value-model-benchmark-training-data / data /simulation /one-shot /annotations /subtasks /metadata.json
Download data/simulation/one-shot/annotations/subtasks/metadata.json from wzlllong/value-model-benchmark-training-data: direct link, hf CLI and curl.
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- Download file 6.02 kB
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https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/resolve/main/data/simulation/one-shot/annotations/subtasks/metadata.json
- Command line
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hf download hf://datasets/wzlllong/value-model-benchmark-training-data/data/simulation/one-shot/annotations/subtasks/metadata.json
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curl -L -o metadata.json https://huggingface.co/datasets/wzlllong/value-model-benchmark-training-data/resolve/main/data/simulation/one-shot/annotations/subtasks/metadata.json
6.02 kB
| { | |
| "schema_version": 1, | |
| "annotation_revision": 2, | |
| "annotation_status": "user_confirmed_release", | |
| "source_dataset": { | |
| "repo_id": "wzlllong/value-model-benchmark-training-data", | |
| "subtree": "data/simulation/one-shot", | |
| "data_revision": "43ae4845fe0461c66aa59a0ee441185d99fb05f8", | |
| "source_subtree_tree_id": "837e271aac36ea3eea72599ab5bca86db64bb025" | |
| }, | |
| "dataset": { | |
| "codebase_version": "v3.0", | |
| "fps": 25, | |
| "total_episodes": 15, | |
| "total_frames": 8080, | |
| "total_videos": 45 | |
| }, | |
| "paper": { | |
| "url": "https://arxiv.org/abs/2610.26663", | |
| "revision": "2610.26663v1", | |
| "section": "C.2 Task Descriptions and Subtask Decomposition" | |
| }, | |
| "segment_count": 58, | |
| "paper_subtask_count": 58, | |
| "annotation_target": "Active semantic subtask for each training-demonstration frame; not success, reward, or task-completion probability.", | |
| "release_scope": "Supplemental annotations for simulation One-Shot training demonstrations, separate from benchmark test-set labels described in paper Section 3.4.", | |
| "coverage_policy": "Every frame receives one printed paper subtask. Initial waiting belongs to the first subtask; terminal tail and retraction belong to the final subtask through episode end.", | |
| "interval_convention": "[start_frame, end_frame); inclusive_end_frame = end_frame - 1", | |
| "join_keys": [ | |
| "episode_index", | |
| "frame_index" | |
| ], | |
| "global_index_check": "global_index equals the LeRobot data index column", | |
| "timestamp_convention": "Nominal timestamp_seconds = frame_index / 25; associate frames by integer keys, not exact float timestamp equality.", | |
| "boundary_band": "Typically 13 frames (0.52 seconds); retained segment-specific widths are suggested adjustment bands, not measured confidence bounds or guarantees of frame-perfect precision.", | |
| "boundary_uncertain_policy": "For each segment, mark its first t frames after an internal start and last t frames before an internal end; episode outer boundaries excluded. Keep all frame labels regardless of mask.", | |
| "video_loading": { | |
| "recommended_lerobot": "0.4.2", | |
| "recommended_pyav": "15.1.0", | |
| "default_tolerance_seconds": 0.0001, | |
| "semantic_band_changes_loader_tolerance": false | |
| }, | |
| "source_training_payload_modified": false, | |
| "printed_label_policy": "Use the paper's printed S definitions, including Press By Number's S1 first button, S2 blue, S3 second button, S4 blue again; preserve the accepted order without rewriting the paper instruction.", | |
| "task_aliases": { | |
