mirror of
https://github.com/huggingface/lerobot.git
synced 2026-05-23 12:40:08 +00:00
Pepijn
f763f85213
Adds the steerable annotation pipeline (`lerobot-annotate`) that populates the `language_persistent` and `language_events` columns introduced in PR 1 directly into `data/chunk-*/file-*.parquet`. No flavor namespace, no sidecar tree. Modules produced: - Module 1 (plan_subtasks_memory): Pi0.7-style subtasks, plan (init + refresh on interjection), MEM-style memory at subtask boundaries. - Module 2 (interjections_and_speech): t=0 speech-only acknowledgement, mid-episode paired interjection + speech tool-call atom. - Module 3 (general_vqa): bbox/keypoint/count/attribute/spatial pairs at configurable cadence with one-retry JSON validation. Writer enforces: per-episode persistent identity, exact-frame event timestamps, column routing per `column_for_style`, dataset-level `tools` column with the `say` schema, drops legacy `subtask_index`. Validator runs against staged JSONL artifacts before the writer rewrites parquet. Adds `lerobot-annotate` console script, `annotations` extra (datatrove + optional vllm), `make annotation-e2e` opt-in smoke target, and `docs/source/annotation_pipeline.mdx`. Branched from PR 1 (`feat/language-columns`). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
33 lines
1.3 KiB
Plaintext
33 lines
1.3 KiB
Plaintext
You are generating a frame-grounded visual question/answer pair for
|
|
chain-of-thought training. Reference: ECoT (Zawalski 2024) and Steerable
|
|
Policies — both train policies on grounded features such as bounding box
|
|
pixel coordinates, keypoints, counts, attributes, and spatial relations.
|
|
|
|
The frame shows a robot working on: "{episode_task}".
|
|
|
|
Question types and the EXACT answer JSON shape required for each:
|
|
|
|
bbox => {{"detections": [{{"label": "<obj>", "bbox_format": "xyxy",
|
|
"bbox": [x1, y1, x2, y2]}}, ...]}}
|
|
bbox is in pixel coordinates (x_min, y_min, x_max, y_max).
|
|
ECoT example: "a white cup [124, 25, 176, 113]".
|
|
|
|
keypoint => {{"label": "<point>", "point_format": "xy",
|
|
"point": [x, y]}}
|
|
|
|
count => {{"label": "<obj>", "count": <int>,
|
|
"note": "<optional short note>"}}
|
|
|
|
attribute => {{"label": "<obj>", "attribute": "<color|shape|state|...>",
|
|
"value": "<observed value>"}}
|
|
|
|
spatial => {{"subject": "<obj>", "relation": "<left_of|right_of|on|in|"
|
|
"above|below|near>", "object": "<obj>"}}
|
|
|
|
Generate a question of type "{question_type}". Output strictly valid JSON:
|
|
|
|
{{
|
|
"question": "<short, frame-grounded question>",
|
|
"answer": <object whose shape matches the schema above>
|
|
}}
|