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5 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Caroline Pascal
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3dd19d043e |
feat(depth maps): adding support for depth in LeRobot (#3644)
* feat(depth): add depth quantization helpers and tests
* feat(video): add ffv1 to supported codecs
* feat(depth): persist depth metadata
* feat(depth): extend quantization tools to better fit the encoding/decoding pipeline
* feat(depth): plumb DepthEncoderConfig through LeRobotDataset and DatasetWriter
* feat(depth): wire StreamingVideoEncoder + writer to depth encoder
* feat(depth): wire DatasetReader to decode_depth_frames
* feat(cameras/realsense): expose async depth in metric meters
* feat(features): route 2D camera shapes to observation.depth.<key>
* feat(robots/so_follower): emit + populate depth keys when use_depth
* feat(record): plumb DepthEncoderConfig through lerobot-record
* feat(viz): render depth observations as rr.DepthImage in Viridis
* feat(depth maps writer): adding support for raw depth maps recording with image writer
* chore(format): format code
* feat(depth shape): ensuring depth maps shape is always including the channel
* feat(is_depth): simplifying is_depth nested name + legacy support
* fix(stop_event): fixing stop_event race condition in camera classes
* fix(plumbing): fixing missing parts in the depth maps pipeline
* chore(typos): fixing typos
* test(fix): fixing exisiting tests to still work with latest features
* tests(depth): adding new tests for depth integration validation
* feat(pix_fmt channels): use PyAv to check get pixel formats number of channels
* feat(refactor): refactor DepthEncoderConfig quantization pipeline, so that the methods do not live in the config class. Add pixel format - channels validation.Move the default pixel format for depth in the config file.
* fix(pre-commit): fixing mutable defautl value
* fix(info): fixing info metadata update when is_depth_map was set
* tests(typos): fixing typos in tests
* fix(realsense): fixing typo in realsense serial number
* fix(normalization): restricting 255 normalization to non depth/uint8 images only
* fix(typo): fixing typo
* fix(TIFF): add missing quantization and cleanup for TIFF files
* feat(batched dequantization): optimizing dequantize_depth for torch based batched dequantization
* feat(tools): adding depth support in LeRobotDataset edition tools
* test(aggregate): extending aggregation tests to depth frames
* test(cleaning): cleaning up tests
* fix(from_video_info): fixing early validation issue in from_video_info
* fix(typo): fixing typo
* fix(is_depth): adding missing doctrings and is_depth arguments in video decoding functions
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
* fix(depth units): fixing depth units output for the realsense cameras
* feat(output unit): adding support for output unit specification at dataset reading/training time
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
* test(depth): cleaning up depth tests
* test(depth encoding): updating and cleaning video/depth encoding tests
* chore(format): formatting code
* docs(depth): improving depth maps docs
* test(fix): fixing depth tests
* test(dataset tools): adding missing tests for new dataset edition tools features
* chore(format): formatting code
* fix(pyav check): fixing PyAV option validation for integer codec options by normalizing
numeric values before calling `is_integer()`
Co-authored-by: Wensi (Vince) Ai <59036629+wensi-ai@users.noreply.github.com>
* docs(mermaid): fixing mermaid diagram
* fix(rebase): rebase follow up corrections
* feat(dataset tools): adding missing docstrings and features for depth fill support in dataset edition tools
* docs(docstring): updating docstrings
* docs(dataset tools): updating docs
* fix(save images): fixing image saving in dataset tools
* fix(update video info): fixing update video info logic to match the recording and editing use cases
* test(reencode): fixing reencoding monkeypatch
* fix(review): add Claude review
* chore(format): format code
* fix(update video info): ditching the differentiated approahces for video info update - video info are always updated unless for preserved keys.
* chore(rebase): fixing rebase merge conflicts
* test(visualization): fixing visualization tests
* feat(docstrings): adding explicit docstring for encoding parameters. Docstrigns will now show up as description in the CLI --help.
