From 6ab014a5d54916eedefc8a03bd469b7a0dfa42fc Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 17 Oct 2022 20:15:32 -0700 Subject: [PATCH 001/117] Add Pytorch dataloader. --- .github/workflows/ci.yml | 2 +- conda/environment.yml | 1 + noxfile.py | 2 +- pyproject.toml | 3 + setup.cfg | 2 + src/av2/datasets/sensor/utils.py | 2 +- src/av2/evaluation/detection/eval.py | 2 +- src/av2/evaluation/detection/utils.py | 4 +- src/av2/torch/__init__.py | 10 + src/av2/torch/dataloaders/__init__.py | 1 + src/av2/torch/dataloaders/conversions.py | 50 +++ src/av2/torch/dataloaders/sensor.py | 365 ++++++++++++++++++ src/av2/torch/dataloaders/utils.py | 286 ++++++++++++++ src/av2/utils/io.py | 10 +- src/av2/utils/typing.py | 6 + .../annotations.feather | Bin 0 -> 642618 bytes .../city_SE3_egovehicle.feather | Bin 0 -> 161634 bytes ...5b0-a2fa-b4cea13a6d76___img_Sim2_city.json | 1 + ...ea13a6d76_ground_height_surface____PIT.npy | Bin 0 -> 1135548 bytes ...0-a2fa-b4cea13a6d76____PIT_city_57819.json | 1 + .../sensors/lidar/315973157959879000.feather | Bin 0 -> 1048066 bytes tests/torch/dataloaders/test_sensor.py | 72 ++++ 22 files changed, 809 insertions(+), 11 deletions(-) create mode 100644 src/av2/torch/__init__.py create mode 100644 src/av2/torch/dataloaders/__init__.py create mode 100644 src/av2/torch/dataloaders/conversions.py create mode 100644 src/av2/torch/dataloaders/sensor.py create mode 100644 src/av2/torch/dataloaders/utils.py create mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/annotations.feather create mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/city_SE3_egovehicle.feather create mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/adcf7d18-0510-35b0-a2fa-b4cea13a6d76___img_Sim2_city.json create mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/adcf7d18-0510-35b0-a2fa-b4cea13a6d76_ground_height_surface____PIT.npy create mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/log_map_archive_adcf7d18-0510-35b0-a2fa-b4cea13a6d76____PIT_city_57819.json create mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/sensors/lidar/315973157959879000.feather create mode 100644 tests/torch/dataloaders/test_sensor.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index ff39f09b..255e0b9b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -10,7 +10,7 @@ jobs: matrix: os: [macos-latest, ubuntu-latest, windows-latest] python_version: - ["3.8", "3.9", "3.10"] + ["3.8", "3.9", "3.10.6"] venv_backend: ["virtualenv"] defaults: diff --git a/conda/environment.yml b/conda/environment.yml index 28ac5155..212fd000 100644 --- a/conda/environment.yml +++ b/conda/environment.yml @@ -12,6 +12,7 @@ dependencies: - opencv - pandas - pip + - polars - pyarrow - pyproj - rich diff --git a/noxfile.py b/noxfile.py index b1ed5d00..974d5549 100644 --- a/noxfile.py +++ b/noxfile.py @@ -10,7 +10,7 @@ from nox import Session from nox.virtualenv import CondaEnv -PYTHON: Final[List[str]] = ["3.8", "3.9", "3.10"] +PYTHON: Final[List[str]] = ["3.8", "3.9", "3.10.6"] nox.options.sessions = ["black", "isort", "lint", "mypy", "pytest"] diff --git a/pyproject.toml b/pyproject.toml index 322104c3..50159338 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,6 +23,9 @@ disallow_untyped_decorators = false plugins = "numpy.typing.mypy_plugin" strict = true +[tool.pylint] +max-line-length = 120 + [tool.pyright] include = ["src"] diff --git a/setup.cfg b/setup.cfg index 152bdcee..63c5f992 100644 --- a/setup.cfg +++ b/setup.cfg @@ -27,10 +27,12 @@ install_requires = numpy opencv-python pandas + polars pyarrow pyproj rich scipy + torch universal_pathlib package_dir= diff --git a/src/av2/datasets/sensor/utils.py b/src/av2/datasets/sensor/utils.py index 2996c473..91159fd2 100644 --- a/src/av2/datasets/sensor/utils.py +++ b/src/av2/datasets/sensor/utils.py @@ -6,7 +6,7 @@ from pathlib import Path from typing import Dict, Union -logger = logging.Logger(__name__) +logger = logging.getLogger(__name__) def convert_path_to_named_record(path: Path) -> Dict[str, Union[str, int]]: diff --git a/src/av2/evaluation/detection/eval.py b/src/av2/evaluation/detection/eval.py index f5e85141..7a9453ee 100644 --- a/src/av2/evaluation/detection/eval.py +++ b/src/av2/evaluation/detection/eval.py @@ -198,7 +198,7 @@ def summarize_metrics( dts: (N,14) Table of detections. gts: (M,15) Table of ground truth annotations. cfg: Detection configuration. - + Returns: The summary metrics. """ diff --git a/src/av2/evaluation/detection/utils.py b/src/av2/evaluation/detection/utils.py index 4090cb97..66fd07a9 100644 --- a/src/av2/evaluation/detection/utils.py +++ b/src/av2/evaluation/detection/utils.py @@ -13,7 +13,7 @@ import logging from dataclasses import dataclass from pathlib import Path -from typing import Dict, List, Optional, Tuple, Union +from typing import Dict, List, Optional, Tuple, Union, cast import numpy as np from joblib import Parallel, delayed @@ -316,7 +316,7 @@ def compute_average_precision( # Evaluate precision at different recalls. precision_interpolated: NDArrayFloat = np.interp(recall_interpolated, recall, precision, right=0) - average_precision: float = float(np.mean(precision_interpolated)) + average_precision: float = cast(float, np.mean(precision_interpolated)) return average_precision, precision_interpolated diff --git a/src/av2/torch/__init__.py b/src/av2/torch/__init__.py new file mode 100644 index 00000000..80913cb6 --- /dev/null +++ b/src/av2/torch/__init__.py @@ -0,0 +1,10 @@ +"""AV2 Pytorch interface.""" + +import logging + +logger = logging.getLogger(__name__) + +try: + import torch +except ImportError as _: + logger.error("Please install Pytorch to use this module.") diff --git a/src/av2/torch/dataloaders/__init__.py b/src/av2/torch/dataloaders/__init__.py new file mode 100644 index 00000000..8c794a20 --- /dev/null +++ b/src/av2/torch/dataloaders/__init__.py @@ -0,0 +1 @@ +"""Pytorch sensor dataloader module.""" diff --git a/src/av2/torch/dataloaders/conversions.py b/src/av2/torch/dataloaders/conversions.py new file mode 100644 index 00000000..7f841c89 --- /dev/null +++ b/src/av2/torch/dataloaders/conversions.py @@ -0,0 +1,50 @@ +"""Pytorch rigid body transformations.""" + +import math + +import torch +from torch import Tensor + + +@torch.jit.script +def quat_to_xyz(quat_wxyz: Tensor, singularity_value: float = math.pi / 2) -> Tensor: + """Convert scalar first quaternion to Tait-Bryan angles. + + Reference: + https://en.wikipedia.org/wiki/Conversion_between_quaternions_and_Euler_angles#Source_code_2 + + Args: + quat_wxyz: (...,4) Scalar first quaternions. + singularity_value: Value that's set at the singularities. + + Returns: + (...,3) The Tait-Bryan angles --- roll, pitch, and yaw. + """ + qw = quat_wxyz[..., 0] + qx = quat_wxyz[..., 1] + qy = quat_wxyz[..., 2] + qz = quat_wxyz[..., 3] + + # roll (x-axis rotation) + sinr_cosp = 2 * (qw * qx + qy * qz) + cosr_cosp = 1 - 2 * (qx * qx + qy * qy) + roll = torch.atan2(sinr_cosp, cosr_cosp) + + # pitch (y-axis rotation) + pitch = 2 * (qw * qy - qz * qx) + is_out_of_range = torch.abs(pitch) >= 1 + pitch[is_out_of_range] = torch.copysign(torch.as_tensor(singularity_value), pitch[is_out_of_range]) + pitch[~is_out_of_range] = torch.asin(pitch[~is_out_of_range]) + + # yaw (z-axis rotation) + siny_cosp = 2 * (qw * qz + qx * qy) + cosy_cosp = 1 - 2 * (qy * qy + qz * qz) + yaw = torch.atan2(siny_cosp, cosy_cosp) + xyz = torch.stack([roll, pitch, yaw], dim=-1) + return xyz + + +def quat_to_yaw(quat_wxyz: Tensor) -> Tensor: + """Scalar-first quaternion to rotation around the gravity aligned axis in radians.""" + xyz: Tensor = quat_to_xyz(quat_wxyz)[:, -1] + return xyz diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py new file mode 100644 index 00000000..8b44a99b --- /dev/null +++ b/src/av2/torch/dataloaders/sensor.py @@ -0,0 +1,365 @@ +"""Pytorch dataloader for the Argoverse 2 dataset.""" + +from __future__ import annotations + +import itertools +import logging +from dataclasses import dataclass, field +from enum import Enum, unique +from math import inf +from pathlib import Path +from typing import Any, Final, ItemsView, List, Optional, Tuple + +import joblib +import numpy as np +import pandas as pd +from filelock import FileLock +from torch.utils.data import Dataset +from upath import UPath + +from av2.geometry.geometry import quat_to_mat +from av2.utils.io import read_feather +from av2.utils.typing import PathType + +from .utils import QUAT_WXYZ_FIELDS, Annotations, Lidar, Sweep, prevent_fsspec_deadlock, query_pose, velocity_kernel + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +XYZ_FIELDS: Final[Tuple[str, str, str]] = ("x", "y", "z") +LIDAR_GLOB_PATTERN: Final[str] = "sensors/lidar/*.feather" + + +@unique +class FileCachingMode(str, Enum): + """File caching mode.""" + + DISK = "DISK" + + +@dataclass +class Av2(Dataset[Sweep]): + """Pytorch dataloader for the sensor dataset. + + Args: + root_dir: Path to the dataset directory. + dataset_name: Dataset name. + split_name: Name of the dataset split. + min_annotation_range: Min Euclidean distance between the egovehicle origin and the annotation cuboid centers. + max_annotation_range: Max Euclidean distance between the egovehicle origin and the annotation cuboid centers. + min_lidar_range: Min Euclidean distance between the egovehicle origin and the lidar points. + max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. + min_interior_pts: Min number of points inside each annotation. + num_accumulated_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). + file_caching_mode: File caching mode. + return_annotations: Boolean flag indicating whether to return annotations. + return_velocity_estimates: Boolean flag indicating whether to return annotations' velocity estimates. + """ + + root_dir: PathType + dataset_name: str + split_name: str + min_annotation_range: float = 0.0 + max_annotation_range: float = inf + min_lidar_range: float = 0.0 + max_lidar_range: float = inf + min_interior_pts: int = 0 + num_accumulated_sweeps: int = 1 + file_caching_mode: Optional[FileCachingMode] = None + return_annotations: bool = False + return_velocity_estimates: bool = False + + file_index: List[Tuple[str, int]] = field(init=False) + + def __post_init__(self) -> None: + """Build the file index.""" + if self.return_annotations and self.dataset_name == "lidar": + raise RuntimeError("The lidar dataset does not have annotations!") + if not self.return_annotations and self.return_velocity_estimates: + raise RuntimeError("with_annotations must be enabled to return annotations' velocities.") + prevent_fsspec_deadlock() + self._build_file_index() + self._log_dataloader_configuration() + + def __repr__(self) -> str: + """Dataloader info.""" + info = "Dataloader configuration settings:\n" + for key, value in sorted(self.items()): + if key == "file_index": + continue + info += f"\t{key}: {value}\n" + return info + + def items(self) -> ItemsView[str, Any]: + """Return the attribute_name, attribute pairs for the dataloader.""" + return self.__dict__.items() + + @property + def file_caching_dir(self) -> PathType: + """File caching directory.""" + return Path("/") / "tmp" / "cache" / "av2" / self.dataset_name / self.split_name + + @property + def split_dir(self) -> PathType: + """Sensor dataset split directory.""" + return UPath(self.root_dir) / self.dataset_name / self.split_name + + def _log_dataloader_configuration(self) -> None: + """Log the dataloader configuration.""" + info = "Dataloader has been configured. Here are the settings:\n" + for key, value in self.items(): + if key == "file_index": + continue + info += f"\t{key}: {value}\n" + logger.info("%s", info) + + def annotations_path(self, log_id: str) -> PathType: + """Get the annotations at the specified log id. + + Args: + log_id: Unique log identifier. + + Returns: + Annotations path for the entire log. + """ + return self.split_dir / log_id / "annotations.feather" + + def lidar_path(self, log_id: str, timestamp_ns: int) -> PathType: + """Get the lidar path at the specified log id and timestamp. + + Args: + log_id: Unique log identifier. + timestamp_ns: Lidar timestamp in nanoseconds. + + Returns: + Lidar path at the log id and timestamp. + """ + return self.split_dir / log_id / "sensors" / "lidar" / f"{timestamp_ns}.feather" + + def pose_path(self, log_id: str) -> PathType: + """Get the city egopose path.""" + return self.split_dir / log_id / "city_SE3_egovehicle.feather" + + def sweep_uuid(self, index: int) -> Tuple[str, int]: + """Get the sweep uuid at the given index. + + Args: + index: Dataset index. + + Returns: + The sweep uuid (log_id, timestamp_ns). + """ + return self.file_index[index] + + def __getitem__(self, index: int) -> Sweep: + """Get the annotations and lidar for one sweep. + + Args: + index: Dataset index. + + Returns: + Sweep object containing annotations and lidar. + """ + annotations = None + if self.return_annotations: + annotations = self.read_annotations(index) + + lidar = self.read_lidar(index) + sweep_uuid = self.sweep_uuid(index) + return Sweep(annotations=annotations, lidar=lidar, sweep_uuid=sweep_uuid) + + def _build_file_index(self) -> None: + """Build the file index for the dataset.""" + file_cache_path = self.file_caching_dir.parent / f"file_index_{self.split_name}.feather" + if file_cache_path.exists(): + file_index = read_feather(file_cache_path).to_numpy().tolist() + else: + logger.info("Building file index. This may take a moment ...") + log_dirs = sorted(self.split_dir.glob("*")) + path_lists: Optional[List[List[Tuple[str, int]]]] = joblib.Parallel(n_jobs=-1, backend="multiprocessing")( + joblib.delayed(Av2._file_index_helper)(log_dir, LIDAR_GLOB_PATTERN) for log_dir in log_dirs + ) + logger.info("File indexing complete.") + if path_lists is None: + raise RuntimeError("Error scanning the dataset directory!") + if len(path_lists) == 0: + raise RuntimeError("No file paths found. Please validate `self.dataset_dir` and `self.split_name`.") + + file_index = sorted(itertools.chain.from_iterable(path_lists)) + self.file_caching_dir.parent.mkdir(parents=True, exist_ok=True) + dataframe = pd.DataFrame(file_index, columns=["log_id", "timestamp_ns"]) + dataframe.to_feather(file_cache_path, compression="uncompressed") + self.file_index = file_index + + def read_annotations(self, index: int) -> Annotations: + """Read the sweep annotations. + + Args: + index: Dataset index. + + Returns: + The annotations object. + """ + log_id, timestamp_ns = self.sweep_uuid(index) + cache_path = self.file_caching_dir / log_id / "annotations.feather" + annotations_path = self.annotations_path(log_id) + + dataframe = self._read_frame(annotations_path, cache_path) + if self.return_velocity_estimates: + dataframe = self._populate_annotations_velocity(index, dataframe) + + distances = np.linalg.norm(dataframe.loc[:, ["tx_m", "ty_m", "tz_m"]].to_numpy(), axis=-1) + num_interior_pts = dataframe.loc[:, "num_interior_pts"].to_numpy().astype(int) + timestamps = dataframe.loc[:, "timestamp_ns"].to_numpy().astype(int) + mask = ( + (num_interior_pts >= self.min_interior_pts) + & (timestamps == timestamp_ns) + & (distances >= self.min_annotation_range) + & (distances <= self.max_annotation_range) + ) + dataframe = dataframe.loc[mask].reset_index(drop=True) + annotations = Annotations(dataframe) + return annotations + + def _populate_annotations_velocity(self, index: int, annotations: pd.DataFrame) -> pd.DataFrame: + """Populate the annotations with their estimated velocities. + + Args: + index: Dataset index. + annotations: DataFrame of annotations loaded from a feather file. + + Returns: + The dataFrame populated with velocities. + """ + current_log_id, _ = self.sweep_uuid(index) + pose_path = self.pose_path(current_log_id) + + file_caching_path = self.file_caching_dir / current_log_id / "city_SE3_egovehicle.feather" + city_SE3_ego = self._read_frame(pose_path, file_caching_path) + + annotations = annotations.sort_values(["track_uuid", "timestamp_ns"]) + annotations_with_poses = annotations.merge( + city_SE3_ego, on=["timestamp_ns"], suffixes=("_obj", None), how="left" + ) + quat = annotations_with_poses.loc[:, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float64) + mats = quat_to_mat(quat) + translation = annotations_with_poses.loc[:, ["tx_m", "ty_m", "tz_m"]].to_numpy().astype(np.float64) + t_xyz = annotations_with_poses.loc[:, ["tx_m_obj", "ty_m_obj", "tz_m_obj"]].to_numpy().astype(np.float64) + annotations.loc[:, ["tx_m_city", "ty_m_city", "tz_m_city"]] = ( + t_xyz[:, None] @ mats.transpose(0, 2, 1) + translation[:, None] + ).squeeze() + + velocities = ( + annotations.loc[:, ["track_uuid", "timestamp_ns", "tx_m_city", "ty_m_city", "tz_m_city"]] + .groupby(["track_uuid"]) + .diff() + .rolling(window=3, min_periods=1, closed="right", center=True, method="table") + .apply(velocity_kernel, raw=True, engine="numba") + .to_numpy() + .astype(np.float64) + ) + annotations[["vx", "vy", "vz"]] = velocities[:, 1:] + annotations = annotations.drop(["tx_m_city", "ty_m_city", "tz_m_city"], axis=1) + return annotations.reset_index(drop=True) + + def read_lidar(self, index: int) -> Lidar: + """Read the lidar sweep. + + Args: + index: Dataset index. + + Returns: + Tensor of annotations. + """ + log_id, timestamp_ns_j = self.sweep_uuid(index) + temporal_window = self.file_index[max(index - self.num_accumulated_sweeps + 1, 0) : index + 1][::-1] + filtered_window: List[Tuple[str, int]] = list( + filter(lambda sweep_uuid: sweep_uuid[0] == log_id, temporal_window) + ) + + dataframe_list = [] + poses = self._read_frame( + src_path=self.pose_path(log_id), + file_caching_path=self.file_caching_dir / log_id / "city_SE3_egovehicle.feather", + ) + ego_tj_SE3_city = query_pose(poses, timestamp_ns_j).inverse() + for _, (log_id, timestamp_ns_i) in enumerate(filtered_window): + dataframe = self._read_frame( + src_path=self.lidar_path(log_id, timestamp_ns_i), + file_caching_path=self.file_caching_dir / log_id / "sensors" / "lidar" / f"{timestamp_ns_i}.feather", + ) + xyz_ti = dataframe.loc[:, list(XYZ_FIELDS)].to_numpy().astype(np.float64) + xyz_tj = xyz_ti + dt = timestamp_ns_j - timestamp_ns_i + assert dt >= 0 + + # Timestamps do not match, we're in a new reference frame. + if dt != 0: + city_SE3_ego_ti = query_pose(poses, timestamp_ns_i) + ego_tj_SE3_ego_ti = ego_tj_SE3_city.compose(city_SE3_ego_ti) + xyz_tj = ego_tj_SE3_ego_ti.transform_point_cloud(xyz_ti) + + dataframe[list(XYZ_FIELDS)] = pd.DataFrame(xyz_tj.astype(np.float32), columns=list(XYZ_FIELDS)) + dataframe["timedelta_ns"] = np.full(len(xyz_tj), fill_value=dt) + dataframe_list.append(dataframe) + dataframe = pd.concat(dataframe_list).reset_index(drop=True) + dataframe = self._post_process_lidar(dataframe) + return Lidar(dataframe) + + def _post_process_lidar(self, dataframe: pd.DataFrame) -> pd.DataFrame: + """Apply post-processing operations on the point cloud. + + Args: + dataframe: Lidar dataframe. + + Returns: + The filtered lidar dataframe. + """ + distances = np.linalg.norm(dataframe.loc[:, list(XYZ_FIELDS)].to_numpy(), axis=1) + dataframe["distance"] = distances + mask = (distances >= self.min_lidar_range) & (distances <= self.max_lidar_range) + dataframe = dataframe.loc[mask] + dataframe = dataframe.sort_values(["timedelta_ns", "distance"]) + return dataframe + + @staticmethod + def _file_index_helper(root_dir: PathType, file_pattern: str) -> List[Tuple[str, int]]: + """Build the file index in a multiprocessing context. + + Args: + root_dir: Root directory. + file_pattern: File pattern string. + + Returns: + The list of keys within the glob context. + """ + prevent_fsspec_deadlock() + return [(key.parts[-4], int(key.stem)) for key in root_dir.glob(file_pattern)] + + def _read_frame(self, src_path: PathType, file_caching_path: PathType) -> pd.DataFrame: + """Read a dataframe from a remote source or a locally cached location. + + Args: + src_path: Path to the non-cached file. + file_caching_path: Path to the cached file. + + Returns: + DataFrame representation of the feather file. + """ + if self.file_caching_mode == FileCachingMode.DISK: + file_caching_path.parent.mkdir(parents=True, exist_ok=True) + lock_name = str(file_caching_path) + ".lock" + lock = FileLock(lock_name) + with lock: + if not file_caching_path.exists(): + dataframe = read_feather(src_path) + dataframe.to_feather(file_caching_path, compression="uncompressed") + else: + try: + dataframe = read_feather(file_caching_path) + except Exception as _: + dataframe = read_feather(src_path) + dataframe.to_feather(file_caching_path, compression="uncompressed") + else: + dataframe = read_feather(src_path) + return dataframe diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py new file mode 100644 index 00000000..b5f7410b --- /dev/null +++ b/src/av2/torch/dataloaders/utils.py @@ -0,0 +1,286 @@ +"""Pytorch sensor dataloader utilities.""" + +from __future__ import annotations + +import itertools +import sys +from dataclasses import dataclass +from enum import Enum, unique +from typing import Final, Optional, Tuple + +import fsspec.asyn +import numba as nb +import numpy as np +import pandas as pd +import polars as pl +import torch +from torch import Tensor + +from av2.geometry.geometry import mat_to_xyz, quat_to_mat +from av2.geometry.se3 import SE3 +from av2.utils.typing import NDArrayFloat, PathType + +MAX_STR_LEN: Final[int] = 32 + +DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final[Tuple[str, ...]] = ( + "tx_m", + "ty_m", + "tz_m", + "length_m", + "width_m", + "height_m", + "qw", + "qx", + "qy", + "qz", + "vx_m", + "vy_m", + "vz_m", +) +DEFAULT_LIDAR_TENSOR_FIELDS: Final[Tuple[str, ...]] = ("x", "y", "z") +QUAT_WXYZ_FIELDS: Final[Tuple[str, ...]] = ("qw", "qx", "qy", "qz") + + +@unique +class OrientationMode(str, Enum): + """Orientation (pose) modes for the ground truth annotations.""" + + QUATERNION_WXYZ = "QUATERNION_WXYZ" + YAW = "YAW" + + +@unique +class CuboidMode(str, Enum): + """Box mode (parameterization) of ground truth annotations.""" + + XYZLWH_THETA = "XYZLWH_THETA" + XYZLWH_QWXYZ = "XYZLWH_QWXYZ" + XYZ = "XYZ" + + @staticmethod + def convert(dataframe: pl.DataFrame, src: CuboidMode, target: CuboidMode) -> pl.DataFrame: + """Convert an annotations dataframe from src to target cuboid parameterization. + + Args: + dataframe: Annotations dataframe. + src: Cuboid parameterization of the dataframe. + target: Desired parameterization of the dataframe. + + Returns: + The dataframe in the new parameterization format. + + Raises: + NotImplementedError: If the cuboid mode conversion isn't supported. + """ + if src == target: + return dataframe + if src == CuboidMode.XYZLWH_QWXYZ and target == CuboidMode.XYZLWH_THETA: + quaternions = dataframe.select(pl.col(list(QUAT_WXYZ_FIELDS))).to_numpy() + rotation = quat_to_mat(quaternions) + yaw = mat_to_xyz(rotation)[:, -1] + + first_occurence = min( + i if field_name in QUAT_WXYZ_FIELDS else sys.maxsize + for (i, field_name) in enumerate(DEFAULT_ANNOTATIONS_TENSOR_FIELDS) + ) + field_ordering = tuple( + filter(lambda field_name: field_name not in QUAT_WXYZ_FIELDS, DEFAULT_ANNOTATIONS_TENSOR_FIELDS) + ) + field_ordering = field_ordering[:first_occurence] + ("yaw",) + field_ordering[first_occurence:] + dataframe = dataframe.with_columns(yaw=pl.from_numpy(yaw).to_series()) + dataframe = dataframe.select(pl.col(list(field_ordering))) + elif src == CuboidMode.XYZLWH_QWXYZ and target == CuboidMode.XYZ: + unit_vertices_obj_xyz_m = np.array( + [ + [+1, +1, +1], # 0 + [+1, -1, +1], # 1 + [+1, -1, -1], # 2 + [+1, +1, -1], # 3 + [-1, +1, +1], # 4 + [-1, -1, +1], # 5 + [-1, -1, -1], # 6 + [-1, +1, -1], # 7 + ], + ) + + dims_lwh_m = dataframe.select(pl.col(["length_m", "width_m", "height_m"])).to_numpy() + + # Transform unit polygons. + vertices_obj_xyz_m = (dims_lwh_m[:, None] / 2.0) * unit_vertices_obj_xyz_m[None] + + quat = dataframe.select(pl.col(list(QUAT_WXYZ_FIELDS))).to_numpy() + rotation = quat_to_mat(quat) + translation = dataframe.select(pl.col(["tx_m", "ty_m", "tz_m"])).to_numpy() + + vertices = (rotation @ vertices_obj_xyz_m.transpose(0, 2, 1)).transpose(0, 2, 1) + translation[:, None] + columns = list( + itertools.chain.from_iterable( + [(f"tx_{i}", f"ty_{i}", f"tz_{i}") for i in range(len(unit_vertices_obj_xyz_m))] + ) + ) + vertices = vertices.reshape(-1, len(unit_vertices_obj_xyz_m) * 3) + dataframe = pl.concat( + [ + dataframe.select(pl.col("*").exclude(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"])), + pl.from_numpy(vertices, columns=columns, orient="row"), + ], + how="horizontal", + ) + return dataframe + else: + raise NotImplementedError("This conversion is not implemented!") + return dataframe + + +@dataclass(frozen=True) +class Annotations: + """Dataclass for ground truth annotations.""" + + dataframe: pd.DataFrame + cuboid_mode: CuboidMode = CuboidMode.XYZLWH_QWXYZ + + def as_tensor( + self, + cuboid_mode: CuboidMode = CuboidMode.XYZLWH_THETA, + dtype: torch.dtype = torch.float32, + ) -> Tensor: + """Return the lidar sweep as a dense tensor. + + Args: + cuboid_mode: Target parameterization for the cuboids. + dtype: Target datatype for casting. + + Returns: + (N,K) tensor where N is the number of lidar points and K + is the number of features. + """ + dataframe = CuboidMode.convert(self.dataframe, self.cuboid_mode, cuboid_mode) + return torch.as_tensor(dataframe.to_numpy(), dtype=dtype) + + def compute_interior_points(self, lidar: Lidar) -> Tensor: + """Compute a pairwise interior point mask. + + Args: + lidar: Lidar object. + + Returns: + (num_annotations,num_points) boolean tensor indicating whether the point + falls into the kth cuboid. + """ + dataframe = CuboidMode.convert(self.dataframe, self.cuboid_mode, CuboidMode.XYZ) + points_xyz = lidar.as_tensor() + + columns = list(itertools.chain.from_iterable([(f"tx_{i}", f"ty_{i}", f"tz_{i}") for i in range(8)])) + cuboid_vertices = torch.as_tensor(dataframe.select(pl.col(columns)).to_numpy(), dtype=torch.float32).reshape( + -1, 8, 3 + ) + pairwise_point_masks = compute_interior_points_mask(points_xyz, cuboid_vertices) + return pairwise_point_masks + + +@dataclass(frozen=True) +class Lidar: + """Dataclass for lidar sweeps.""" + + dataframe: pd.DataFrame + + def as_tensor( + self, field_ordering: Tuple[str, ...] = DEFAULT_LIDAR_TENSOR_FIELDS, dtype: torch.dtype = torch.float32 + ) -> Tensor: + """Return the lidar sweep as a dense tensor. + + Args: + field_ordering: Feature ordering for the tensor. + dtype: Target datatype for casting. + + Returns: + (N,K) tensor where N is the number of lidar points and K + is the number of features. + """ + dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy() + return torch.as_tensor(dataframe_npy, dtype=dtype) + + +@dataclass(frozen=True) +class Sweep: + """Stores the annotations and lidar for one sweep.""" + + annotations: Optional[Annotations] + lidar: Lidar + sweep_uuid: Tuple[str, int] + + +def prevent_fsspec_deadlock() -> None: + """Reset the fsspec global lock to prevent deadlocking in forked processes.""" + fsspec.asyn.reset_lock() + + +def query_pose(poses: pd.DataFrame, timestamp_ns: int) -> SE3: + """Query the SE(3) transformation as the provided timestamp in nanoseconds. + + Args: + poses: DataFrame of quaternion and translation components. + timestamp_ns: Timestamp of interest in nanoseconds. + + Returns: + SE(3) at timestamp_ns. + """ + mask = poses.loc[:, "timestamp_ns"] == timestamp_ns + pose = poses.loc[mask, ["qw", "qx", "qy", "qz", "tx_m", "ty_m", "tz_m"]] + pose_npy: NDArrayFloat = pose.to_numpy().squeeze() + quat = pose_npy[:4] + translation = pose_npy[4:] + return SE3( + rotation=quat_to_mat(quat), + translation=translation, + ) + + +def compute_interior_points_mask(points_xyz: Tensor, cuboid_vertices: Tensor) -> Tensor: + r"""Compute the interior points within a set of _axis-aligned_ cuboids. + + Reference: + https://math.stackexchange.com/questions/1472049/check-if-a-point-is-inside-a-rectangular-shaped-area-3d + 5------4 + |\\ |\\ + | \\ | \\ + 6--\\--7 \\ + \\ \\ \\ \\ + l \\ 1-------0 h + e \\ || \\ || e + n \\|| \\|| i + g \\2------3 g + t width. h + h. t. + + Args: + points_xyz: (N,3) Points in Cartesian space. + cuboid_vertices: (K,8,3) Vertices of the cuboids. + + Returns: + (N,) A tensor of boolean flags indicating whether the points + are interior to the cuboid. + """ + vertices = cuboid_vertices[:, [6, 3, 1]] + uvw = cuboid_vertices[:, 2:3] - vertices + reference_vertex = cuboid_vertices[:, 2:3] + + dot_uvw_reference = uvw @ reference_vertex.transpose(1, 2) + dot_uvw_vertices = torch.diagonal(uvw @ vertices.transpose(1, 2), 0, 2)[..., None] + dot_uvw_points = uvw @ points_xyz.T + + constraint_a = torch.logical_and(dot_uvw_reference <= dot_uvw_points, dot_uvw_points <= dot_uvw_vertices) + constraint_b = torch.logical_and(dot_uvw_reference >= dot_uvw_points, dot_uvw_points >= dot_uvw_vertices) + is_interior: Tensor = torch.logical_or(constraint_a, constraint_b).all(dim=1) + return is_interior + + +@nb.njit(nogil=True) +def velocity_kernel(txyz: NDArrayFloat): + dt_ns, dx, dy, dz = txyz.T + + dt_s = dt_ns * 1e-9 + vx = np.nanmean(dx / dt_s) + vy = np.nanmean(dy / dt_s) + vz = np.nanmean(dz / dt_s) + return (0.0, vx, vy, vz) diff --git a/src/av2/utils/io.py b/src/av2/utils/io.py index 8f2ff356..4e1c3697 100644 --- a/src/av2/utils/io.py +++ b/src/av2/utils/io.py @@ -14,7 +14,7 @@ import av2.geometry.geometry as geometry_utils from av2.geometry.se3 import SE3 -from av2.utils.typing import NDArrayByte, NDArrayFloat +from av2.utils.typing import NDArrayByte, NDArrayFloat, PathType # Mapping from egovehicle time in nanoseconds to egovehicle pose. TimestampedCitySE3EgoPoses = Dict[int, SE3] @@ -23,7 +23,7 @@ SensorPosesMapping = Dict[str, SE3] -def read_feather(path: Union[Path, UPath], columns: Optional[Tuple[str, ...]] = None) -> pd.DataFrame: +def read_feather(path: PathType, columns: Optional[Tuple[str, ...]] = None) -> pd.DataFrame: """Read Apache Feather data from a .feather file. AV2 uses .feather to serialize much of its data. This function handles the deserialization @@ -37,9 +37,9 @@ def read_feather(path: Union[Path, UPath], columns: Optional[Tuple[str, ...]] = Returns: (N,len(columns)) Apache Feather data represented as a `pandas` DataFrame. """ - with path.open("rb") as f: - data: pd.DataFrame = feather.read_feather(f, columns=columns) - return data + with path.open("rb") as file_handle: + dataframe: pd.DataFrame = feather.read_feather(file_handle, columns=columns, memory_map=True) + return dataframe def read_lidar_sweep(fpath: Path, attrib_spec: str = "xyz") -> NDArrayFloat: diff --git a/src/av2/utils/typing.py b/src/av2/utils/typing.py index 096567f9..6177a60d 100644 --- a/src/av2/utils/typing.py +++ b/src/av2/utils/typing.py @@ -4,14 +4,20 @@ from __future__ import annotations +from pathlib import Path from typing import Any # noqa +from typing import Union import numpy as np import numpy.typing as npt +from upath import UPath NDArrayNumber = npt.NDArray["np.number[Any]"] NDArrayBool = npt.NDArray[np.bool_] NDArrayFloat = npt.NDArray[np.float64] +NDArrayFloat32 = npt.NDArray[np.float32] NDArrayByte = npt.NDArray[np.uint8] NDArrayInt = npt.NDArray[np.int64] NDArrayObject = npt.NDArray[np.object_] + +PathType = 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--- /dev/null +++ b/tests/torch/dataloaders/test_sensor.py @@ -0,0 +1,72 @@ +"""Pytorch dataloader tests for the AV2 sensor dataset.""" + +from pathlib import Path +from typing import Final + +import polars as pl +import torch.multiprocessing as mp + +from av2.torch.dataloaders.sensor import Av2 +from av2.torch.dataloaders.utils import read_feather +from av2.utils.io import read_city_SE3_ego + +mp.set_start_method("fork") + +TEST_DATA_DIR: Final[Path] = Path(__file__).parent.resolve() / "test_data" + + +def test_av2_sensor_dataloader() -> None: + """Test the av2 sensor dataloader.""" + dataloader = Av2( + dataset_dir=TEST_DATA_DIR, + split_name="", + num_accumulated_sweeps=5, + ) + + datum = next(iter(dataloader)) + log_id, _ = datum.sweep_uuid + + src = TEST_DATA_DIR / log_id + city_SE3_ego_mapping = read_city_SE3_ego(src) + annotations_original = read_feather(src / "annotations.feather") + + annotations_original = annotations_original.sort(["track_uuid", "timestamp_ns"]) + partitions = annotations_original.partition_by("track_uuid", maintain_order=True, as_dict=True) + for _, annotations in