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RoboDojo keyframe memory annotations

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  1. .gitattributes +60 -0
  2. README.md +81 -0
  3. cover_blocks/trajectory_0/progress.json +9 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ task_categories:
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+ - robotics
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+ tags:
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+ - robodojo
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+ - annotations
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+ ---
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+
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+ # RoboDojo progress annotations
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+
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+ Frame-level labels over the official RoboDojo episodes, for the six tasks that
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+ require remembering something seen earlier in the episode. They carry no images,
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+ states, actions or episodes; the observations and actions a policy trains on
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+ come from [`RoboDojo-Benchmark/Robodojo`](https://huggingface.co/datasets/RoboDojo-Benchmark/Robodojo).
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+
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+ Published so that the training recipe behind our RoboDojo entry can be run by
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+ anyone: without these labels the keyframe-memory stage has nothing to learn
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+ from.
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+
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+ ## What is in it
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+
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+ 600 files, `<task>/trajectory_<n>/progress.json`, covering all 100 episodes of
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+ each of the six tasks. Plus `index.json`, which maps each task directory to the
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+ official task instruction and states the schema.
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+
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+ | field | meaning |
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+ | --- | --- |
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+ | `keyframes` | the frames at which the task made visible progress that has to be remembered |
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+ | `meta[].frame` / `meta[].box` | `[x1, y1, x2, y2]` in raw-video pixels, the object that progress was about |
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+ | `meta[].window` | `[first, last]` — the frames at which recording that keyframe still counts as correct |
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+ | `total_frames` | the episode's length, so a file can be checked against the episode it describes |
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+
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+ `meta[].window` exists because a keyframe is a moment, not a frame: several
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+ consecutive frames show the same progress, so a selector that answers one frame
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+ early is not wrong. Training scores the answer against the whole interval
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+ rather than against a single index.
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+
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+ ## Per-task shape
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+
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+ | task | episodes | keyframes each | boxes each | acceptance intervals each |
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+ | --- | --- | --- | --- | --- |
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+ | `cover_blocks` | 100 | 4 | — | — |
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+ | `imitate_sorting_sequence` | 100 | 5 | 5 | — |
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+ | `match_and_pick_from_conveyor` | 100 | 1 | — | 1 |
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+ | `press_by_number` | 100 | 5–21 | — | — |
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+ | `swap_T` | 100 | 1 | — | — |
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+ | `swap_blocks` | 100 | 7 | — | 1 |
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+
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+ Where a task has no acceptance interval, the selection answer is scored against
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+ the single annotated candidate.
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+
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+ `swap_T` and `match_and_pick_from_conveyor` carry one keyframe, at frame 0: what
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+ has to be remembered is the initial position and orientation of the two blocks,
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+ and the first object on the conveyor. Both are visible at the start.
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+
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+ ## Checking them against the official episodes
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+
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+ An annotation bound to the wrong episode would train a policy to recall the
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+ wrong frames. Each file therefore records its episode's length; the loader binds
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+ by task instruction and stops if a length disagrees.
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+
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+ ## How they were produced
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+
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+ For each task we decided by hand what counts as a keyframe — the moments at
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+ which the task makes the progress a policy has to remember, such as a block
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+ being covered or a button press being committed. A script then located the
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+ frames that satisfy the rule in each episode, and every file was checked by a
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+ person and corrected where the script had put a frame in the wrong place.
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+
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+ ## Using them
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+
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+ ```bash
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+ hf download x-square-robot/robodojo-memory-annotations --repo-type dataset \
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+ --local-dir <bench_root>/data/robodojo_memory_annotations
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+ ```
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+
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+ The training code that reads them is in
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+ [wall-x](https://github.com/X-Square-Robot/wall-x)
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+ (`wall_x/data/backends/lerobot/robodojo/`); see the WallX policy README in XPolicyLab
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+ for the two training stages.
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