| "sweep_objects": "sweep_blocks" | |
| }, | |
| "episodes": [ | |
| { | |
| "episode_index": 0, | |
| "task_index": 0, | |
| "task_key": "arrange_largest_number", | |
| "source_task_key": "arrange_largest_number", | |
| "length": 579, | |
| "dataset_from_index": 0, | |
| "dataset_to_index": 579 | |
| }, | |
| { | |
| "episode_index": 1, | |
| "task_index": 1, | |
| "task_key": "fill_pen_holder", | |
| "source_task_key": "fill_pen_holder", | |
| "length": 934, | |
| "dataset_from_index": 579, | |
| "dataset_to_index": 1513 | |
| }, | |
| { | |
| "episode_index": 2, | |
| "task_index": 2, | |
| "task_key": "fold_clothes", | |
| "source_task_key": "fold_clothes", | |
| "length": 301, | |
| "dataset_from_index": 1513, | |
| "dataset_to_index": 1814 | |
| }, | |
| { | |
| "episode_index": 3, | |
| "task_index": 3, | |
| "task_key": "hang_mugs", | |
| "source_task_key": "hang_mugs", | |
| "length": 513, | |
| "dataset_from_index": 1814, | |
| "dataset_to_index": 2327 | |
| }, | |
| { | |
| "episode_index": 4, | |
| "task_index": 4, | |
| "task_key": "insert_tubes", | |
| "source_task_key": "insert_tubes", | |
| "length": 320, | |
| "dataset_from_index": 2327, | |
| "dataset_to_index": 2647 | |
| }, | |
| { | |
| "episode_index": 5, | |
| "task_index": 5, | |
| "task_key": "make_toast", | |
| "source_task_key": "make_toast", | |
| "length": 584, | |
| "dataset_from_index": 2647, | |
| "dataset_to_index": 3231 | |
| }, | |
| { | |
| "episode_index": 6, | |
| "task_index": 6, | |
| "task_key": "organize_table", | |
| "source_task_key": "organize_table", | |
| "length": 839, | |
| "dataset_from_index": 3231, | |
| "dataset_to_index": 4070 | |
| }, | |
| { | |
| "episode_index": 7, | |
| "task_index": 7, | |
| "task_key": "pack_objects_into_box", | |
| "source_task_key": "pack_objects_into_box", | |
| "length": 414, | |
| "dataset_from_index": 4070, | |
| "dataset_to_index": 4484 | |
| }, | |
| { | |
| "episode_index": 8, | |
| "task_index": 8, | |
| "task_key": "play_stacking_toy", | |
| "source_task_key": "play_stacking_toy", | |
| "length": 888, | |
| "dataset_from_index": 4484, | |
| "dataset_to_index": 5372 | |
| }, | |
| { | |
| "episode_index": 9, | |
| "task_index": 9, | |
| "task_key": "press_by_number", | |
| "source_task_key": "press_by_number", | |
| "length": 378, | |
| "dataset_from_index": 5372, | |
| "dataset_to_index": 5750 | |
| }, | |
| { | |
| "episode_index": 10, | |
| "task_index": 10, | |
| "task_key": "put_bottles_into_dustbin", | |
| "source_task_key": "put_bottles_into_dustbin", | |
| "length": 363, | |
| "dataset_from_index": 5750, | |
| "dataset_to_index": 6113 | |
| }, | |
| { | |
| "episode_index": 11, | |
| "task_index": 11, | |
| "task_key": "stack_blocks", | |
| "source_task_key": "stack_blocks", | |
| "length": 268, | |
| "dataset_from_index": 6113, | |
| "dataset_to_index": 6381 | |
| }, | |
| { | |
| "episode_index": 12, | |
| "task_index": 12, | |
| "task_key": "store_laptop_and_headphones", | |
| "source_task_key": "store_laptop_and_headphones", | |
| "length": 551, | |
| "dataset_from_index": 6381, | |
| "dataset_to_index": 6932 | |
| }, | |
| { | |
| "episode_index": 13, | |
| "task_index": 13, | |
| "task_key": "swap_blocks", | |
| "source_task_key": "swap_blocks", | |
| "length": 445, | |
| "dataset_from_index": 6932, | |
| "dataset_to_index": 7377 | |
| }, | |
| { | |
| "episode_index": 14, | |
| "task_index": 14, | |
| "task_key": "sweep_blocks", | |
| "source_task_key": "sweep_objects", | |
| "length": 703, | |
| "dataset_from_index": 7377, | |
| "dataset_to_index": 8080 | |
| } | |
| ] | |
| } | |