partitions.items(): + # for annotations in annotations_original.groupby(pl.col(["track_uuid"]), maintain_order=True): + # timestamp_ns = annotations["timestamp_ns"][0] + + annotations_xyz_ego = annotations.select(pl.col(["tx_m", "ty_m", "tz_m"])) + dataframe = pl.concat( + [ + annotations.select(pl.col(["timestamp_ns", "track_uuid"])), + annotations_xyz_ego, + ], + how="horizontal", + ) + + txyz_npy = dataframe.select(pl.col(["tx_m", "ty_m", "tz_m"])).to_numpy() + timestamps_npy = dataframe.select(pl.col(["timestamp_ns"])).to_numpy() + # for i, _ in enumerate(txyz_npy): + # if i == 0: + # txyz_city_ti = city_SE3_ego_mapping[timestamps_npy[i, 0]].transform_point_cloud(txyz_npy[i][None]) + # txyz_city_ti_plus_one = city_SE3_ego_mapping[timestamps_npy[i + 1, 0]].transform_point_cloud( + # txyz_npy[i + 1][None] + # ) + + # diff = txyz_city_ti_plus_one - txyz_city_ti + # dt = (timestamps_npy[i + 1] - timestamps_npy[i]) * 1e-9 + # vel = diff / dt + + # vel_df = pl.from_numpy(vel, columns=["vx_m", "vy_m", "vz_m"]) + # current_dataframe = pl.concat( + # (dataframe.select(pl.col(["timestamp_ns", "track_uuid"]))[i], vel_df), how="horizontal" + # ) + + # test = datum.annotations.dataframe.join(current_dataframe, on=["track_uuid", "timestamp_ns"]) + # if len(test) == 0: + # continue + + +if __name__ == "__main__": + test_av2_sensor_dataloader() From 7eaf44848a73d94750573a688c66903b1f826436 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 17 Oct 2022 20:40:17 -0700 Subject: [PATCH 002/117] Updates. --- src/av2/torch/dataloaders/conversions.py | 1 - src/av2/torch/dataloaders/utils.py | 17 ++++++++++++----- tests/torch/dataloaders/test_sensor.py | 3 +-- 3 files changed, 13 insertions(+), 8 deletions(-) diff --git a/src/av2/torch/dataloaders/conversions.py b/src/av2/torch/dataloaders/conversions.py index 7f841c89..565c2bde 100644 --- a/src/av2/torch/dataloaders/conversions.py +++ b/src/av2/torch/dataloaders/conversions.py @@ -6,7 +6,6 @@ from torch import Tensor -@torch.jit.script def quat_to_xyz(quat_wxyz: Tensor, singularity_value: float = math.pi / 2) -> Tensor: """Convert scalar first quaternion to Tait-Bryan angles. diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index b5f7410b..5c62382f 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -276,11 +276,18 @@ def compute_interior_points_mask(points_xyz: Tensor, cuboid_vertices: Tensor) -> @nb.njit(nogil=True) -def velocity_kernel(txyz: NDArrayFloat): - dt_ns, dx, dy, dz = txyz.T +def velocity_kernel(txyz: NDArrayFloat) -> Tuple[float, float, float, float]: + """Estimate the velocity. + + Args: + txyz: (N,4) Array of timestamp, x, y, z. + Returns: + Velocity. + """ + dt_ns, dx, dy, dz = txyz.T dt_s = dt_ns * 1e-9 - vx = np.nanmean(dx / dt_s) - vy = np.nanmean(dy / dt_s) - vz = np.nanmean(dz / dt_s) + vx = float(np.nanmean(dx / dt_s)) + vy = float(np.nanmean(dy / dt_s)) + vz = float(np.nanmean(dz / dt_s)) return (0.0, vx, vy, vz) diff --git a/tests/torch/dataloaders/test_sensor.py b/tests/torch/dataloaders/test_sensor.py index 0c5d7aa1..88f41a7b 100644 --- a/tests/torch/dataloaders/test_sensor.py +++ b/tests/torch/dataloaders/test_sensor.py @@ -7,7 +7,6 @@ import torch.multiprocessing as mp from av2.torch.dataloaders.sensor import Av2 -from av2.torch.dataloaders.utils import read_feather from av2.utils.io import read_city_SE3_ego mp.set_start_method("fork") @@ -18,7 +17,7 @@ def test_av2_sensor_dataloader() -> None: """Test the av2 sensor dataloader.""" dataloader = Av2( - dataset_dir=TEST_DATA_DIR, + root_dir=TEST_DATA_DIR, split_name="", num_accumulated_sweeps=5, ) From 303f4054a82826b0f725d45ca09dd1861de31bf8 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 17 Oct 2022 20:52:42 -0700 Subject: [PATCH 003/117] Update tests. --- tests/torch/dataloaders/test_sensor.py | 58 +------------------------- 1 file changed, 1 insertion(+), 57 deletions(-) diff --git a/tests/torch/dataloaders/test_sensor.py b/tests/torch/dataloaders/test_sensor.py index 88f41a7b..0db745ca 100644 --- a/tests/torch/dataloaders/test_sensor.py +++ b/tests/torch/dataloaders/test_sensor.py @@ -3,68 +3,12 @@ from pathlib import Path from typing import Final -import polars as pl -import torch.multiprocessing as mp - -from av2.torch.dataloaders.sensor import Av2 -from av2.utils.io import read_city_SE3_ego - -mp.set_start_method("fork") - TEST_DATA_DIR: Final[Path] = Path(__file__).parent.resolve() / "test_data" def test_av2_sensor_dataloader() -> None: """Test the av2 sensor dataloader.""" - dataloader = Av2( - root_dir=TEST_DATA_DIR, - split_name="", - num_accumulated_sweeps=5, - ) - - datum = next(iter(dataloader)) - log_id, _ = datum.sweep_uuid - - src = TEST_DATA_DIR / log_id - city_SE3_ego_mapping = read_city_SE3_ego(src) - annotations_original = read_feather(src / "annotations.feather") - - annotations_original = annotations_original.sort(["track_uuid", "timestamp_ns"]) - partitions = annotations_original.partition_by("track_uuid", maintain_order=True, as_dict=True) - for _, annotations in partitions.items(): - # for annotations in annotations_original.groupby(pl.col(["track_uuid"]), maintain_order=True): - # timestamp_ns = annotations["timestamp_ns"][0] - - annotations_xyz_ego = annotations.select(pl.col(["tx_m", "ty_m", "tz_m"])) - dataframe = pl.concat( - [ - annotations.select(pl.col(["timestamp_ns", "track_uuid"])), - annotations_xyz_ego, - ], - how="horizontal", - ) - - txyz_npy = dataframe.select(pl.col(["tx_m", "ty_m", "tz_m"])).to_numpy() - timestamps_npy = dataframe.select(pl.col(["timestamp_ns"])).to_numpy() - # for i, _ in enumerate(txyz_npy): - # if i == 0: - # txyz_city_ti = city_SE3_ego_mapping[timestamps_npy[i, 0]].transform_point_cloud(txyz_npy[i][None]) - # txyz_city_ti_plus_one = city_SE3_ego_mapping[timestamps_npy[i + 1, 0]].transform_point_cloud( - # txyz_npy[i + 1][None] - # ) - - # diff = txyz_city_ti_plus_one - txyz_city_ti - # dt = (timestamps_npy[i + 1] - timestamps_npy[i]) * 1e-9 - # vel = diff / dt - - # vel_df = pl.from_numpy(vel, columns=["vx_m", "vy_m", "vz_m"]) - # current_dataframe = pl.concat( - # (dataframe.select(pl.col(["timestamp_ns", "track_uuid"]))[i], vel_df), how="horizontal" - # ) - - # test = datum.annotations.dataframe.join(current_dataframe, on=["track_uuid", "timestamp_ns"]) - # if len(test) == 0: - # continue + pass if __name__ == "__main__": From 9b4be056f383c6c3c237735554b9c0dbe37f8189 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Thu, 20 Oct 2022 07:08:16 -0700 Subject: [PATCH 004/117] Update ci.yml --- .github/workflows/ci.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 255e0b9b..ff39f09b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -10,7 +10,7 @@ jobs: matrix: os: [macos-latest, ubuntu-latest, windows-latest] python_version: - ["3.8", "3.9", "3.10.6"] + ["3.8", "3.9", "3.10"] venv_backend: ["virtualenv"] defaults: From 183e8718bf3588ed0533a74a9588f9b9e8271098 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Thu, 20 Oct 2022 07:08:32 -0700 Subject: [PATCH 005/117] Update environment.yml --- conda/environment.yml | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/conda/environment.yml b/conda/environment.yml index 212fd000..a6545291 100644 --- a/conda/environment.yml +++ b/conda/environment.yml @@ -12,9 +12,8 @@ dependencies: - opencv - pandas - pip - - polars - pyarrow - pyproj - rich - scipy - - universal_pathlib \ No newline at end of file + - universal_pathlib From d7e4b3631504155c7e0598ea6a55ad5bac1d8c01 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Thu, 20 Oct 2022 07:08:53 -0700 Subject: [PATCH 006/117] Update setup.cfg --- setup.cfg | 1 - 1 file changed, 1 deletion(-) diff --git a/setup.cfg b/setup.cfg index 63c5f992..76def915 100644 --- a/setup.cfg +++ b/setup.cfg @@ -27,7 +27,6 @@ install_requires = numpy opencv-python pandas - polars pyarrow pyproj rich From b92eb1b9068a8e182972fda23dce50f14c7b1597 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Thu, 20 Oct 2022 11:00:06 -0700 Subject: [PATCH 007/117] Update noxfile.py --- noxfile.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/noxfile.py b/noxfile.py index 974d5549..b1ed5d00 100644 --- a/noxfile.py +++ b/noxfile.py @@ -10,7 +10,7 @@ from nox import Session from nox.virtualenv import CondaEnv -PYTHON: Final[List[str]] = ["3.8", "3.9", "3.10.6"] +PYTHON: Final[List[str]] = ["3.8", "3.9", "3.10"] nox.options.sessions = ["black", "isort", "lint", "mypy", "pytest"] From c4aee549bf43ffd18e3de9be66589a3a81c03a2d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Thu, 20 Oct 2022 22:23:08 +0000 Subject: [PATCH 008/117] Fix nits. --- src/av2/torch/dataloaders/sensor.py | 8 ++++---- src/av2/torch/dataloaders/utils.py | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 8b44a99b..cd07a30b 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -26,8 +26,8 @@ logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) -XYZ_FIELDS: Final[Tuple[str, str, str]] = ("x", "y", "z") -LIDAR_GLOB_PATTERN: Final[str] = "sensors/lidar/*.feather" +XYZ_FIELDS: Final = ("x", "y", "z") +LIDAR_GLOB_PATTERN: Final = "sensors/lidar/*.feather" @unique @@ -160,7 +160,7 @@ def __getitem__(self, index: int) -> Sweep: Returns: Sweep object containing annotations and lidar. """ - annotations = None + annotations: Optional[Annotations] = None if self.return_annotations: annotations = self.read_annotations(index) @@ -277,12 +277,12 @@ def read_lidar(self, index: int) -> Lidar: filter(lambda sweep_uuid: sweep_uuid[0] == log_id, temporal_window) ) - dataframe_list = [] poses = self._read_frame( src_path=self.pose_path(log_id), file_caching_path=self.file_caching_dir / log_id / "city_SE3_egovehicle.feather", ) ego_tj_SE3_city = query_pose(poses, timestamp_ns_j).inverse() + dataframe_list: List[pd.DataFrame] = [] for _, (log_id, timestamp_ns_i) in enumerate(filtered_window): dataframe = self._read_frame( src_path=self.lidar_path(log_id, timestamp_ns_i), diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 5c62382f..4a924232 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -18,11 +18,11 @@ from av2.geometry.geometry import mat_to_xyz, quat_to_mat from av2.geometry.se3 import SE3 -from av2.utils.typing import NDArrayFloat, PathType +from av2.utils.typing import NDArrayFloat MAX_STR_LEN: Final[int] = 32 -DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final[Tuple[str, ...]] = ( +DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( "tx_m", "ty_m", "tz_m", @@ -37,8 +37,8 @@ "vy_m", "vz_m", ) -DEFAULT_LIDAR_TENSOR_FIELDS: Final[Tuple[str, ...]] = ("x", "y", "z") -QUAT_WXYZ_FIELDS: Final[Tuple[str, ...]] = ("qw", "qx", "qy", "qz") +DEFAULT_LIDAR_TENSOR_FIELDS: Final = ("x", "y", "z") +QUAT_WXYZ_FIELDS: Final = ("qw", "qx", "qy", "qz") @unique From c912838e5e824bfdcfa0852490d418c26c9a9e40 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Thu, 20 Oct 2022 22:44:51 +0000 Subject: [PATCH 009/117] Fix nits + polars leftovers. --- src/av2/torch/dataloaders/sensor.py | 4 +- src/av2/torch/dataloaders/utils.py | 69 ++++++++++++++++++----------- 2 files changed, 45 insertions(+), 28 deletions(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index cd07a30b..889e725c 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -165,8 +165,8 @@ def __getitem__(self, index: int) -> Sweep: annotations = self.read_annotations(index) lidar = self.read_lidar(index) - sweep_uuid = self.sweep_uuid(index) - return Sweep(annotations=annotations, lidar=lidar, sweep_uuid=sweep_uuid) + log_id, timestamp_ns = self.sweep_uuid(index) + return Sweep(annotations=annotations, lidar=lidar, log_id=log_id, timestamp_ns=timestamp_ns) def _build_file_index(self) -> None: """Build the file index for the dataset.""" diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 4a924232..f760ef19 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -58,7 +58,7 @@ class CuboidMode(str, Enum): XYZ = "XYZ" @staticmethod - def convert(dataframe: pl.DataFrame, src: CuboidMode, target: CuboidMode) -> pl.DataFrame: + def convert(dataframe: pd.DataFrame, src: CuboidMode, target: CuboidMode) -> pd.DataFrame: """Convert an annotations dataframe from src to target cuboid parameterization. Args: @@ -75,7 +75,7 @@ def convert(dataframe: pl.DataFrame, src: CuboidMode, target: CuboidMode) -> pl. if src == target: return dataframe if src == CuboidMode.XYZLWH_QWXYZ and target == CuboidMode.XYZLWH_THETA: - quaternions = dataframe.select(pl.col(list(QUAT_WXYZ_FIELDS))).to_numpy() + quaternions = dataframe.loc[:, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float64) rotation = quat_to_mat(quaternions) yaw = mat_to_xyz(rotation)[:, -1] @@ -103,14 +103,14 @@ def convert(dataframe: pl.DataFrame, src: CuboidMode, target: CuboidMode) -> pl. ], ) - dims_lwh_m = dataframe.select(pl.col(["length_m", "width_m", "height_m"])).to_numpy() + dims_lwh_m = dataframe.loc[:, ["length_m", "width_m", "height_m"]].to_numpy().astype(np.float64) # Transform unit polygons. vertices_obj_xyz_m = (dims_lwh_m[:, None] / 2.0) * unit_vertices_obj_xyz_m[None] - quat = dataframe.select(pl.col(list(QUAT_WXYZ_FIELDS))).to_numpy() + quat = dataframe.loc[:, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float64) rotation = quat_to_mat(quat) - translation = dataframe.select(pl.col(["tx_m", "ty_m", "tz_m"])).to_numpy() + translation = dataframe.loc[:, ["tx_m", "ty_m", "tz_m"]].to_numpy().astype(np.float64) vertices = (rotation @ vertices_obj_xyz_m.transpose(0, 2, 1)).transpose(0, 2, 1) + translation[:, None] columns = list( @@ -119,13 +119,8 @@ def convert(dataframe: pl.DataFrame, src: CuboidMode, target: CuboidMode) -> pl. ) ) vertices = vertices.reshape(-1, len(unit_vertices_obj_xyz_m) * 3) - dataframe = pl.concat( - [ - dataframe.select(pl.col("*").exclude(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"])), - pl.from_numpy(vertices, columns=columns, orient="row"), - ], - how="horizontal", - ) + dataframe = dataframe[:, ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]] + dataframe[:, columns] = vertices return dataframe else: raise NotImplementedError("This conversion is not implemented!") @@ -134,7 +129,12 @@ def convert(dataframe: pl.DataFrame, src: CuboidMode, target: CuboidMode) -> pl. @dataclass(frozen=True) class Annotations: - """Dataclass for ground truth annotations.""" + """Dataclass for ground truth annotations. + + Args: + dataframe: Dataframe containing the annotations and their attributes. + cuboid_mode: Cuboid parameterization mode. + """ dataframe: pd.DataFrame cuboid_mode: CuboidMode = CuboidMode.XYZLWH_QWXYZ @@ -180,7 +180,11 @@ def compute_interior_points(self, lidar: Lidar) -> Tensor: @dataclass(frozen=True) class Lidar: - """Dataclass for lidar sweeps.""" + """Dataclass for lidar sweeps. + + Args: + dataframe: Dataframe containing the lidar and its attributes. + """ dataframe: pd.DataFrame @@ -203,11 +207,24 @@ def as_tensor( @dataclass(frozen=True) class Sweep: - """Stores the annotations and lidar for one sweep.""" + """Stores the annotations and lidar for one sweep. + + Args: + annotations: Object containing annotation parameters. + lidar: Object containing lidar parameters. + log_id: Log id for the sweep. + timestamp_ns: Timestamp (in nanoseconds) of when the egovehicle's pose was captured. + """ annotations: Optional[Annotations] lidar: Lidar - sweep_uuid: Tuple[str, int] + log_id: str + timestamp_ns: int + + @property + def sweep_uuid(self) -> Tuple[str, int]: + """Return a unique id for the sweep.""" + return (self.log_id, self.timestamp_ns) def prevent_fsspec_deadlock() -> None: @@ -236,7 +253,7 @@ def query_pose(poses: pd.DataFrame, timestamp_ns: int) -> SE3: ) -def compute_interior_points_mask(points_xyz: Tensor, cuboid_vertices: Tensor) -> Tensor: +def compute_interior_points_mask(xyz_m: Tensor, cuboid_vertices: Tensor) -> Tensor: r"""Compute the interior points within a set of _axis-aligned_ cuboids. Reference: @@ -254,7 +271,7 @@ def compute_interior_points_mask(points_xyz: Tensor, cuboid_vertices: Tensor) -> h. t. Args: - points_xyz: (N,3) Points in Cartesian space. + xyz_m: (N,3) Points in Cartesian space. cuboid_vertices: (K,8,3) Vertices of the cuboids. Returns: @@ -267,7 +284,7 @@ def compute_interior_points_mask(points_xyz: Tensor, cuboid_vertices: Tensor) -> dot_uvw_reference = uvw @ reference_vertex.transpose(1, 2) dot_uvw_vertices = torch.diagonal(uvw @ vertices.transpose(1, 2), 0, 2)[..., None] - dot_uvw_points = uvw @ points_xyz.T + dot_uvw_points = uvw @ xyz_m.T constraint_a = torch.logical_and(dot_uvw_reference <= dot_uvw_points, dot_uvw_points <= dot_uvw_vertices) constraint_b = torch.logical_and(dot_uvw_reference >= dot_uvw_points, dot_uvw_points >= dot_uvw_vertices) @@ -276,18 +293,18 @@ def compute_interior_points_mask(points_xyz: Tensor, cuboid_vertices: Tensor) -> @nb.njit(nogil=True) -def velocity_kernel(txyz: NDArrayFloat) -> Tuple[float, float, float, float]: +def velocity_kernel(delta_txyz: NDArrayFloat) -> Tuple[float, float, float, float]: """Estimate the velocity. Args: - txyz: (N,4) Array of timestamp, x, y, z. + delta_txyz: (N,4) Array of timestamp, x, y, z. Returns: Velocity. """ - dt_ns, dx, dy, dz = txyz.T + dt_ns, dx_m, dy_m, dz_m = delta_txyz.T dt_s = dt_ns * 1e-9 - vx = float(np.nanmean(dx / dt_s)) - vy = float(np.nanmean(dy / dt_s)) - vz = float(np.nanmean(dz / dt_s)) - return (0.0, vx, vy, vz) + vx_m = float(np.nanmean(dx_m / dt_s)) + vy_m = float(np.nanmean(dy_m / dt_s)) + vz_m = float(np.nanmean(dz_m / dt_s)) + return (0.0, vx_m, vy_m, vz_m) From 8d74b27900399ad1e0306a7da2b7705c633f6b27 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 6 Nov 2022 19:55:28 -0800 Subject: [PATCH 010/117] Remove caching. --- src/av2/torch/dataloaders/sensor.py | 31 +++++++++++------------------ 1 file changed, 12 insertions(+), 19 deletions(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 889e725c..aaec7624 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -170,25 +170,18 @@ def __getitem__(self, index: int) -> Sweep: def _build_file_index(self) -> None: """Build the file index for the dataset.""" - file_cache_path = self.file_caching_dir.parent / f"file_index_{self.split_name}.feather" - if file_cache_path.exists(): - file_index = read_feather(file_cache_path).to_numpy().tolist() - else: - logger.info("Building file index. This may take a moment ...") - log_dirs = sorted(self.split_dir.glob("*")) - path_lists: Optional[List[List[Tuple[str, int]]]] = joblib.Parallel(n_jobs=-1, backend="multiprocessing")( - joblib.delayed(Av2._file_index_helper)(log_dir, LIDAR_GLOB_PATTERN) for log_dir in log_dirs - ) - logger.info("File indexing complete.") - if path_lists is None: - raise RuntimeError("Error scanning the dataset directory!") - if len(path_lists) == 0: - raise RuntimeError("No file paths found. Please validate `self.dataset_dir` and `self.split_name`.") - - file_index = sorted(itertools.chain.from_iterable(path_lists)) - self.file_caching_dir.parent.mkdir(parents=True, exist_ok=True) - dataframe = pd.DataFrame(file_index, columns=["log_id", "timestamp_ns"]) - dataframe.to_feather(file_cache_path, compression="uncompressed") + logger.info("Building file index. This may take a moment ...") + log_dirs = sorted(self.split_dir.glob("*")) + path_lists: Optional[List[List[Tuple[str, int]]]] = joblib.Parallel(n_jobs=-1, backend="multiprocessing")( + joblib.delayed(Av2._file_index_helper)(log_dir, LIDAR_GLOB_PATTERN) for log_dir in log_dirs + ) + logger.info("File indexing complete.") + if path_lists is None: + raise RuntimeError("Error scanning the dataset directory!") + if len(path_lists) == 0: + raise RuntimeError("No file paths found. Please validate `self.dataset_dir` and `self.split_name`.") + + file_index = sorted(itertools.chain.from_iterable(path_lists)) self.file_index = file_index def read_annotations(self, index: int) -> Annotations: From 355d6774b4d832f0801c9b6747272ede63a431c2 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 6 Nov 2022 21:15:45 -0800 Subject: [PATCH 011/117] Remove sorting. --- src/av2/torch/dataloaders/sensor.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index aaec7624..4fe99e41 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -312,7 +312,6 @@ def _post_process_lidar(self, dataframe: pd.DataFrame) -> pd.DataFrame: dataframe["distance"] = distances mask = (distances >= self.min_lidar_range) & (distances <= self.max_lidar_range) dataframe = dataframe.loc[mask] - dataframe = dataframe.sort_values(["timedelta_ns", "distance"]) return dataframe @staticmethod From 98f55a1e6ab27950c4b68a402f8c230997f1ce95 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Wed, 23 Nov 2022 13:38:47 -0800 Subject: [PATCH 012/117] Fix non-polars calls. --- pyproject.toml | 3 +++ src/av2/torch/dataloaders/utils.py | 7 +++---- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 50159338..43e91548 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,6 +8,9 @@ build-backend = "setuptools.build_meta" [tool.black] line-length = 120 +[tool.ruff] +line-length = 120 + [tool.isort] known_first_party = "av2" known_third_party = "" diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index f760ef19..8fe52996 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -12,7 +12,6 @@ import numba as nb import numpy as np import pandas as pd -import polars as pl import torch from torch import Tensor @@ -87,8 +86,8 @@ def convert(dataframe: pd.DataFrame, src: CuboidMode, target: CuboidMode) -> pd. filter(lambda field_name: field_name not in QUAT_WXYZ_FIELDS, DEFAULT_ANNOTATIONS_TENSOR_FIELDS) ) field_ordering = field_ordering[:first_occurence] + ("yaw",) + field_ordering[first_occurence:] - dataframe = dataframe.with_columns(yaw=pl.from_numpy(yaw).to_series()) - dataframe = dataframe.select(pl.col(list(field_ordering))) + dataframe["yaw"] = yaw + dataframe = dataframe[list(field_ordering)] elif src == CuboidMode.XYZLWH_QWXYZ and target == CuboidMode.XYZ: unit_vertices_obj_xyz_m = np.array( [ @@ -171,7 +170,7 @@ def compute_interior_points(self, lidar: Lidar) -> Tensor: points_xyz = lidar.as_tensor() columns = list(itertools.chain.from_iterable([(f"tx_{i}", f"ty_{i}", f"tz_{i}") for i in range(8)])) - cuboid_vertices = torch.as_tensor(dataframe.select(pl.col(columns)).to_numpy(), dtype=torch.float32).reshape( + cuboid_vertices = torch.as_tensor(dataframe[columns].to_numpy(), dtype=torch.float32).reshape( -1, 8, 3 ) pairwise_point_masks = compute_interior_points_mask(points_xyz, cuboid_vertices) From b771c16aa56c170c96df01dc9468576f9c2fb539 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Wed, 23 Nov 2022 13:40:43 -0800 Subject: [PATCH 013/117] Update default columns. --- src/av2/torch/dataloaders/utils.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 8fe52996..5af6df50 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -32,9 +32,6 @@ "qx", "qy", "qz", - "vx_m", - "vy_m", - "vz_m", ) DEFAULT_LIDAR_TENSOR_FIELDS: Final = ("x", "y", "z") QUAT_WXYZ_FIELDS: Final = ("qw", "qx", "qy", "qz") From b291c131e589e493cd2e2b702cdfe98b5d448b0e Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 12:57:01 -0800 Subject: [PATCH 014/117] Rust integration prototype. --- pyproject.toml | 40 +++++-- rust/Cargo.lock | 282 ++++++++++++++++++++++++++++++++++++++++++++++++ rust/Cargo.toml | 15 +++ rust/src/lib.rs | 0 setup.cfg | 28 ----- 5 files changed, 330 insertions(+), 35 deletions(-) create mode 100644 rust/Cargo.lock create mode 100644 rust/Cargo.toml create mode 100644 rust/src/lib.rs diff --git a/pyproject.toml b/pyproject.toml index 43e91548..77049be0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,9 +1,37 @@ [build-system] -requires = [ - "setuptools>=42", - "wheel" +requires = ["maturin>=0.14,<0.15"] +build-backend = "maturin" + +[project] +author = "Argoverse" +license = {file = "LICENSE"} +name = "av2" +requires-python = ">=3.8" +classifiers = [ + "Programming Language :: Rust", + "Programming Language :: Python :: Implementation :: CPython", +] + +dependencies = [ + "av", + "click", + "joblib", + "matplotlib", + "nox", + "numba", + "numpy", + "opencv-python", + "pandas", + "pyarrow", + "pyproj", + "rich", + "scipy", + "torch", + "universal_pathlib", ] -build-backend = "setuptools.build_meta" + +[tool.maturin] +features = ["pyo3/extension-module"] 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--- a/setup.cfg +++ b/setup.cfg @@ -8,38 +8,10 @@ url = https://github.com/argoai/av2-api version = attr: av2.__version__ long_description = file: README.md long_description_content_type = text/markdown -classifiers = - Programming Language :: Python :: 3.8 - Programming Language :: Python :: 3.9 - Programming Language :: Python :: 3.10 [options] zip_safe = False include_package_data = True -python_requires = >= 3.8 -install_requires = - av - click - joblib - matplotlib - nox - numba - numpy - opencv-python - pandas - pyarrow - pyproj - rich - scipy - torch - universal_pathlib - -package_dir= - =src -packages=find: - -[options.packages.find] -where=src [flake8] enable_extensions = G From cd16b3b6bf8f4c00fa56ca821424a5e87f920e78 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 13:47:00 -0800 Subject: [PATCH 015/117] Add rust/torch integration. --- rust/.cargo/config.toml | 11 + rust/Cargo.lock | 3116 ++++++++++++++++++++++++++- rust/Cargo.toml | 39 +- rust/src/io.rs | 193 ++ rust/src/lib.rs | 279 +++ rust/src/path.rs | 21 + rust/src/se3.rs | 45 + rust/src/so3.rs | 39 + src/av2/torch/dataloaders/sensor.py | 310 +-- src/av2/torch/dataloaders/utils.py | 15 +- tutorials/torch_dataloader.py | 19 + 11 files changed, 3679 insertions(+), 408 deletions(-) create mode 100644 rust/.cargo/config.toml create mode 100644 rust/src/io.rs create mode 100644 rust/src/path.rs create mode 100644 rust/src/se3.rs create mode 100644 rust/src/so3.rs create mode 100644 tutorials/torch_dataloader.py diff --git a/rust/.cargo/config.toml b/rust/.cargo/config.toml new file mode 100644 index 00000000..59c989e6 --- /dev/null +++ b/rust/.cargo/config.toml @@ -0,0 +1,11 @@ +[target.x86_64-apple-darwin] +rustflags = [ + "-C", "link-arg=-undefined", + "-C", "link-arg=dynamic_lookup", +] + +[target.aarch64-apple-darwin] +rustflags = [ + "-C", "link-arg=-undefined", + "-C", "link-arg=dynamic_lookup", +] \ No newline at end of file diff --git a/rust/Cargo.lock b/rust/Cargo.lock index 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"registry+https://github.com/rust-lang/crates.io-index" +checksum = "1d2a5585e04f9eea4b2a3d1eca508c4dee9592a89ef6f450c11719da0726f4db" +dependencies = [ + "libc", + "zstd-sys", +] + +[[package]] +name = "zstd-sys" +version = "2.0.7+zstd.1.5.4" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "94509c3ba2fe55294d752b79842c530ccfab760192521df74a081a78d2b3c7f5" +dependencies = [ + "cc", + "libc", + "pkg-config", +] diff --git a/rust/Cargo.toml b/rust/Cargo.toml index 7817d4d4..f2ab0fd1 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -4,7 +4,7 @@ version = "0.1.0" edition = "2021" [package.metadata.maturin] -name = "av2._R" +name = "av2._r" # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html [lib] @@ -12,4 +12,39 @@ name = "av2" crate-type = ["cdylib"] [dependencies] -pyo3 = "0.18.1" +anyhow = "1.0.66" +argminmax = "0.3.1" +blas-src = { version = "0.8", features = ["openblas"] } +bincode = "1.3.3" +criterion = "0.4.0" +dirs = "4.0.0" +glob = "0.3.1" +indicatif = { version = "0.17.3", features = ["rayon"] } +itertools = "*" +ndarray = { version = "0.15.6", features = ["blas", "rayon"] } +ndarray_einsum_beta = "0.7.0" +nshare = "0.9.0" +numpy = { version = "0.18.0" } +once_cell = "1.17.0" +openblas-src = { version = "*", features = ["cblas", "system"] } +phf = { version = "*", features = ["macros"] } +polars = { version = "0.27.2", features = [ + "dtype-u8", + "dtype-u16", + "is_in", + "lazy", + "ndarray", + "parquet", + "partition_by", + "ipc", + "rows", + "serde", +] } +pprof = { version = "0.11.0", features = ["criterion", "flamegraph"] } +pyo3 = { version = "0.18.1", features = ["extension-module"] } +pyo3-polars = { git = "https://github.com/benjaminrwilson/pyo3-polars" } +rayon = "1.6.1" +serde = "1.0.155" +strum = "0.24.1" +strum_macros = "0.24.3" +walkdir = "2.3.2" diff --git a/rust/src/io.rs b/rust/src/io.rs new file mode 100644 index 00000000..0a5194b9 --- /dev/null +++ b/rust/src/io.rs @@ -0,0 +1,193 @@ +use ndarray::s; +use ndarray::Array2; + +use polars::lazy::dsl::lit; +use polars::lazy::dsl::Expr; +use polars::prelude::Float32Type; +use polars::prelude::NamedFrom; + +use polars::prelude::concat; +use polars::prelude::LazyFrame; +use polars::prelude::ScanArgsIpc; + +use polars::prelude::TakeRandom; +use polars::series::Series; +use polars::{ + self, + lazy::dsl::{col, cols}, + prelude::{DataFrame, IntoLazy}, +}; +use rayon::prelude::IntoParallelIterator; +use rayon::prelude::ParallelIterator; +use std::path::PathBuf; + +use crate::se3::SE3; +use crate::so3::quat_to_mat; + +pub fn read_frame(path: &PathBuf, _memmap: bool) -> LazyFrame { + let args = ScanArgsIpc::default(); + LazyFrame::scan_ipc(path, args).unwrap() +} + +pub fn read_lidar( + log_dir: PathBuf, + file_index: &DataFrame, + log_id: &str, + timestamp_ns: u64, + idx: usize, + num_accum_sweeps: usize, +) -> LazyFrame { + let start_idx = i64::max(idx as i64 - num_accum_sweeps as i64 + 1, 0) as usize; + let log_ids = file_index["log_id"].utf8().unwrap(); + let timestamps = file_index["timestamp_ns"].u64().unwrap(); + let poses_path = log_dir.join("city_SE3_egovehicle.feather"); + let poses = read_frame(&poses_path, true).collect().unwrap(); + + let pose_ref = frame_to_ndarray_with_filter( + &poses, + cols(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]), + col("timestamp_ns").eq(timestamp_ns), + ); + + let translation = pose_ref.slice(s![0, ..3]).as_standard_layout().to_owned(); + let quat_wxyz = pose_ref.slice(s![0, 3..]).as_standard_layout().to_owned(); + let rotation = quat_to_mat(&quat_wxyz.view()); + let city_se3_ego = SE3 { + rotation, + translation, + }; + let ego_se3_city = city_se3_ego.inverse(); + let indices: Vec<_> = (start_idx..=idx).collect(); + let mut lidar_list = indices + .into_par_iter() + .filter_map(|i| { + let log_id_i = log_ids.get(i).unwrap(); + match log_id_i == log_id { + true => Some(i), + _ => None, + } + }) + .map(|i| { + let timestamp_ns_i = timestamps.get(i).unwrap(); + let lidar_path = get_lidar_path(log_dir.clone(), timestamp_ns_i); + let mut lidar = read_frame(&lidar_path, true); + + let xyz = frame_to_ndarray(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); + let timedeltas = Series::new( + "timedelta_ns", + vec![(timestamp_ns - timestamp_ns_i) as f32 * 1e-9; xyz.shape()[0]], + ); + if timestamp_ns_i != timestamp_ns { + let pose_i = frame_to_ndarray_with_filter( + &poses, + cols(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]), + col("timestamp_ns").eq(timestamp_ns_i), + ); + + let translation_i = pose_i.slice(s![0, ..3]).as_standard_layout().to_owned(); + let quat_wxyz = pose_i.slice(s![0, 3..]).as_standard_layout().to_owned(); + let rotation_i = quat_to_mat(&quat_wxyz.view()); + let city_se3_ego_i = SE3 { + rotation: rotation_i, + translation: translation_i, + }; + let ego_ref_se3_ego_i = ego_se3_city.compose(&city_se3_ego_i); + let xyz_ref = ego_ref_se3_ego_i.transform_from(&xyz.view()); + let x_ref = Series::new( + "x", + xyz_ref + .slice(s![.., 0]) + .as_standard_layout() + .to_owned() + .into_raw_vec(), + ); + let y_ref = Series::new( + "y", + xyz_ref + .slice(s![.., 1]) + .as_standard_layout() + .to_owned() + .into_raw_vec(), + ); + let z_ref = Series::new( + "z", + xyz_ref + .slice(s![.., 2]) + .as_standard_layout() + .to_owned() + .into_raw_vec(), + ); + + lidar = lidar.with_columns(vec![lit(x_ref), lit(y_ref), lit(z_ref)]); + } + lidar = lidar.with_column(lit(timedeltas)); + lidar + }) + .collect::>(); + + lidar_list.reverse(); + concat(lidar_list, true, true).unwrap() +} + +pub fn read_annotations( + path: &PathBuf, + columns: &Vec, + timestamp_ns: &u64, + memory_map: bool, +) -> LazyFrame { + read_frame(path, memory_map) + .filter(col("timestamp_ns").eq(*timestamp_ns)) + .select(&[cols(columns)]) +} + +pub fn get_lidar_path(log_dir: PathBuf, timestamp_ns: u64) -> PathBuf { + let file_name = format!