation from an expert-like policy |
 
-Total: 35,179 episodes and 5,407,275 action steps.
+Total: 35,204 episodes and 5,402,955 action steps.
 
 ## Loading Parquet
 
@@ -54,7 +54,7 @@ Total: 35,179 episodes and 5,407,275 action steps.
 from datasets import load_dataset
 
 human = load_dataset("KlaskLab/klasktron-il-benchmark", "human", split="train")
-augmented = load_dataset("KlaskLab/klasktron-il-benchmark", "augmented", split="train")
+human_augmented = load_dataset("KlaskLab/klasktron-il-benchmark", "human_augmented", split="train")
 synthetic = load_dataset("KlaskLab/klasktron-il-benchmark", "synthetic", split="train")
 ```
 
@@ -62,7 +62,7 @@ Each Parquet row is one transition:
 
 | Column | Meaning |
 | --- | --- |
-| `tier` | `human`, `augmented`, or `synthetic` |
+| `tier` | `human`, `human_augmented`, or `synthetic` |
 | `episode_id` | tier-local episode id |
 | `source_file` | original pickle file |
 | `episode_in_file` | episode index inside that pickle |
@@ -96,7 +96,7 @@ Raw pickle files live under:
 
 ```text
 human/trajectories/
-augmented/trajectories/
+human_augmented/trajectories/
 synthetic/trajectories/
 ```
 
@@ -113,10 +113,10 @@ Raw container types:
 | Tier | Container |
 | --- | --- |
 | `human` | `imitation.data.types.TrajectoryWithRew` |
-| `augmented` | `imitation.data.types.Trajectory` |
+| `human_augmented` | `imitation.data.types.Trajectory` |
 | `synthetic` | plain Python `dict` |
 
-The human and augmented pickles need a compatible Python environment with `imitation` available. The synthetic pickles only use plain dictionaries and NumPy arrays. As usual, only unpickle data you trust.
+The human and human_augmented pickles need a compatible Python environment with `imitation` available. The synthetic pickles only use plain dictionaries and NumPy arrays. As usual, only unpickle data you trust.
 
 ## Rewards
 
@@ -124,8 +124,8 @@ There is no meaningful per-step reward signal. `rew` / `rews` is an all-zero pla
 
 ## Notes
 
-- The human tier comes from recorded play that was reestimated into simulation coordinates.
-- The augmented tier extends the small human-data regime through benchmark preprocessing and augmentation.
+- The human tier comes from 111 recorded human Klask trajectories that were reestimated into simulation coordinates.
+- The human_augmented tier extends the human tier 4x by applying axis-mirror augmentation (none, x, y, xy) to each trajectory.
 - The synthetic tier reflects simulator and expert-policy assumptions.
 
 ### Why Both Formats Exist

human/metadata.json

@@ -1,10 +1,10 @@
-{
-  "tier": "human",
-  "source_format": "sim_native",
-  "episode_count": 106,
-  "step_count": 81455,
-  "frame_rate_hz": 50,
-  "num_files": 106,
-  "collection_id": "expert_trajectories_cleaned",
-  "notes": "Recorded from real human Klask play, converted into simulation-coordinate trajectories through the state-reestimation pipeline, and manually cleaned before benchmark release."
-}
+{
+  "tier": "human",
+  "source_format": "sim_native",
+  "episode_count": 111,
+  "step_count": 80591,
+  "frame_rate_hz": 50,
+  "num_files": 111,
+  "collection_id": "expert_trajectories_cleaned",
+  "notes": "Recorded from real human Klask play, converted into simulation-coordinate trajectories through the state-reestimation pipeline, and manually cleaned before benchmark release."
+}

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