* feat(mm as default): adding a global DEFAULT_DEPTH_UNIT variable setting mm as default depth unit
* fix(RGB <-> camera): renaming camera_encoder to rgb_encoder for clarity
* chore(TODO): removing deprecated TODO
* doc(write_u16_plane): improving docstrings for write_u16_plane
* feat(units): adding constants for depth frames units (m and mm)
* fix(spam): replacing spamming warning but a debug log
* feat(leagcy metadata): adding automatic metadata update for legacy 'video.is_depth_map' feature
* fix(copy&reindex): fixing metadat reshaping for single channel frames
* fix(ImageNet): excluding dpeth frames from ImageNet stats
* fix(PyAV container seek): fixing initial PyAV container seek to be robust againsy codec choice
* feat(lerobot-dataset-viz): adding support for depth in lerobot-dataset-viz
* fix(compress): removing rerun compression for DepthImages
* fix(signle channel squeeze): fixing single channel squeezing
* chore(format): format code
* fix(streaming): adding support for dequantization in streaming_dataset.py
* refactor(read depth): factorizing depth reading methods for realsense camera and adding support for depth-only usage
* chore(renaming): fixing missed RGBEncoderConfig renamings
* docs(renaming): reflecting renamings in a clearer way in the docs
* chore(annotation): excluding depth from the annotation pipeline
* feat(robots): adding depth support in compatible follower robots
* feat(LeSadKiwi): excluding LeKiwi from depth support (for now)
* chore(fail): removing misplaced file
* chore(fail): removing misplaced file
* fix(remove ffv1): removing ffv1 as it does not support MP4
* docs(cheat sheet): adding depth and video encoding to the cheat sheet
* fix(lossless): tuning depth encoding parameters for lossless depth storage
* test(fix): fixing failing tests
* depth(ZMQ): excluding ZMQ from depth support
* Revert "depth(ZMQ): excluding ZMQ from depth support"
This reverts commit
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|
Pepijn
|
7ab4936b1b |
Add extensive language support (#3467)
* Add extensive language support * Address review: split persistent/event schemas, drop event timestamps - recipe.py: derive _VALID_ROLES/_VALID_STREAMS from MessageRole/MessageStream Literals - dataset_metadata.py: keep CODEBASE_VERSION at v3.0 - language.py: remove RESERVED_STYLES; split arrow/feature schemas into persistent (with timestamp) and event (without timestamp); add docstrings - language_render.py: events use frame-row timestamp implicitly; no per-event timestamp filtering or sorting - converters.py: drop unused subtask_key passthrough - add docstrings to new public APIs (recipe, render_messages_processor, collate) - update tests for split schemas; revert uv.lock Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Add docstrings to all new helpers; revert uv.lock Covers private helpers in recipe.py, language.py, language_render.py, and render_messages_processor.py. Also reverts uv.lock to main (it was re-generated by `uv run` during local checks). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(language): add motion (persistent) and trace (event-only) styles Promote the previously-reserved motion/trace styles to first-class core styles. motion routes to language_persistent (it tracks robot state over time); trace routes to language_events (single-moment annotations). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(language): per-camera tagging on view-dependent styles Adds a nullable `camera` field to the language row struct (both persistent and event variants) so view-dependent styles like `vqa` can carry which `observation.images.*` view they were grounded against. Without this, multi-camera datasets ended up with multiple `(vqa, role)` rows at the same timestamp that the resolver could not disambiguate. - `language.py`: add `camera` to PERSISTENT_ROW_FIELDS / EVENT_ROW_FIELDS, to both Arrow struct types and the HF datasets feature mappings; introduce VIEW_DEPENDENT_STYLES = {vqa, motion, trace} plus `is_view_dependent_style` and `validate_camera_field` helpers (camera required iff style is view-dependent). - `language_render.py`: thread an optional `camera=` kwarg through every resolver (`active_at`, `emitted_at`, `nth_prev`, `nth_next`) and through `_matching_rows` / `_select_*`, so recipes can disambiguate per-camera VQA with `emitted_at(t, style=vqa, role=assistant, camera=...)`. Without a `camera` filter, multi-row matches keep raising the existing ambiguity error — which is the desired behaviour on multi-camera data. - `recipes/pi05_hirobot.yaml`: replace the single `ask_vqa` branch with `ask_vqa_top` and `ask_vqa_wrist` per-camera sub-recipes (each carrying the matching image block), keeping the original 0.20 budget and documenting the customization point for datasets with different cameras. - Tests: schema test asserts the new field order; new tests cover `is_view_dependent_style`, `validate_camera_field` (both required and forbidden directions), per-camera `emitted_at` filtering, and the ambiguity error when two cameras emit `(vqa, assistant)` at the same timestamp without a `camera=` filter. RenderMessagesStep + dataset passthrough fixtures updated to include the new field. - `docs/source/language_and_recipes.mdx`: document the `camera` field, the per-camera resolver pattern, and the canonical recipe convention. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(language): drop motion from VIEW_DEPENDENT_STYLES Motion primitives are described in robot-frame (joint / Cartesian) terms, not pixel space, so they are camera-agnostic. Only `vqa` (event) and `trace` (event, pixel-trajectory) are view-dependent. The `camera` field stays on PERSISTENT_ROW_FIELDS for schema symmetry — the validator, resolver, and HF feature mapping behave identically across the two columns regardless of which styles populate `camera` today — but persistent rows now always have `camera=None` in practice. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(language): task_aug style + automatic ${task} rephrasing rotation Adds task-prompt diversity (Xiao 2022 / CAST) without touching ``meta/tasks.parquet`` or forcing recipes to opt in. The plan reserved ``task_aug`` as a future style; this lands it now. - ``language.py``: add ``task_aug`` to ``CORE_STYLES`` and ``PERSISTENT_STYLES``. ``column_for_style("task_aug")`` returns ``language_persistent`` so PR 2 writers route it correctly. - ``language_render.py``: ``_resolve_task`` now consults the persistent slice for rows of ``style="task_aug", role="user"``. When any exist it picks one deterministically by ``sample_idx`` (blake2b-keyed, not Python's randomized hash) so an epoch sees every rephrasing of every episode while the same sample still resolves identically across reruns. Falls back to the canonical ``meta/tasks.parquet`` task when no rephrasings are present, so existing datasets and unannotated runs keep their behaviour. Explicit ``task=`` overrides still win. - Tests: rephrasing coverage across samples, determinism on repeat ``sample_idx``, fallback when persistent has no ``task_aug`` rows, and explicit override priority. Recipes get this for free: any ``${task}`` placeholder rotates through the available rephrasings. Recipes that want the literal canonical task can override the binding. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(language): tool catalog in meta/info.json + LeRobotDatasetMetadata.tools Stores OpenAI-style function schemas at ``meta/info.json["tools"]`` so datasets can declare which tools are available (today: just ``say``; tomorrow: per-dataset extensions). The ``DEFAULT_TOOLS`` constant fills in for unannotated datasets so chat-template consumers don't have to special-case anything. Three pieces: - ``language.py``: ``SAY_TOOL_SCHEMA`` and ``DEFAULT_TOOLS`` constants. Single source of truth — PR 2's writer and PR 3's runtime tool registry will both import from here instead of duplicating the dict. - ``dataset_metadata.py``: ``LeRobotDatasetMetadata.tools`` property reads ``info.json["tools"]`` and falls back to ``DEFAULT_TOOLS``. Returns deep-copied dicts so callers can mutate the result safely. - ``docs/source/tools.mdx``: spec page covering the catalog, per-row invocations, and the three-step "how to add a new tool" workflow (declare schema, implement, register). Linked from the docs toctree under the Datasets section. This lays the groundwork for PR 2's pipeline writing the catalog out during annotation, and PR 3's ``src/lerobot/tools/`` package shipping runnable implementations (one file per tool — first up: ``say.py`` wrapping Kyutai's pocket-tts). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Apply ruff and prettier formatting after merge Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * refactor(language): unify resolver dispatch and prune redundant test scaffolding * Drop the unused `events` kwarg from `active_at`/`nth_prev`/`nth_next`; only `emitted_at` actually consults events. The dispatcher in `_resolve_spec` now passes events conditionally. * Replace the dual `_persistent_sort_key`/`_event_sort_key` pair with a single `_row_sort_key` and drop the `sort_key` parameter from `_select_one`. Event rows lack `timestamp` (it is implicit in the frame) and now default to `0.0` for sort purposes — the `(style, role)` tiebreaker is unchanged. * Inline `_select_latest` into `active_at` (its only caller). * Collapse `emitted_at`'s dual-branch into one `_select_one` call. * Tighten `_validate_persistent_resolver` to a single `column_for_style(style) != LANGUAGE_PERSISTENT` check. * Parameterize `test_per_camera_blend_renders_both_views` over the two cameras and factor the sub-recipe builder into `_vqa_subrecipe` so the test no longer hand-rolls two near-identical recipe blocks. Net -98 LOC; behavior, public resolver names, and test expectations unchanged. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(language): always raise on ambiguous resolver matches `_select_one` previously skipped its ambiguity check whenever any of `role`/`tool_name`/`camera` was set, on the assumption that the caller had already pinned down a unique row. That left a real ambiguity hole for VQA: with two cameras emitting `(vqa, assistant)` at the same frame, `emitted_at(..., role="assistant")` silently picked the first sorted row instead of telling the recipe to add `camera=...`. The existing `test_emitted_at_raises_on_ambiguous_per_camera_vqa` test already encoded the desired behavior. Tighten the check: any time `len(rows) > 1` we now raise with the selectors echoed back, so users see exactly which fields they passed and that more is needed to disambiguate. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore: fix CI — collapse short ValueError to one line, refresh uv.lock * `ruff format` on CI (newer version) wants the short `camera=None` ValueError on a single line. * `uv.lock` was stale relative to `pyproject.toml`'s `datasets>=4.7.0` pin (and picked up upstream `s390x` marker fixes for cuda packages). CI runs `uv sync --locked` which rejected the divergence. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(language): keep base install green — drop processor re-export, gate dataset-extra tests `lerobot.processor` re-exported `RenderMessagesStep` at the package level, so importing anything from `lerobot.processor` pulled in `lerobot.datasets.language` → `lerobot.datasets/__init__.py` → `require_package("datasets")`, which fails in the Tier 1 base install that intentionally omits the `[dataset]` extra. The chain bricked collection for unrelated suites (`tests/policies/pi0_pi05/...`, `tests/envs/...`, etc.). * Stop re-exporting `RenderMessagesStep` from `lerobot.processor`. The only consumer (the test) already imports from the submodule. Document the deliberate omission in the module docstring. * Add `pytest.importorskip("datasets", ...)` (and `pandas` where needed) at the top of the four PR-added tests that exercise the language stack: - tests/datasets/test_language.py - tests/datasets/test_language_render.py - tests/processor/test_render_messages_processor.py - tests/utils/test_collate.py Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(language): address review — tools accessor, motion docs, conditional collate * **`meta.tools` actually reads `info.json["tools"]`.** `DatasetInfo` had no `tools` field, so `from_dict` silently dropped the key (it warned about unknown fields then discarded them) and the property always returned `DEFAULT_TOOLS`. Added `tools: list[dict] | None` to the dataclass; `to_dict()` drops it when unset so existing datasets keep a clean `info.json`. Fixed the accessor to read `self.info.tools` (the previous `.get(...)` would have raised AttributeError on the dataclass anyway). Added regression tests: fallback when absent, round-trip from disk, and round-trip through `DatasetInfo.from_dict` / `to_dict`. * **`motion` is not view-dependent — fix the docs.** The mdx claimed rows of style `motion` must carry `camera`, but `VIEW_DEPENDENT_STYLES = {"vqa", "trace"}` and the validator agrees: motion primitives are joint/Cartesian-frame, not pixel-space. Updated both call-out paragraphs in `language_and_recipes.mdx`. * **Conditional `collate_fn` swap.** Added `meta.has_language_columns` and gate the `lerobot_collate_fn` swap in `lerobot_train.py` on it, so non-language datasets keep PyTorch's `default_collate`. Also added a pass-through test in `test_collate.py` that asserts on a plain tensor batch the custom collate matches `default_collate` key-for-key, plus a test for the `None`-sample drop path. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * review: dedupe regex, centralize column names, harden collate, more tests * **#2 — dedupe `_PLACEHOLDER_RE`.** The same regex was compiled in `recipe.py` and `language_render.py`. Promote to module-level `PLACEHOLDER_RE` in `recipe.py` (its primary owner — declares template syntax) and import from `language_render.py`. * **#3 — centralize language column names.** `io_utils.py` had hardcoded `{"language_persistent", "language_events"}` literals at two sites. Replace with `LANGUAGE_COLUMNS` import so a future column rename can't silently desync. * **#4 — defensive collate preserved-keys.** `lerobot_collate_fn` silently filtered language fields from samples that didn't have them, which would hand downstream consumers a preserved list shorter than the tensor batch. Now: if any sample carries a key, every sample in the batch must carry it; otherwise raise a `ValueError` so the upstream rendering bug surfaces at the boundary. * **#5 — `_scalar` rejects non-singleton lists.** Previously a zero- or multi-element list fell through and triggered confusing `float([])` errors downstream. Now raises `ValueError` with the actual length. * **#6 — refactor `_extract_complementary_data`.** Replace 11 lines of `key = {... if ... else {}}` plus an 11-line splat dict with a single `_COMPLEMENTARY_KEYS` tuple iterated once. * **#7 — document `EXTENDED_STYLES`.** Was an empty `set()` with no comment. Add a docstring explaining it's an intentional extension point: downstream modules append project-local styles before `column_for_style` is called. * **#9 — `tools.mdx` notes the runtime layer is future work.** The page referenced `src/lerobot/tools/`, `registry.py`, and `get_tools(meta)` — none exist in this PR. Added a callout at the start of "How to add your own tool" plus a note on the implementations paragraph. * **#10 — tests for YAML round-trip, malformed rows, blend validation.** `test_recipe.py` grew from 1 case to 12 covering: blend-or-messages exclusivity, target-turn requirement, blend emptiness, weight presence/positivity, nested-blend rejection, `from_dict` with nested blends, `from_yaml` / `load_recipe` agreement, top-level non-mapping rejection. Added a malformed-row test for `_normalize_rows` that asserts non-dict entries raise `TypeError`. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * review: emitted_at uses 0.1s tolerance; MessageTurn requires stream at construction * **Float tolerance in `emitted_at` for persistent styles.** The ``_timestamp(row) == t`` exact-equality check silently missed any caller that derived ``t`` arithmetically (e.g. ``frame_idx / fps``) even though the parquet timestamp would only differ by ULPs. Added ``EMITTED_AT_TOLERANCE_S = 0.1`` and check ``abs(...) <= tolerance`` instead, with a docstring explaining why exact equality wasn't enough and why 0.1 s is safe at typical 30–100 Hz control rates. Test asserts the new behavior at half-window (matches) and double-window (no match) using the constant so it stays in sync. * **`MessageTurn.stream` is required at construction.** It was typed ``MessageStream | None = None`` so YAML could omit ``stream:`` and pass the dataclass invariant — but ``_validate_rendered`` rejected ``None`` streams later, surfacing the error at the first sample instead of at recipe load. Now ``__post_init__`` raises ``ValueError`` if ``stream`` is ``None``, with the list of valid streams in the message. The redundant late-stage check in ``_validate_rendered`` is replaced with a one-line comment that cites the upstream invariant. Test pins the new construction-time rejection. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs(tools): drop follow-up-PR references Reword the two callouts in `tools.mdx` to describe the runtime layer in present tense ("not part of the catalog layer shipped today", "those modules don't yet exist in the tree") instead of pointing at a specific follow-up PR. Keeps the doc honest about what works now without coupling it to a particular release order. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * review: address CarolinePascal feedback - language timestamps: float64 -> float32 to match LeRobotDataset frame timestamps (Arrow struct + HF feature) - dataset_metadata: hoist `.language` imports to module top — language.py has no lerobot imports, so there is no circular-import risk - dataset_metadata: add a `meta.tools` setter that persists the catalog to info.json and reloads `meta.info` - feature_utils: validate the `language` dtype instead of returning "" — warn (non-fatal) when a non-empty value is written at record time - centralize the scalar-unwrap helper as `lerobot.utils.utils.unwrap_scalar`, shared by render_messages_processor and language_render - docs: move `## Layer 2 — recipe anatomy` ahead of the resolver sections, which describe recipe bindings rather than dataset layout - language_render: note in EMITTED_AT_TOLERANCE_S that persistent rows change on a human-action timescale, not the camera frame rate Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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Maxime Ellerbach
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cb0a944941 |
refactor(datasets): replace untyped dict with typed DatasetInfo dataclass (#3472)
* refactor(datasets): replace untyped dict with typed DatasetInfo dataclass Introduce typed DatasetInfo dataclass to replace untyped dict representation of info.json. Changes: - Add DatasetInfo dataclass with explicit fields and validation - Implement __post_init__ for shape conversion (list ↔ tuple) - Add dict-style compatibility layer (__getitem__, __setitem__, .get()) - Add from_dict() and to_dict() for JSON serialization - Update io_utils to use load_info/write_info with DatasetInfo - Update dataset utilities and metadata to use attribute access - Remove aggregate.py dict-style field access - Add tests fixture support for DatasetInfo Benefits: - Type safety with IDE auto-completion - Validation at construction time - Explicit schema documentation * fix pre-commit * update docstring inside DatasetInfo.from_dict() * sorts the unknown to have deterministic output Signed-off-by: Maxime Ellerbach <maxime@ellerbach.net> * refactoring the last few old fieds * fix crop dataset roi type mismatch * use consistantly int for data and video_files_size_in_mb --------- Signed-off-by: Maxime Ellerbach <maxime@ellerbach.net> Co-authored-by: jjolla93 <jjolla93@gmail.com> |
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Steven Palma
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df0763a2bc | feat(dependencies): minimal default tag install (#3362) | ||
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Steven Palma
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123495250b |
refactor(dataset): split LeRobotDataset into DatasetReader & DatasetWriter (+ API cleanup) (#3180)
* refactor(dataset): split reader and writer * chore(dataset): remove proxys * refactor(dataset): better reader & writer encapsulation * refactor(datasets): clean API + reduce leaky implementations * refactor(dataset): API cleaning for writer, reader and meta * refactor(dataset): expose writer & reader + other minor improvements * refactor(dataset): improve teardown routine * refactor(dataset): add hf_dataset property at the facade level * chore(dataset): add init for datasset module * docs(dataset): add docstrings for public API of the dataset classes * tests(dataset): add tests for new classes * fix(dataset): remove circular dependecy |