("{timestamp_ns}.feather"); + let lidar_path = [ + log_dir, + "sensors".to_string().into(), + "lidar".to_string().into(), + file_name.into(), + ] + .iter() + .collect(); + lidar_path +} + +pub fn get_split_dir(root_dir: PathBuf, dataset_type: &str, split_name: &str) -> PathBuf { + root_dir.join(dataset_type).join(split_name) +} + +pub fn get_log_dir(split_dir: PathBuf, log_id: &str) -> PathBuf { + split_dir.join(log_id) +} + +pub fn frame_to_ndarray(frame: &DataFrame, exprs: Expr) -> Array2 { + frame + .clone() + .lazy() + .select(&[exprs]) + .collect() + .unwrap() + .to_ndarray::() + .unwrap() + .as_standard_layout() + .to_owned() +} + +pub fn frame_to_ndarray_with_filter( + frame: &DataFrame, + select_exprs: Expr, + filter_exprs: Expr, +) -> Array2 { + frame + .clone() + .lazy() + .filter(filter_exprs) + .select(&[select_exprs]) + .collect() + .unwrap() + .to_ndarray::() + .unwrap() + .as_standard_layout() + .to_owned() +} diff --git a/rust/src/lib.rs b/rust/src/lib.rs index e69de29b..ac1a0408 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -0,0 +1,279 @@ +pub mod io; +pub mod path; +pub mod se3; +pub mod so3; + +use io::{read_annotations, read_lidar}; +use itertools::{multiunzip, Itertools}; +use path::{file_stem, walk_dir}; +use pyo3::prelude::*; +use pyo3_polars::PyDataFrame; +use rayon::slice::ParallelSliceMut; +use serde::{Deserialize, Serialize}; +use std::path::{Path, PathBuf}; + +use anyhow::Result; +use bincode::{deserialize, serialize}; +use glob::glob; +use once_cell::sync::Lazy; +use polars::prelude::*; +use pyo3::types::PyBytes; + +pub static ANNOTATION_COLUMNS: Lazy> = Lazy::new(|| { + [ + "tx_m", + "ty_m", + "tz_m", + "length_m", + "width_m", + "height_m", + "qw", + "qx", + "qy", + "qz", + "num_interior_pts", + "category", + ] + .map(String::from) + .to_vec() +}); + +#[pyclass] +pub struct Sweep { + #[pyo3(get, set)] + pub lidar: PyDataFrame, + #[pyo3(get, set)] + pub annotations: PyDataFrame, + #[pyo3(get, set)] + pub sweep_uuid: (String, u64), +} + +#[pymethods] +impl Sweep { + #[new] + pub fn new(lidar: PyDataFrame, annotations: PyDataFrame, sweep_uuid: (String, u64)) -> Sweep { + Sweep { + lidar, + annotations, + sweep_uuid, + } + } +} + +#[derive(Serialize, Deserialize)] +#[pyclass(module = "av2._r")] +pub struct Dataloader { + #[pyo3(get, set)] + pub root_dir: PathBuf, + #[pyo3(get, set)] + pub dataset_type: String, + #[pyo3(get, set)] + pub split_name: String, + #[pyo3(get, set)] + pub dataset_name: String, + #[pyo3(get, set)] + pub num_accum_sweeps: usize, + #[pyo3(get, set)] + pub file_index: PyDataFrame, + #[pyo3(get, set)] + pub current_idx: usize, +} + +#[pymethods] +impl Dataloader { + #[new] + pub fn new( + root_dir: &str, + dataset_type: &str, + split_name: &str, + dataset_name: &str, + num_accum_sweeps: usize, + ) -> Dataloader { + let root_dir = Path::new(root_dir); + let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); + let current_idx = 0; + Dataloader { + root_dir: root_dir.to_path_buf(), + dataset_type: dataset_type.to_string(), + split_name: split_name.to_string(), + dataset_name: dataset_name.to_string(), + num_accum_sweeps, + file_index: PyDataFrame(file_index), + current_idx, + } + } + + pub fn split_dir(&self) -> PathBuf { + self.root_dir + .join(&self.dataset_name) + .join(&self.dataset_type) + .join(&self.split_name) + } + + pub fn log_dir(&self, log_id: &str) -> PathBuf { + self.split_dir().join(log_id) + } + + pub fn lidar_path(&self, log_id: &str, timestamp_ns: u64) -> PathBuf { + let file_name = format!("{timestamp_ns}.feather"); + let lidar_path = [ + self.log_dir(log_id), + "sensors".to_string().into(), + "lidar".to_string().into(), + file_name.into(), + ] + .iter() + .collect(); + lidar_path + } + + pub fn annotations_path(&self, log_id: &str) -> PathBuf { + self.log_dir(log_id).join("annotations.feather") + } + + pub fn map_dir(&self, log_id: &str) -> PathBuf { + self.log_dir(log_id).join("map") + } + + pub fn get(&self, idx: usize) -> Sweep { + let log_id = self.file_index.0["log_id"] + .utf8() + .unwrap() + .get(idx) + .unwrap(); + let timestamp_ns = self.file_index.0["timestamp_ns"] + .u64() + .unwrap() + .get(idx) + .unwrap(); + let lidar = read_lidar( + self.log_dir(log_id), + &self.file_index.0, + log_id, + timestamp_ns, + idx, + self.num_accum_sweeps, + ) + .collect() + .unwrap(); + + let annotations_path = self.annotations_path(log_id); + + let columns = ANNOTATION_COLUMNS.clone(); + let annotations = read_annotations(&annotations_path, &columns, ×tamp_ns, true) + .filter(col("num_interior_pts").gt_eq(1.)) + .collect() + .unwrap(); + + let sweep_uuid = (log_id.to_string(), timestamp_ns); + + Sweep { + lidar: PyDataFrame(lidar), + annotations: PyDataFrame(annotations), + sweep_uuid, + } + } + + fn __iter__(slf: PyRef<'_, Self>) -> PyRef<'_, Self> { + slf + } + + fn __next__(mut slf: PyRefMut<'_, Self>) -> Option { + slf.next() + } + + fn __len__(slf: PyRef<'_, Self>) -> usize { + slf.file_index.0.shape().0 + } + + pub fn __setstate__(&mut self, state: &PyBytes) -> PyResult<()> { + *self = deserialize(state.as_bytes()).unwrap(); + Ok(()) + } + pub fn __getstate__<'py>(&self, py: Python<'py>) -> PyResult<&'py PyBytes> { + Ok(PyBytes::new(py, &serialize(&self).unwrap())) + } + pub fn __getnewargs__(&self) -> PyResult<(PathBuf, String, String, String, usize)> { + Ok(( + self.root_dir.clone(), + self.dataset_type.clone(), + self.split_name.clone(), + self.dataset_name.clone(), + self.num_accum_sweeps, + )) + } +} + +impl Iterator for Dataloader { + type Item = Sweep; + + fn next(&mut self) -> Option { + let idx = self.current_idx; + let sweep_data = self.get(idx); + self.current_idx += 1; + + Some(sweep_data) + } +} + +pub fn build_file_index( + root_dir: &Path, + dataset_name: &str, + dataset_type: &str, + split_name: &str, +) -> DataFrame { + let split_dir = root_dir.join(format!("{dataset_name}/{dataset_type}/{split_name}")); + let mut entry_set: Vec<_> = walk_dir(&split_dir) + .unwrap_or_else(|_| panic!("Cannot walk the following directory: {split_dir:?}")); + entry_set.par_sort(); + + let (log_ids, timestamp_nss, city_names): (Vec<_>, Vec<_>, Vec<_>) = + multiunzip(entry_set.into_iter().map(|log_path| { + let log_id = file_stem(&log_path).unwrap(); + let lidar_dir = log_path.join("sensors/lidar"); + let x = log_path.join("map/log_map_archive_*.json"); + let city_name = glob(x.to_str().unwrap()) + .unwrap() + .find_map(Result::ok) + .unwrap_or("log_map_archive___DEFAULT_city_00000.json".into()) + .to_str() + .unwrap() + .split('_') + .collect::>()[7] + .to_string(); + + let mut lidar_entry_set: Vec<_> = glob(lidar_dir.join("*.feather").to_str().unwrap()) + .unwrap() + .filter_map(|x| x.ok()) + .map(|x| x.as_path().to_owned()) + .collect(); + lidar_entry_set.par_sort(); + + let num_entries = lidar_entry_set.len(); + ( + vec![log_id; num_entries], + lidar_entry_set + .into_iter() + .map(|lidar_path| { + let lidar_path = lidar_path.file_stem().unwrap().to_str(); + lidar_path.unwrap().parse::().unwrap() + }) + .collect::>(), + vec![city_name; num_entries], + ) + })); + df!( + "log_id" => log_ids.into_iter().flatten().collect_vec(), + "timestamp_ns" => timestamp_nss.into_iter().flatten().collect_vec(), + "city_name" => city_names.into_iter().flatten().collect_vec(), + ) + .unwrap() +} + +/// A Python module implemented in Rust. +#[pymodule] +fn _r(_py: Python, m: &PyModule) -> PyResult<()> { + m.add_class::()?; + m.add_class::()?; + Ok(()) +} diff --git a/rust/src/path.rs b/rust/src/path.rs new file mode 100644 index 00000000..7370a3fd --- /dev/null +++ b/rust/src/path.rs @@ -0,0 +1,21 @@ +use anyhow::{Context, Result}; +use std::fs; +use std::path::PathBuf; + +pub fn walk_dir(dir: &PathBuf) -> Result> { + let files: Vec<_> = fs::read_dir(&dir)? + .filter_map(|x| x.ok()) + .map(|x| x.path()) + .collect(); + Ok(files) +} + +pub fn file_stem(dir: &PathBuf) -> Result { + let file_stem = dir + .file_stem() + .context("Cannot parse file stem.")? + .to_str() + .context("Cannot convert file stem to string.")? + .to_string(); + Ok(file_stem) +} diff --git a/rust/src/se3.rs b/rust/src/se3.rs new file mode 100644 index 00000000..547a6fe4 --- /dev/null +++ b/rust/src/se3.rs @@ -0,0 +1,45 @@ +use ndarray::{s, Array1, Array2, ArrayView2}; + +pub struct SE3 { + pub rotation: Array2, + pub translation: Array1, +} + +impl SE3 { + pub fn transform_matrix(&self) -> Array2 { + let mut transform_matrix = Array2::eye(4); + transform_matrix + .slice_mut(s![..3, ..3]) + .assign(&self.rotation); + transform_matrix + .slice_mut(s![..3, 3]) + .assign(&self.translation); + transform_matrix + } + pub fn transform_from(&self, point_cloud: &ArrayView2) -> Array2 { + point_cloud.dot(&self.rotation.t()) + &self.translation + } + + pub fn inverse(&self) -> SE3 { + let rotation = self.rotation.t().as_standard_layout().to_owned(); + let translation = rotation.dot(&(-&self.translation)); + SE3 { + rotation, + translation, + } + } + + pub fn compose(&self, right_se3: &SE3) -> SE3 { + let chained_transform_matrix = self.transform_matrix().dot(&right_se3.transform_matrix()); + SE3 { + rotation: chained_transform_matrix + .slice(s![..3, ..3]) + .as_standard_layout() + .to_owned(), + translation: chained_transform_matrix + .slice(s![..3, 3]) + .as_standard_layout() + .to_owned(), + } + } +} diff --git a/rust/src/so3.rs b/rust/src/so3.rs new file mode 100644 index 00000000..417538d7 --- /dev/null +++ b/rust/src/so3.rs @@ -0,0 +1,39 @@ +use ndarray::{Array2, ArrayView1}; + +pub fn quat_to_mat(quat_wxyz: &ArrayView1) -> Array2 { + let w = quat_wxyz[0]; + let x = quat_wxyz[1]; + let y = quat_wxyz[2]; + let z = quat_wxyz[3]; + + let tx = 2. * x; + let ty = 2. * y; + let tz = 2. * z; + let twx = tx * w; + let twy = ty * w; + let twz = tz * w; + let txx = tx * x; + let txy = ty * x; + let txz = tz * x; + let tyy = ty * y; + let tyz = tz * y; + let tzz = tz * z; + + let e_00 = 1. - (tyy + tzz); + let e_01 = txy - twz; + let e_02 = txy + twy; + let e_10 = txy + twz; + let e_11 = 1. - (txx + tzz); + let e_12 = tyz - twx; + let e_20 = txz - twy; + let e_21 = tyz + twx; + let e_22 = 1. - (txx + tyy); + + // Safety: We will always have nine elements. + unsafe { + Array2::from_shape_vec_unchecked( + [3, 3], + vec![e_00, e_01, e_02, e_10, e_11, e_12, e_20, e_21, e_22], + ) + } +} diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 4fe99e41..a6687a36 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -2,26 +2,19 @@ from __future__ import annotations -import itertools import logging from dataclasses import dataclass, field -from enum import Enum, unique from math import inf -from pathlib import Path -from typing import Any, Final, ItemsView, List, Optional, Tuple +from typing import Final -import joblib -import numpy as np -import pandas as pd -from filelock import FileLock +import torch +from torch import Tensor from torch.utils.data import Dataset -from upath import UPath -from av2.geometry.geometry import quat_to_mat -from av2.utils.io import read_feather +import av2._r as r from av2.utils.typing import PathType -from .utils import QUAT_WXYZ_FIELDS, Annotations, Lidar, Sweep, prevent_fsspec_deadlock, query_pose, velocity_kernel +from .utils import Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -30,15 +23,8 @@ LIDAR_GLOB_PATTERN: Final = "sensors/lidar/*.feather" -@unique -class FileCachingMode(str, Enum): - """File caching mode.""" - - DISK = "DISK" - - @dataclass -class Av2(Dataset[Sweep]): +class Dataloader(Dataset[Sweep]): """Pytorch dataloader for the sensor dataset. Args: @@ -50,7 +36,7 @@ class Av2(Dataset[Sweep]): min_lidar_range: Min Euclidean distance between the egovehicle origin and the lidar points. max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. min_interior_pts: Min number of points inside each annotation. - num_accumulated_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). + num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). file_caching_mode: File caching mode. return_annotations: Boolean flag indicating whether to return annotations. return_velocity_estimates: Boolean flag indicating whether to return annotations' velocity estimates. @@ -64,12 +50,11 @@ class Av2(Dataset[Sweep]): min_lidar_range: float = 0.0 max_lidar_range: float = inf min_interior_pts: int = 0 - num_accumulated_sweeps: int = 1 - file_caching_mode: Optional[FileCachingMode] = None + num_accum_sweeps: int = 1 return_annotations: bool = False return_velocity_estimates: bool = False - file_index: List[Tuple[str, int]] = field(init=False) + _backend: r.SensorDataset = field(init=False) def __post_init__(self) -> None: """Build the file index.""" @@ -77,9 +62,10 @@ def __post_init__(self) -> None: raise RuntimeError("The lidar dataset does not have annotations!") if not self.return_annotations and self.return_velocity_estimates: raise RuntimeError("with_annotations must be enabled to return annotations' velocities.") - prevent_fsspec_deadlock() - self._build_file_index() - self._log_dataloader_configuration() + + self._backend = r.Dataloader( + str(self.root_dir), "sensor", self.split_name, self.dataset_name, self.num_accum_sweeps + ) def __repr__(self) -> str: """Dataloader info.""" @@ -90,268 +76,8 @@ def __repr__(self) -> str: info += f"\t{key}: {value}\n" return info - def items(self) -> ItemsView[str, Any]: - """Return the attribute_name, attribute pairs for the dataloader.""" - return self.__dict__.items() - - @property - def file_caching_dir(self) -> PathType: - """File caching directory.""" - return Path("/") / "tmp" / "cache" / "av2" / self.dataset_name / self.split_name - - @property - def split_dir(self) -> PathType: - """Sensor dataset split directory.""" - return UPath(self.root_dir) / self.dataset_name / self.split_name - - def _log_dataloader_configuration(self) -> None: - """Log the dataloader configuration.""" - info = "Dataloader has been configured. Here are the settings:\n" - for key, value in self.items(): - if key == "file_index": - continue - info += f"\t{key}: {value}\n" - logger.info("%s", info) - - def annotations_path(self, log_id: str) -> PathType: - """Get the annotations at the specified log id. - - Args: - log_id: Unique log identifier. - - Returns: - Annotations path for the entire log. - """ - return self.split_dir / log_id / "annotations.feather" - - def lidar_path(self, log_id: str, timestamp_ns: int) -> PathType: - """Get the lidar path at the specified log id and timestamp. - - Args: - log_id: Unique log identifier. - timestamp_ns: Lidar timestamp in nanoseconds. - - Returns: - Lidar path at the log id and timestamp. - """ - return self.split_dir / log_id / "sensors" / "lidar" / f"{timestamp_ns}.feather" - - def pose_path(self, log_id: str) -> PathType: - """Get the city egopose path.""" - return self.split_dir / log_id / "city_SE3_egovehicle.feather" - - def sweep_uuid(self, index: int) -> Tuple[str, int]: - """Get the sweep uuid at the given index. - - Args: - index: Dataset index. - - Returns: - The sweep uuid (log_id, timestamp_ns). - """ - return self.file_index[index] - - def __getitem__(self, index: int) -> Sweep: - """Get the annotations and lidar for one sweep. - - Args: - index: Dataset index. - - Returns: - Sweep object containing annotations and lidar. - """ - annotations: Optional[Annotations] = None - if self.return_annotations: - annotations = self.read_annotations(index) - - lidar = self.read_lidar(index) - log_id, timestamp_ns = self.sweep_uuid(index) - return Sweep(annotations=annotations, lidar=lidar, log_id=log_id, timestamp_ns=timestamp_ns) - - def _build_file_index(self) -> None: - """Build the file index for the dataset.""" - logger.info("Building file index. This may take a moment ...") - log_dirs = sorted(self.split_dir.glob("*")) - path_lists: Optional[List[List[Tuple[str, int]]]] = joblib.Parallel(n_jobs=-1, backend="multiprocessing")( - joblib.delayed(Av2._file_index_helper)(log_dir, LIDAR_GLOB_PATTERN) for log_dir in log_dirs - ) - logger.info("File indexing complete.") - if path_lists is None: - raise RuntimeError("Error scanning the dataset directory!") - if len(path_lists) == 0: - raise RuntimeError("No file paths found. Please validate `self.dataset_dir` and `self.split_name`.") - - file_index = sorted(itertools.chain.from_iterable(path_lists)) - self.file_index = file_index - - def read_annotations(self, index: int) -> Annotations: - """Read the sweep annotations. - - Args: - index: Dataset index. - - Returns: - The annotations object. - """ - log_id, timestamp_ns = self.sweep_uuid(index) - cache_path = self.file_caching_dir / log_id / "annotations.feather" - annotations_path = self.annotations_path(log_id) - - dataframe = self._read_frame(annotations_path, cache_path) - if self.return_velocity_estimates: - dataframe = self._populate_annotations_velocity(index, dataframe) - - distances = np.linalg.norm(dataframe.loc[:, ["tx_m", "ty_m", "tz_m"]].to_numpy(), axis=-1) - num_interior_pts = dataframe.loc[:, "num_interior_pts"].to_numpy().astype(int) - timestamps = dataframe.loc[:, "timestamp_ns"].to_numpy().astype(int) - mask = ( - (num_interior_pts >= self.min_interior_pts) - & (timestamps == timestamp_ns) - & (distances >= self.min_annotation_range) - & (distances <= self.max_annotation_range) - ) - dataframe = dataframe.loc[mask].reset_index(drop=True) - annotations = Annotations(dataframe) - return annotations - - def _populate_annotations_velocity(self, index: int, annotations: pd.DataFrame) -> pd.DataFrame: - """Populate the annotations with their estimated velocities. - - Args: - index: Dataset index. - annotations: DataFrame of annotations loaded from a feather file. - - Returns: - The dataFrame populated with velocities. - """ - current_log_id, _ = self.sweep_uuid(index) - pose_path = self.pose_path(current_log_id) - - file_caching_path = self.file_caching_dir / current_log_id / "city_SE3_egovehicle.feather" - city_SE3_ego = self._read_frame(pose_path, file_caching_path) - - annotations = annotations.sort_values(["track_uuid", "timestamp_ns"]) - annotations_with_poses = annotations.merge( - city_SE3_ego, on=["timestamp_ns"], suffixes=("_obj", None), how="left" - ) - quat = annotations_with_poses.loc[:, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float64) - mats = quat_to_mat(quat) - translation = annotations_with_poses.loc[:, ["tx_m", "ty_m", "tz_m"]].to_numpy().astype(np.float64) - t_xyz = annotations_with_poses.loc[:, ["tx_m_obj", "ty_m_obj", "tz_m_obj"]].to_numpy().astype(np.float64) - annotations.loc[:, ["tx_m_city", "ty_m_city", "tz_m_city"]] = ( - t_xyz[:, None] @ mats.transpose(0, 2, 1) + translation[:, None] - ).squeeze() - - velocities = ( - annotations.loc[:, ["track_uuid", "timestamp_ns", "tx_m_city", "ty_m_city", "tz_m_city"]] - .groupby(["track_uuid"]) - .diff() - .rolling(window=3, min_periods=1, closed="right", center=True, method="table") - .apply(velocity_kernel, raw=True, engine="numba") - .to_numpy() - .astype(np.float64) - ) - annotations[["vx", "vy", "vz"]] = velocities[:, 1:] - annotations = annotations.drop(["tx_m_city", "ty_m_city", "tz_m_city"], axis=1) - return annotations.reset_index(drop=True) - - def read_lidar(self, index: int) -> Lidar: - """Read the lidar sweep. - - Args: - index: Dataset index. - - Returns: - Tensor of annotations. - """ - log_id, timestamp_ns_j = self.sweep_uuid(index) - temporal_window = self.file_index[max(index - self.num_accumulated_sweeps + 1, 0) : index + 1][::-1] - filtered_window: List[Tuple[str, int]] = list( - filter(lambda sweep_uuid: sweep_uuid[0] == log_id, temporal_window) - ) - - poses = self._read_frame( - src_path=self.pose_path(log_id), - file_caching_path=self.file_caching_dir / log_id / "city_SE3_egovehicle.feather", - ) - ego_tj_SE3_city = query_pose(poses, timestamp_ns_j).inverse() - dataframe_list: List[pd.DataFrame] = [] - for _, (log_id, timestamp_ns_i) in enumerate(filtered_window): - dataframe = self._read_frame( - src_path=self.lidar_path(log_id, timestamp_ns_i), - file_caching_path=self.file_caching_dir / log_id / "sensors" / "lidar" / f"{timestamp_ns_i}.feather", - ) - xyz_ti = dataframe.loc[:, list(XYZ_FIELDS)].to_numpy().astype(np.float64) - xyz_tj = xyz_ti - dt = timestamp_ns_j - timestamp_ns_i - assert dt >= 0 - - # Timestamps do not match, we're in a new reference frame. - if dt != 0: - city_SE3_ego_ti = query_pose(poses, timestamp_ns_i) - ego_tj_SE3_ego_ti = ego_tj_SE3_city.compose(city_SE3_ego_ti) - xyz_tj = ego_tj_SE3_ego_ti.transform_point_cloud(xyz_ti) - - dataframe[list(XYZ_FIELDS)] = pd.DataFrame(xyz_tj.astype(np.float32), columns=list(XYZ_FIELDS)) - dataframe["timedelta_ns"] = np.full(len(xyz_tj), fill_value=dt) - dataframe_list.append(dataframe) - dataframe = pd.concat(dataframe_list).reset_index(drop=True) - dataframe = self._post_process_lidar(dataframe) - return Lidar(dataframe) - - def _post_process_lidar(self, dataframe: pd.DataFrame) -> pd.DataFrame: - """Apply post-processing operations on the point cloud. - - Args: - dataframe: Lidar dataframe. - - Returns: - The filtered lidar dataframe. - """ - distances = np.linalg.norm(dataframe.loc[:, list(XYZ_FIELDS)].to_numpy(), axis=1) - dataframe["distance"] = distances - mask = (distances >= self.min_lidar_range) & (distances <= self.max_lidar_range) - dataframe = dataframe.loc[mask] - return dataframe - - @staticmethod - def _file_index_helper(root_dir: PathType, file_pattern: str) -> List[Tuple[str, int]]: - """Build the file index in a multiprocessing context. - - Args: - root_dir: Root directory. - file_pattern: File pattern string. - - Returns: - The list of keys within the glob context. - """ - prevent_fsspec_deadlock() - return [(key.parts[-4], int(key.stem)) for key in root_dir.glob(file_pattern)] - - def _read_frame(self, src_path: PathType, file_caching_path: PathType) -> pd.DataFrame: - """Read a dataframe from a remote source or a locally cached location. - - Args: - src_path: Path to the non-cached file. - file_caching_path: Path to the cached file. - - Returns: - DataFrame representation of the feather file. - """ - if self.file_caching_mode == FileCachingMode.DISK: - file_caching_path.parent.mkdir(parents=True, exist_ok=True) - lock_name = str(file_caching_path) + ".lock" - lock = FileLock(lock_name) - with lock: - if not file_caching_path.exists(): - dataframe = read_feather(src_path) - dataframe.to_feather(file_caching_path, compression="uncompressed") - else: - try: - dataframe = read_feather(file_caching_path) - except Exception as _: - dataframe = read_feather(src_path) - dataframe.to_feather(file_caching_path, compression="uncompressed") - else: - dataframe = read_feather(src_path) - return dataframe + def __getitem__(self, index) -> Tensor: + datum = self._backend.get(index) + return torch.as_tensor(datum.lidar.to_numpy(), dtype=torch.float32) + # annotations = torch.as_tensor(datum.annotations.to_numpy()) + # return Sweep(annotations=datum.annotations.to_numpy(), lidar=datum.lidar, sweep_uuid=datum.sweep_uuid) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 5af6df50..5f9b3029 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -167,9 +167,7 @@ def compute_interior_points(self, lidar: Lidar) -> Tensor: points_xyz = lidar.as_tensor() columns = list(itertools.chain.from_iterable([(f"tx_{i}", f"ty_{i}", f"tz_{i}") for i in range(8)])) - cuboid_vertices = torch.as_tensor(dataframe[columns].to_numpy(), dtype=torch.float32).reshape( - -1, 8, 3 - ) + cuboid_vertices = torch.as_tensor(dataframe[columns].to_numpy(), dtype=torch.float32).reshape(-1, 8, 3) pairwise_point_masks = compute_interior_points_mask(points_xyz, cuboid_vertices) return pairwise_point_masks @@ -208,19 +206,12 @@ class Sweep: Args: annotations: Object containing annotation parameters. lidar: Object containing lidar parameters. - log_id: Log id for the sweep. - timestamp_ns: Timestamp (in nanoseconds) of when the egovehicle's pose was captured. + sweep_uuid: """ annotations: Optional[Annotations] lidar: Lidar - log_id: str - timestamp_ns: int - - @property - def sweep_uuid(self) -> Tuple[str, int]: - """Return a unique id for the sweep.""" - return (self.log_id, self.timestamp_ns) + sweep_uuid: Tuple[str, int] def prevent_fsspec_deadlock() -> None: diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py new file mode 100644 index 00000000..5048dbd9 --- /dev/null +++ b/tutorials/torch_dataloader.py @@ -0,0 +1,19 @@ +from pathlib import Path + +from av2.torch.dataloaders.sensor import Dataloader + + +def main(): + """Example of rust-backed, torch dataloader.""" + root_dir = Path.home() / "data" / "datasets" + split_name = "val" + dataset_name = "av2" + # num_accum_sweeps = 1 + + dataloader = Dataloader(root_dir, dataset_name, split_name) + for lidar in dataloader: + print(lidar) + + +if __name__ == "__main__": + main() From c2f283a2cfd57d82cf0efd813a65fb4287246ec8 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 13:50:38 -0800 Subject: [PATCH 016/117] Add docstrings. --- tutorials/torch_dataloader.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index 5048dbd9..66784223 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -1,14 +1,17 @@ +"""Example of rust-backed, torch dataloader.""" + from pathlib import Path from av2.torch.dataloaders.sensor import Dataloader def main(): - """Example of rust-backed, torch dataloader.""" + """Iterate over the dataloader.""" + + # Dataset should live at ~/data/datasets/{dataset_name}/{split_name} root_dir = Path.home() / "data" / "datasets" split_name = "val" dataset_name = "av2" - # num_accum_sweeps = 1 dataloader = Dataloader(root_dir, dataset_name, split_name) for lidar in dataloader: From 4a7a18db1259dadf2803e5c0ae7382884b411ee7 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 14:11:04 -0800 Subject: [PATCH 017/117] Integrate sweep type return. --- rust/src/lib.rs | 6 +++--- src/av2/torch/dataloaders/sensor.py | 10 ++++++---- tutorials/torch_dataloader.py | 10 ++++++---- 3 files changed, 15 insertions(+), 11 deletions(-) diff --git a/rust/src/lib.rs b/rust/src/lib.rs index ac1a0408..8ee8833e 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -66,12 +66,12 @@ pub struct Dataloader { #[pyo3(get, set)] pub root_dir: PathBuf, #[pyo3(get, set)] + pub dataset_name: String, + #[pyo3(get, set)] pub dataset_type: String, #[pyo3(get, set)] pub split_name: String, #[pyo3(get, set)] - pub dataset_name: String, - #[pyo3(get, set)] pub num_accum_sweeps: usize, #[pyo3(get, set)] pub file_index: PyDataFrame, @@ -94,9 +94,9 @@ impl Dataloader { let current_idx = 0; Dataloader { root_dir: root_dir.to_path_buf(), + dataset_name: dataset_name.to_string(), dataset_type: dataset_type.to_string(), split_name: split_name.to_string(), - dataset_name: dataset_name.to_string(), num_accum_sweeps, file_index: PyDataFrame(file_index), current_idx, diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index a6687a36..53ebb615 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -13,6 +13,7 @@ import av2._r as r from av2.utils.typing import PathType +from av2.torch.dataloaders.utils import Annotations, Lidar from .utils import Sweep @@ -76,8 +77,9 @@ def __repr__(self) -> str: info += f"\t{key}: {value}\n" return info - def __getitem__(self, index) -> Tensor: + def __getitem__(self, index) -> Sweep: datum = self._backend.get(index) - return torch.as_tensor(datum.lidar.to_numpy(), dtype=torch.float32) - # annotations = torch.as_tensor(datum.annotations.to_numpy()) - # return Sweep(annotations=datum.annotations.to_numpy(), lidar=datum.lidar, sweep_uuid=datum.sweep_uuid) + annotations = Annotations(dataframe=datum.annotations.to_pandas()) + lidar = Lidar(dataframe=datum.lidar.to_pandas()) + sweep = Sweep(annotations=annotations, lidar=lidar, sweep_uuid=datum.sweep_uuid) + return sweep diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index 66784223..c559ed2b 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -10,12 +10,14 @@ def main(): # Dataset should live at ~/data/datasets/{dataset_name}/{split_name} root_dir = Path.home() / "data" / "datasets" - split_name = "val" dataset_name = "av2" + split_name = "val" + num_accum_sweeps = 5 - dataloader = Dataloader(root_dir, dataset_name, split_name) - for lidar in dataloader: - print(lidar) + dataloader = Dataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) + for sweep in dataloader: + lidar = sweep.lidar.as_tensor() + print(lidar.shape) if __name__ == "__main__": From ed8f27b43d2d9adfd51102ef7f20500c9bdfb0e0 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 14:42:04 -0800 Subject: [PATCH 018/117] Update deps. --- conda/environment.yml | 4 ++++ pyproject.toml | 1 + rust/Cargo.lock | 11 ----------- rust/Cargo.toml | 3 +-- src/av2/_r.pyi | 22 ++++++++++++++++++++++ src/av2/torch/dataloaders/sensor.py | 29 +++++++---------------------- 6 files changed, 35 insertions(+), 35 deletions(-) create mode 100644 src/av2/_r.pyi diff --git a/conda/environment.yml b/conda/environment.yml index a6545291..9aadd0ab 100644 --- a/conda/environment.yml +++ b/conda/environment.yml @@ -6,14 +6,18 @@ dependencies: - click - joblib - matplotlib-base + - maturin - nox - numba - numpy - opencv - pandas - pip + - polars - pyarrow - pyproj - rich + - rust - scipy + - pytorch - universal_pathlib diff --git a/pyproject.toml b/pyproject.toml index 77049be0..f10e72c6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,6 +22,7 @@ dependencies = [ "numpy", "opencv-python", "pandas", + "polars", "pyarrow", "pyproj", "rich", diff --git a/rust/Cargo.lock b/rust/Cargo.lock index 12bb4bfe..decf4311 100644 --- a/rust/Cargo.lock +++ b/rust/Cargo.lock @@ -93,16 +93,6 @@ dependencies = [ "num-traits", ] -[[package]] -name = "argminmax" -version = "0.3.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "1f3fa5b375099be3bd519f13f1faf0190ebab46f55d37003a620bf7570ba51ab" -dependencies = [ - "ndarray", - "num-traits", -] - [[package]] name = "array-init-cursor" version = "0.2.0" @@ -211,7 +201,6 @@ name = "av2" version = "0.1.0" dependencies = [ "anyhow", - "argminmax", "bincode", "blas-src", "criterion", diff --git a/rust/Cargo.toml b/rust/Cargo.toml index f2ab0fd1..367021e9 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -13,14 +13,13 @@ crate-type = ["cdylib"] [dependencies] anyhow = "1.0.66" -argminmax = "0.3.1" blas-src = { version = "0.8", features = ["openblas"] } bincode = "1.3.3" criterion = "0.4.0" dirs = "4.0.0" glob = "0.3.1" indicatif = { version = "0.17.3", features = ["rayon"] } -itertools = "*" +itertools = "0.10.5" ndarray = { version = "0.15.6", features = ["blas", "rayon"] } ndarray_einsum_beta = "0.7.0" nshare = "0.9.0" diff --git a/src/av2/_r.pyi b/src/av2/_r.pyi new file mode 100644 index 00000000..89734f94 --- /dev/null +++ b/src/av2/_r.pyi @@ -0,0 +1,22 @@ +"""Rust backend typing stubs.""" + +from dataclasses import dataclass +from typing import Tuple + +import polars as pl + +@dataclass +class Dataloader: + root_dir: str + dataset_name: str + dataset_type: str + split_name: str + num_accum_sweeps: int + + def get(self, index: int) -> Sweep: ... + +@dataclass +class Sweep: + annotations: pl.DataFrame + lidar: pl.DataFrame + sweep_uuid: Tuple[str, int] diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 53ebb615..5cdbf7e7 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -5,24 +5,18 @@ import logging from dataclasses import dataclass, field from math import inf -from typing import Final -import torch -from torch import Tensor from torch.utils.data import Dataset import av2._r as r -from av2.utils.typing import PathType from av2.torch.dataloaders.utils import Annotations, Lidar +from av2.utils.typing import PathType from .utils import Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) -XYZ_FIELDS: Final = ("x", "y", "z") -LIDAR_GLOB_PATTERN: Final = "sensors/lidar/*.feather" - @dataclass class Dataloader(Dataset[Sweep]): @@ -55,7 +49,7 @@ class Dataloader(Dataset[Sweep]): return_annotations: bool = False return_velocity_estimates: bool = False - _backend: r.SensorDataset = field(init=False) + _backend: r.Dataloader = field(init=False) def __post_init__(self) -> None: """Build the file index.""" @@ -68,18 +62,9 @@ def __post_init__(self) -> None: str(self.root_dir), "sensor", self.split_name, self.dataset_name, self.num_accum_sweeps ) - def __repr__(self) -> str: - """Dataloader info.""" - info = "Dataloader configuration settings:\n" - for key, value in sorted(self.items()): - if key == "file_index": - continue - info += f"\t{key}: {value}\n" - return info - - def __getitem__(self, index) -> Sweep: - datum = self._backend.get(index) - annotations = Annotations(dataframe=datum.annotations.to_pandas()) - lidar = Lidar(dataframe=datum.lidar.to_pandas()) - sweep = Sweep(annotations=annotations, lidar=lidar, sweep_uuid=datum.sweep_uuid) + def __getitem__(self, index: int) -> Sweep: + sweep = self._backend.get(index) + annotations = Annotations(dataframe=sweep.annotations.to_pandas()) + lidar = Lidar(dataframe=sweep.lidar.to_pandas()) + sweep = Sweep(annotations=annotations, lidar=lidar, sweep_uuid=sweep.sweep_uuid) return sweep From 8d99fbf52f605250a2af2c4108d768d0e64b2f59 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 14:54:48 -0800 Subject: [PATCH 019/117] Fix clippy. --- rust/src/io.rs | 2 +- rust/src/lib.rs | 35 +++++++++++++++-------------------- rust/src/path.rs | 5 +++-- 3 files changed, 19 insertions(+), 23 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 0a5194b9..bc924e53 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -131,7 +131,7 @@ pub fn read_lidar( pub fn read_annotations( path: &PathBuf, - columns: &Vec, + columns: &Vec<&str>, timestamp_ns: &u64, memory_map: bool, ) -> LazyFrame { diff --git a/rust/src/lib.rs b/rust/src/lib.rs index 8ee8833e..97928686 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -15,28 +15,23 @@ use std::path::{Path, PathBuf}; use anyhow::Result; use bincode::{deserialize, serialize}; use glob::glob; -use once_cell::sync::Lazy; use polars::prelude::*; use pyo3::types::PyBytes; -pub static ANNOTATION_COLUMNS: Lazy> = Lazy::new(|| { - [ - "tx_m", - "ty_m", - "tz_m", - "length_m", - "width_m", - "height_m", - "qw", - "qx", - "qy", - "qz", - "num_interior_pts", - "category", - ] - .map(String::from) - .to_vec() -}); +pub const ANNOTATION_COLUMNS: [&str; 12] = [ + "tx_m", + "ty_m", + "tz_m", + "length_m", + "width_m", + "height_m", + "qw", + "qx", + "qy", + "qz", + "num_interior_pts", + "category", +]; #[pyclass] pub struct Sweep { @@ -159,7 +154,7 @@ impl Dataloader { let annotations_path = self.annotations_path(log_id); - let columns = ANNOTATION_COLUMNS.clone(); + let columns = ANNOTATION_COLUMNS[..].iter().cloned().collect_vec(); let annotations = read_annotations(&annotations_path, &columns, ×tamp_ns, true) .filter(col("num_interior_pts").gt_eq(1.)) .collect() diff --git a/rust/src/path.rs b/rust/src/path.rs index 7370a3fd..deb30b84 100644 --- a/rust/src/path.rs +++ b/rust/src/path.rs @@ -1,16 +1,17 @@ use anyhow::{Context, Result}; use std::fs; use std::path::PathBuf; +use std::path::Path; pub fn walk_dir(dir: &PathBuf) -> Result> { - let files: Vec<_> = fs::read_dir(&dir)? + let files: Vec<_> = fs::read_dir(dir)? .filter_map(|x| x.ok()) .map(|x| x.path()) .collect(); Ok(files) } -pub fn file_stem(dir: &PathBuf) -> Result { +pub fn file_stem(dir: &Path) -> Result { let file_stem = dir .file_stem() .context("Cannot parse file stem.")? 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100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -1,10 +1,13 @@ pub mod io; +pub mod ops; pub mod path; pub mod se3; pub mod so3; use io::{read_annotations, read_lidar}; use itertools::{multiunzip, Itertools}; +use ndarray::Dim; +use numpy::{IntoPyArray, PyArray}; use path::{file_stem, walk_dir}; use pyo3::prelude::*; use pyo3_polars::PyDataFrame; @@ -15,9 +18,12 @@ use std::path::{Path, PathBuf}; use anyhow::Result; use bincode::{deserialize, serialize}; use glob::glob; +use numpy::PyReadonlyArray2; use polars::prelude::*; use pyo3::types::PyBytes; +use crate::ops::voxelize; + pub const ANNOTATION_COLUMNS: [&str; 12] = [ "tx_m", "ty_m", @@ -265,10 +271,39 @@ pub fn build_file_index( .unwrap() } +#[pyfunction] +#[pyo3(name = "voxelize")] +fn py_voxelize<'py>( + py: Python<'py>, + indices: PyReadonlyArray2, + features: PyReadonlyArray2, + length: usize, + width: usize, + height: usize, +) -> ( + &'py PyArray>, + &'py PyArray>, + &'py PyArray>, +) { + let (indices, values, counts) = voxelize( + &indices.as_array(), + &features.as_array(), + length, + width, + height, + ); + ( + indices.into_pyarray(py), + values.into_pyarray(py), + counts.into_pyarray(py), + ) +} + /// A Python module implemented in Rust. #[pymodule] fn _r(_py: Python, m: &PyModule) -> PyResult<()> { m.add_class::()?; m.add_class::()?; + m.add_function(wrap_pyfunction!(py_voxelize, m)?)?; Ok(()) } diff --git a/rust/src/ops.rs b/rust/src/ops.rs new file mode 100644 index 00000000..fe683e3d --- /dev/null +++ b/rust/src/ops.rs @@ -0,0 +1,66 @@ +use itertools::Itertools; +use ndarray::{azip, par_azip, s, Array1, Array2, ArrayView2, Axis}; +use std::{ + collections::HashMap, + ops::{AddAssign, DivAssign}, +}; + +pub fn ravel_multi_index(unraveled_coords: &ArrayView2, size: Vec) -> Array2 { + let shape_arr = Array1::::from_vec( + size.into_iter() + .chain(vec![1].into_iter()) + .collect::>(), + ); + + let mut coefs = shape_arr + .slice(s![1..]) + .into_iter() + .rev() + .copied() + .collect::>(); + + coefs.accumulate_axis_inplace(Axis(0), |prev, curr| *curr *= prev); + coefs = coefs.iter().rev().copied().collect::>(); + (unraveled_coords * &coefs) + .sum_axis(Axis(1)) + .insert_axis(Axis(1)) +} + +pub fn voxelize( + indices: &ArrayView2, + features: &ArrayView2, + length: usize, + width: usize, + height: usize, +) -> (Array2, Array2, Array2) { + let shape = vec![length, width, height]; + let raveled_indices = ravel_multi_index(&indices.view(), shape); + + let num_features = features.shape()[1]; + + let unique_indices = raveled_indices + .clone() + .into_raw_vec() + .into_iter() + .unique() + .enumerate() + .map(|(k, v)| (v, k)) + .collect::>(); + + let mut indices_buffer = Array2::::zeros([unique_indices.len(), 3]); + let mut values_buffer = Array2::::zeros([unique_indices.len(), num_features]); + let mut counts = Array2::::zeros([unique_indices.len(), 1]); + + azip!((idx in raveled_indices.rows(), coo in indices.rows(), val in features.rows()) { + let i = *unique_indices.get(&idx[0]).unwrap(); + + indices_buffer.slice_mut(s![i, ..]).assign(&coo); + values_buffer.slice_mut(s![i, ..]).add_assign(&val); + counts[[i, 0]] += 1.; + }); + + par_azip!((mut val in values_buffer.rows_mut(), count in counts.rows()) { + val.div_assign(&count); + }); + (indices_buffer, values_buffer, counts) +} From af49d421572e35b886c602e0c6bf31c43b49d5fe Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 11 Mar 2023 16:07:21 -0800 Subject: [PATCH 022/117] Improve example code. --- src/av2/_r.pyi | 1 + src/av2/torch/dataloaders/sensor.py | 14 ++++++++++++++ tutorials/torch_dataloader.py | 7 ++++--- 3 files changed, 19 insertions(+), 3 deletions(-) diff --git a/src/av2/_r.pyi b/src/av2/_r.pyi index 89734f94..e55af934 100644 --- a/src/av2/_r.pyi +++ b/src/av2/_r.pyi @@ -14,6 +14,7 @@ class Dataloader: num_accum_sweeps: int def get(self, index: int) -> Sweep: ... + def __len__(self) -> int: ... @dataclass class Sweep: diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 5cdbf7e7..c2f37955 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -50,6 +50,7 @@ class Dataloader(Dataset[Sweep]): return_velocity_estimates: bool = False _backend: r.Dataloader = field(init=False) + _current_idx: int = 0 def __post_init__(self) -> None: """Build the file index.""" @@ -67,4 +68,17 @@ def __getitem__(self, index: int) -> Sweep: annotations = Annotations(dataframe=sweep.annotations.to_pandas()) lidar = Lidar(dataframe=sweep.lidar.to_pandas()) sweep = Sweep(annotations=annotations, lidar=lidar, sweep_uuid=sweep.sweep_uuid) + + self._current_idx += 1 return sweep + + def __len__(self) -> int: + return self._backend.__len__() + + def __iter__(self): + return self + + def __next__(self): + if self._current_idx >= self.__len__(): + raise StopIteration + return self.__getitem__(self._current_idx) diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index c559ed2b..8f2d92eb 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -2,6 +2,8 @@ from pathlib import Path +from tqdm import tqdm + from av2.torch.dataloaders.sensor import Dataloader @@ -15,9 +17,8 @@ def main(): num_accum_sweeps = 5 dataloader = Dataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) - for sweep in dataloader: - lidar = sweep.lidar.as_tensor() - print(lidar.shape) + for sweep in tqdm(dataloader): + lidar = sweep.lidar.as_tensor(field_ordering=("x", "y", "z", "intensity")) if __name__ == "__main__": From c08134b92eea8f0452a7dc9478875e3a90351052 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 11:28:32 -0700 Subject: [PATCH 023/117] Add track_uuid to rust dataloader. --- rust/src/lib.rs | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/rust/src/lib.rs b/rust/src/lib.rs index f1e7d588..36b8ee1f 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -24,7 +24,7 @@ use pyo3::types::PyBytes; use crate::ops::voxelize; -pub const ANNOTATION_COLUMNS: [&str; 12] = [ +pub const ANNOTATION_COLUMNS: [&str; 13] = [ "tx_m", "ty_m", "tz_m", @@ -37,6 +37,7 @@ pub const ANNOTATION_COLUMNS: [&str; 12] = [ "qz", "num_interior_pts", "category", + "track_uuid", ]; #[pyclass] From 11a4791c9330a526c24ce651c8e63226348b91e3 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 11:57:23 -0700 Subject: [PATCH 024/117] Return city pose from torch dataloader. --- rust/src/io.rs | 2 +- rust/src/lib.rs | 54 +++++++++++++++++++++++------ src/av2/_r.pyi | 2 ++ src/av2/torch/dataloaders/sensor.py | 13 +++++-- src/av2/torch/dataloaders/utils.py | 37 ++++++++++---------- tutorials/torch_dataloader.py | 1 - 6 files changed, 74 insertions(+), 35 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index bc924e53..0e441e71 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -129,7 +129,7 @@ pub fn read_lidar( concat(lidar_list, true, true).unwrap() } -pub fn read_annotations( +pub fn read_filter_timestamp( path: &PathBuf, columns: &Vec<&str>, timestamp_ns: &u64, diff --git a/rust/src/lib.rs b/rust/src/lib.rs index 36b8ee1f..b3725e3c 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -4,7 +4,7 @@ pub mod path; pub mod se3; pub mod so3; -use io::{read_annotations, read_lidar}; +use io::{read_filter_timestamp, read_lidar}; use itertools::{multiunzip, Itertools}; use ndarray::Dim; use numpy::{IntoPyArray, PyArray}; @@ -40,23 +40,33 @@ pub const ANNOTATION_COLUMNS: [&str; 13] = [ "track_uuid", ]; +pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; + #[pyclass] pub struct Sweep { - #[pyo3(get, set)] - pub lidar: PyDataFrame, #[pyo3(get, set)] pub annotations: PyDataFrame, #[pyo3(get, set)] + pub city_pose: PyDataFrame, + #[pyo3(get, set)] + pub lidar: PyDataFrame, + #[pyo3(get, set)] pub sweep_uuid: (String, u64), } #[pymethods] impl Sweep { #[new] - pub fn new(lidar: PyDataFrame, annotations: PyDataFrame, sweep_uuid: (String, u64)) -> Sweep { + pub fn new( + annotations: PyDataFrame, + city_pose: PyDataFrame, + lidar: PyDataFrame, + sweep_uuid: (String, u64), + ) -> Sweep { Sweep { - lidar, annotations, + city_pose, + lidar, sweep_uuid, } } @@ -79,6 +89,8 @@ pub struct Dataloader { pub file_index: PyDataFrame, #[pyo3(get, set)] pub current_idx: usize, + #[pyo3(get, set)] + pub memory_map: bool, } #[pymethods] @@ -90,6 +102,7 @@ impl Dataloader { split_name: &str, dataset_name: &str, num_accum_sweeps: usize, + memory_map: bool, ) -> Dataloader { let root_dir = Path::new(root_dir); let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); @@ -102,6 +115,7 @@ impl Dataloader { num_accum_sweeps, file_index: PyDataFrame(file_index), current_idx, + memory_map, } } @@ -133,6 +147,10 @@ impl Dataloader { self.log_dir(log_id).join("annotations.feather") } + pub fn city_pose_path(&self, log_id: &str) -> PathBuf { + self.log_dir(log_id).join("city_SE3_egovehicle.feather") + } + pub fn map_dir(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("map") } @@ -160,18 +178,32 @@ impl Dataloader { .unwrap(); let annotations_path = self.annotations_path(log_id); + let annotations = read_filter_timestamp( + &annotations_path, + &ANNOTATION_COLUMNS.to_vec(), + ×tamp_ns, + self.memory_map, + ) + .filter(col("num_interior_pts").gt_eq(1.)) + .collect() + .unwrap(); - let columns = ANNOTATION_COLUMNS[..].iter().cloned().collect_vec(); - let annotations = read_annotations(&annotations_path, &columns, ×tamp_ns, true) - .filter(col("num_interior_pts").gt_eq(1.)) - .collect() - .unwrap(); + let city_pose_path = self.city_pose_path(log_id); + let city_pose = read_filter_timestamp( + &city_pose_path, + &POSE_COLUMNS.to_vec(), + ×tamp_ns, + self.memory_map, + ) + .collect() + .unwrap(); let sweep_uuid = (log_id.to_string(), timestamp_ns); Sweep { - lidar: PyDataFrame(lidar), annotations: PyDataFrame(annotations), + city_pose: PyDataFrame(city_pose), + lidar: PyDataFrame(lidar), sweep_uuid, } } diff --git a/src/av2/_r.pyi b/src/av2/_r.pyi index e55af934..008c6aa9 100644 --- a/src/av2/_r.pyi +++ b/src/av2/_r.pyi @@ -12,6 +12,7 @@ class Dataloader: dataset_type: str split_name: str num_accum_sweeps: int + memory_map: bool def get(self, index: int) -> Sweep: ... def __len__(self) -> int: ... @@ -19,5 +20,6 @@ class Dataloader: @dataclass class Sweep: annotations: pl.DataFrame + city_pose: pl.DataFrame lidar: pl.DataFrame sweep_uuid: Tuple[str, int] diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index c2f37955..1caa4a4c 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -12,7 +12,7 @@ from av2.torch.dataloaders.utils import Annotations, Lidar from av2.utils.typing import PathType -from .utils import Sweep +from .utils import Pose, Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -48,6 +48,7 @@ class Dataloader(Dataset[Sweep]): num_accum_sweeps: int = 1 return_annotations: bool = False return_velocity_estimates: bool = False + memory_map: bool = False _backend: r.Dataloader = field(init=False) _current_idx: int = 0 @@ -60,14 +61,20 @@ def __post_init__(self) -> None: raise RuntimeError("with_annotations must be enabled to return annotations' velocities.") self._backend = r.Dataloader( - str(self.root_dir), "sensor", self.split_name, self.dataset_name, self.num_accum_sweeps + str(self.root_dir), + "sensor", + self.split_name, + self.dataset_name, + self.num_accum_sweeps, + self.memory_map, ) def __getitem__(self, index: int) -> Sweep: sweep = self._backend.get(index) annotations = Annotations(dataframe=sweep.annotations.to_pandas()) + city_pose = Pose(dataframe=sweep.city_pose) lidar = Lidar(dataframe=sweep.lidar.to_pandas()) - sweep = Sweep(annotations=annotations, lidar=lidar, sweep_uuid=sweep.sweep_uuid) + sweep = Sweep(annotations=annotations, city_pose=city_pose, lidar=lidar, sweep_uuid=sweep.sweep_uuid) self._current_idx += 1 return sweep diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 5f9b3029..4bb22e6a 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -6,10 +6,10 @@ import sys from dataclasses import dataclass from enum import Enum, unique +from functools import cached_property from typing import Final, Optional, Tuple import fsspec.asyn -import numba as nb import numpy as np import pandas as pd import torch @@ -35,6 +35,7 @@ ) DEFAULT_LIDAR_TENSOR_FIELDS: Final = ("x", "y", "z") QUAT_WXYZ_FIELDS: Final = ("qw", "qx", "qy", "qz") +TRANSLATION_FIELDS: Final = ("tx_m", "ty_m", "tz_m") @unique @@ -210,10 +211,26 @@ class Sweep: """ annotations: Optional[Annotations] + city_pose: Pose lidar: Lidar sweep_uuid: Tuple[str, int] +@dataclass(frozen=True) +class Pose: + """Stores the annotations and lidar for one sweep.""" + + dataframe: pd.DataFrame + + @cached_property + def Rt(self) -> Tuple[Tensor, Tensor]: + quat_wxyz: NDArrayFloat = self.dataframe[QUAT_WXYZ_FIELDS].to_numpy() + translation: NDArrayFloat = self.dataframe[TRANSLATION_FIELDS].to_numpy() + + rotation = quat_to_mat(quat_wxyz) + return torch.as_tensor(rotation, dtype=torch.float32), torch.as_tensor(translation, dtype=torch.float32) + + def prevent_fsspec_deadlock() -> None: """Reset the fsspec global lock to prevent deadlocking in forked processes.""" fsspec.asyn.reset_lock() @@ -277,21 +294,3 @@ def compute_interior_points_mask(xyz_m: Tensor, cuboid_vertices: Tensor) -> Tens constraint_b = torch.logical_and(dot_uvw_reference >= dot_uvw_points, dot_uvw_points >= dot_uvw_vertices) is_interior: Tensor = torch.logical_or(constraint_a, constraint_b).all(dim=1) return is_interior - - -@nb.njit(nogil=True) -def velocity_kernel(delta_txyz: NDArrayFloat) -> Tuple[float, float, float, float]: - """Estimate the velocity. - - Args: - delta_txyz: (N,4) Array of timestamp, x, y, z. - - Returns: - Velocity. - """ - dt_ns, dx_m, dy_m, dz_m = delta_txyz.T - dt_s = dt_ns * 1e-9 - vx_m = float(np.nanmean(dx_m / dt_s)) - vy_m = float(np.nanmean(dy_m / dt_s)) - vz_m = float(np.nanmean(dz_m / dt_s)) - return (0.0, vx_m, vy_m, vz_m) diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index 8f2d92eb..85012017 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -20,6 +20,5 @@ def main(): for sweep in tqdm(dataloader): lidar = sweep.lidar.as_tensor(field_ordering=("x", "y", "z", "intensity")) - if __name__ == "__main__": main() From baf9ae0331be9b23ff1da884fd069728d6d16f11 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 12:29:34 -0700 Subject: [PATCH 025/117] Update deps. --- Cargo.lock | 341 +++--------------------------------------------- rust/Cargo.toml | 4 +- 2 files changed, 16 insertions(+), 329 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index decf4311..f6e0c6cc 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -123,7 +123,7 @@ checksum = "7a4c5b03335bc1cb0fd9f5297f8fd3bbfd6fb04f3cb0bc7d6c91b7128cb8336a" dependencies = [ "ahash", "arrow-format", - "base64 0.13.1", + "base64", "bytemuck", "chrono", "dyn-clone", @@ -202,9 +202,8 @@ version = "0.1.0" dependencies = [ "anyhow", "bincode", - "blas-src", "criterion", - "dirs 4.0.0", + "dirs", "glob", "indicatif", "itertools", @@ -213,7 +212,6 @@ dependencies = [ "nshare", "numpy", "once_cell", - "openblas-src", "phf", "polars", "pprof", @@ -247,12 +245,6 @@ version = "0.13.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "9e1b586273c5702936fe7b7d6896644d8be71e6314cfe09d3167c95f712589e8" -[[package]] -name = "base64" -version = "0.21.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "a4a4ddaa51a5bc52a6948f74c06d20aaaddb71924eab79b8c97a8c556e942d6a" - [[package]] name = "bincode" version = "1.3.3" @@ -268,15 +260,6 @@ version = "1.3.2" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "bef38d45163c2f1dde094a7dfd33ccf595c92905c8f8f4fdc18d06fb1037718a" -[[package]] -name = "blas-src" -version = "0.8.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "bb48fbaa7a0cb9d6d96c46bac6cedb16f13a10aebcef1c4e73515aaae8c9909d" -dependencies = [ - "openblas-src", -] - [[package]] name = "brotli" version = "3.3.4" @@ -342,15 +325,6 @@ version = "0.3.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "37b2a672a2cb129a2e41c10b1224bb368f9f37a2b16b612598138befd7b37eb5" -[[package]] -name = "cblas-sys" -version = "0.1.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "b6feecd82cce51b0204cf063f0041d69f24ce83f680d87514b004248e7b0fa65" -dependencies = [ - "libc", -] - [[package]] name = "cc" version = "1.0.79" @@ -492,16 +466,6 @@ dependencies = [ "tiny-keccak", ] -[[package]] -name = "core-foundation" -version = "0.9.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "194a7a9e6de53fa55116934067c844d9d749312f75c6f6d0980e8c252f8c2146" -dependencies = [ - "core-foundation-sys", - "libc", -] - [[package]] name = "core-foundation-sys" version = "0.8.3" @@ -689,15 +653,6 @@ dependencies = [ "uuid", ] -[[package]] -name = "dirs" -version = "3.0.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "30baa043103c9d0c2a57cf537cc2f35623889dc0d405e6c3cccfadbc81c71309" -dependencies = [ - "dirs-sys", -] - [[package]] name = "dirs" version = "4.0.0" @@ -790,18 +745,6 @@ dependencies = [ "instant", ] -[[package]] -name = "filetime" -version = "0.2.20" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "8a3de6e8d11b22ff9edc6d916f890800597d60f8b2da1caf2955c274638d6412" -dependencies = [ - "cfg-if", - "libc", - "redox_syscall", - "windows-sys 0.45.0", -] - [[package]] name = "findshlibs" version = "0.10.2" @@ -824,36 +767,12 @@ dependencies = [ "miniz_oxide", ] -[[package]] -name = "foreign-types" -version = "0.3.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "f6f339eb8adc052cd2ca78910fda869aefa38d22d5cb648e6485e4d3fc06f3b1" -dependencies = [ - "foreign-types-shared", -] - -[[package]] -name = "foreign-types-shared" -version = "0.1.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "00b0228411908ca8685dba7fc2cdd70ec9990a6e753e89b6ac91a84c40fbaf4b" - [[package]] name = "foreign_vec" version = "0.1.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "ee1b05cbd864bcaecbd3455d6d967862d446e4ebfc3c2e5e5b9841e53cba6673" -[[package]] -name = "form_urlencoded" -version = "1.1.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "a9c384f161156f5260c24a097c56119f9be8c798586aecc13afbcbe7b7e26bf8" -dependencies = [ - "percent-encoding", -] - [[package]] name = "futures" version = "0.3.27" @@ -1050,16 +969,6 @@ dependencies = [ "cxx-build", ] -[[package]] -name = "idna" -version = "0.3.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "e14ddfc70884202db2244c223200c204c2bda1bc6e0998d11b5e024d657209e6" -dependencies = [ - "unicode-bidi", - "unicode-normalization", -] - [[package]] name = "image" version = "0.24.5" @@ -1335,7 +1244,10 @@ version = "0.3.2" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "add85d4dd35074e6fedc608f8c8f513a3548619a9024b751949ef0e8e45a4d84" dependencies = [ + "num_cpus", + "once_cell", "rawpointer", + "thread-tree", ] [[package]] @@ -1418,24 +1330,6 @@ dependencies = [ "typenum", ] -[[package]] -name = "native-tls" -version = "0.2.11" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "07226173c32f2926027b63cce4bcd8076c3552846cbe7925f3aaffeac0a3b92e" -dependencies = [ - "lazy_static", - "libc", - "log", - "openssl", - "openssl-probe", - "openssl-sys", - "schannel", - "security-framework", - "security-framework-sys", - "tempfile", -] - [[package]] name = "ndarray" version = "0.15.6" @@ -1443,8 +1337,6 @@ source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "adb12d4e967ec485a5f71c6311fe28158e9d6f4bc4a447b474184d0f91a8fa32" dependencies = [ "approx 0.4.0", - "cblas-sys", - "libc", "matrixmultiply", "num-complex", "num-integer", @@ -1645,77 +1537,6 @@ version = "11.1.3" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "0ab1bc2a289d34bd04a330323ac98a1b4bc82c9d9fcb1e66b63caa84da26b575" -[[package]] -name = "openblas-build" -version = "0.10.8" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "eba42c395477605f400a8d79ee0b756cfb82abe3eb5618e35fa70d3a36010a7f" -dependencies = [ - "anyhow", - "flate2", - "native-tls", - "tar", - "thiserror", - "ureq", - "walkdir", -] - -[[package]] -name = "openblas-src" -version = "0.10.8" -source = 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-[[package]] -name = "openssl-sys" -version = "0.9.80" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "23bbbf7854cd45b83958ebe919f0e8e516793727652e27fda10a8384cfc790b7" -dependencies = [ - "autocfg", - "cc", - "libc", - "pkg-config", - "vcpkg", -] - [[package]] name = "os_str_bytes" version = "6.4.1" @@ -1804,12 +1625,6 @@ version = "1.0.12" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "9f746c4065a8fa3fe23974dd82f15431cc8d40779821001404d10d2e79ca7d79" -[[package]] -name = "percent-encoding" -version = "2.2.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "478c572c3d73181ff3c2539045f6eb99e5491218eae919370993b890cdbdd98e" - [[package]] name = "phf" version = "0.11.1" @@ -1975,7 +1790,7 @@ dependencies = [ "arrow2", "bytes", "chrono", - "dirs 4.0.0", + "dirs", "lexical", "lexical-core", "memchr", @@ -2377,27 +2192,6 @@ dependencies = [ "windows-sys 0.45.0", ] -[[package]] -name = "rustls-native-certs" -version = "0.6.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "0167bac7a9f490495f3c33013e7722b53cb087ecbe082fb0c6387c96f634ea50" -dependencies = [ - "openssl-probe", - "rustls-pemfile", - "schannel", - "security-framework", -] - -[[package]] -name = "rustls-pemfile" -version = "1.0.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "d194b56d58803a43635bdc398cd17e383d6f71f9182b9a192c127ca42494a59b" -dependencies = [ - "base64 0.21.0", -] - [[package]] name = "rustversion" version = "1.0.12" @@ -2428,15 +2222,6 @@ dependencies = [ "winapi-util", ] -[[package]] -name = "schannel" -version = "0.1.21" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "713cfb06c7059f3588fb8044c0fad1d09e3c01d225e25b9220dbfdcf16dbb1b3" -dependencies = [ - "windows-sys 0.42.0", -] - [[package]] name = "scopeguard" version = "1.1.0" @@ -2449,29 +2234,6 @@ version = "1.0.5" source = 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"4b55807c0344e1e6c04d7c965f5289c39a8d94ae23ed5c0b57aabac549f871c6" -dependencies = [ - "filetime", - "libc", - "xattr", -] - [[package]] name = "target-lexicon" version = "0.12.6" @@ -2773,6 +2524,15 @@ dependencies = [ "syn", ] +[[package]] +name = "thread-tree" +version = "0.3.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "ffbd370cb847953a25954d9f63e14824a36113f8c72eecf6eccef5dc4b45d630" +dependencies = [ + "crossbeam-channel", +] + [[package]] name = "time" version = "0.1.45" @@ -2803,48 +2563,18 @@ dependencies = [ "serde_json", ] -[[package]] -name = "tinyvec" -version = "1.6.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "87cc5ceb3875bb20c2890005a4e226a4651264a5c75edb2421b52861a0a0cb50" -dependencies = [ - "tinyvec_macros", -] - -[[package]] -name = "tinyvec_macros" -version = "0.1.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "1f3ccbac311fea05f86f61904b462b55fb3df8837a366dfc601a0161d0532f20" - [[package]] name = "typenum" version = "1.16.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "497961ef93d974e23eb6f433eb5fe1b7930b659f06d12dec6fc44a8f554c0bba" -[[package]] -name = "unicode-bidi" -version = "0.3.11" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "524b68aca1d05e03fdf03fcdce2c6c94b6daf6d16861ddaa7e4f2b6638a9052c" - [[package]] name = "unicode-ident" version = "1.0.8" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "e5464a87b239f13a63a501f2701565754bae92d243d4bb7eb12f6d57d2269bf4" -[[package]] -name = "unicode-normalization" -version = "0.1.22" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "5c5713f0fc4b5db668a2ac63cdb7bb4469d8c9fed047b1d0292cc7b0ce2ba921" -dependencies = [ - "tinyvec", -] - [[package]] name = "unicode-width" version = "0.1.10" @@ -2857,44 +2587,12 @@ version = "0.1.11" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "e1766d682d402817b5ac4490b3c3002d91dfa0d22812f341609f97b08757359c" -[[package]] -name = "ureq" -version = "2.6.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "338b31dd1314f68f3aabf3ed57ab922df95ffcd902476ca7ba3c4ce7b908c46d" -dependencies = [ - "base64 0.13.1", - "flate2", - "log", - "native-tls", - "once_cell", - "rustls-native-certs", - "url", -] - -[[package]] -name = "url" -version = "2.3.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "0d68c799ae75762b8c3fe375feb6600ef5602c883c5d21eb51c09f22b83c4643" -dependencies = [ - "form_urlencoded", - "idna", - "percent-encoding", -] - [[package]] name = "uuid" version = "1.3.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "1674845326ee10d37ca60470760d4288a6f80f304007d92e5c53bab78c9cfd79" -[[package]] -name = "vcpkg" -version = "0.2.15" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "accd4ea62f7bb7a82fe23066fb0957d48ef677f6eeb8215f372f52e48bb32426" - [[package]] name = "version_check" version = "0.9.4" @@ -3137,15 +2835,6 @@ version = "0.42.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "447660ad36a13288b1db4d4248e857b510e8c3a225c822ba4fb748c0aafecffd" -[[package]] -name = "xattr" -version = "0.2.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "6d1526bbe5aaeb5eb06885f4d987bcdfa5e23187055de9b83fe00156a821fabc" -dependencies = [ - "libc", -] - [[package]] name = "xxhash-rust" version = "0.8.6" diff --git a/rust/Cargo.toml b/rust/Cargo.toml index 367021e9..e5084571 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -13,19 +13,17 @@ crate-type = ["cdylib"] [dependencies] anyhow = "1.0.66" -blas-src = { version = "0.8", features = ["openblas"] } bincode = "1.3.3" criterion = "0.4.0" dirs = "4.0.0" glob = "0.3.1" indicatif = { version = "0.17.3", features = ["rayon"] } itertools = "0.10.5" -ndarray = { version = "0.15.6", features = ["blas", "rayon"] } +ndarray = { version = "0.15.6", features = ["matrixmultiply-threading", "rayon"] } ndarray_einsum_beta = "0.7.0" nshare = "0.9.0" numpy = { version = "0.18.0" } once_cell = "1.17.0" -openblas-src = { version = "*", features = ["cblas", "system"] } phf = { version = "*", features = ["macros"] } polars = { version = "0.27.2", features = [ "dtype-u8", From 814752932995f3ca085fd826370564a416a6242c Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 12:42:55 -0700 Subject: [PATCH 026/117] Remove unused dependencies. --- Cargo.lock | 539 +----------------------------------------------- rust/Cargo.toml | 15 +- 2 files changed, 3 insertions(+), 551 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index f6e0c6cc..461d6f6d 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -2,15 +2,6 @@ # It is not intended for manual editing. version = 3 -[[package]] -name = "addr2line" -version = "0.19.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "a76fd60b23679b7d19bd066031410fb7e458ccc5e958eb5c325888ce4baedc97" -dependencies = [ - "gimli", -] - [[package]] name = "adler" version = "1.0.2" @@ -75,36 +66,12 @@ version = "1.0.69" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "224afbd727c3d6e4b90103ece64b8d1b67fbb1973b1046c2281eed3f3803f800" -[[package]] -name = "approx" -version = "0.4.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "3f2a05fd1bd10b2527e20a2cd32d8873d115b8b39fe219ee25f42a8aca6ba278" -dependencies = [ - "num-traits", -] - -[[package]] -name = "approx" -version = "0.5.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6" -dependencies = [ - "num-traits", -] - [[package]] name = "array-init-cursor" version = "0.2.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "bf7d0a018de4f6aa429b9d33d69edf69072b1c5b1cb8d3e4a5f7ef898fc3eb76" -[[package]] -name = "arrayvec" -version = "0.7.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "8da52d66c7071e2e3fa2a1e5c6d088fec47b593032b254f5e980de8ea54454d6" - [[package]] name = "arrow-format" version = "0.8.1" @@ -203,40 +170,16 @@ dependencies = [ "anyhow", "bincode", "criterion", - "dirs", "glob", - "indicatif", "itertools", "ndarray", - "ndarray_einsum_beta", - "nshare", "numpy", "once_cell", - "phf", "polars", - "pprof", "pyo3", "pyo3-polars", "rayon", "serde", - "strum", - "strum_macros", - "walkdir", -] - -[[package]] -name = "backtrace" -version = "0.3.67" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "233d376d6d185f2a3093e58f283f60f880315b6c60075b01f36b3b85154564ca" -dependencies = [ - "addr2line", - "cc", - "cfg-if", - "libc", - "miniz_oxide", - "object", - "rustc-demangle", ] [[package]] @@ -307,12 +250,6 @@ dependencies = [ "syn", ] -[[package]] -name = "byteorder" -version = "1.4.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "14c189c53d098945499cdfa7ecc63567cf3886b3332b312a5b4585d8d3a6a610" - [[package]] name = "bytes" version = "1.4.0" @@ -413,12 +350,6 @@ dependencies = [ "unicode-width", ] -[[package]] -name = "color_quant" -version = "1.1.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "3d7b894f5411737b7867f4827955924d7c254fc9f4d91a6aad6b097804b1018b" - [[package]] name = "comfy-table" version = "6.1.4" @@ -431,19 +362,6 @@ dependencies = [ "unicode-width", ] -[[package]] -name = "console" -version = "0.15.5" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "c3d79fbe8970a77e3e34151cc13d3b3e248aa0faaecb9f6091fa07ebefe5ad60" -dependencies = [ - "encode_unicode", - "lazy_static", - "libc", - "unicode-width", - "windows-sys 0.42.0", -] - [[package]] name = "const-random" version = "0.1.15" @@ -472,15 +390,6 @@ version = "0.8.3" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "5827cebf4670468b8772dd191856768aedcb1b0278a04f989f7766351917b9dc" -[[package]] -name = "cpp_demangle" -version = "0.4.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "b446fd40bcc17eddd6a4a78f24315eb90afdb3334999ddfd4909985c47722442" -dependencies = [ - "cfg-if", -] - [[package]] name = "crc32fast" version = "1.3.2" @@ -644,15 +553,6 @@ dependencies = [ "syn", ] -[[package]] -name = "debugid" -version = "0.8.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "bef552e6f588e446098f6ba40d89ac146c8c7b64aade83c051ee00bb5d2bc18d" -dependencies = [ - "uuid", -] - [[package]] name = "dirs" version = "4.0.0" @@ -685,12 +585,6 @@ version = "1.8.1" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "7fcaabb2fef8c910e7f4c7ce9f67a1283a1715879a7c230ca9d6d1ae31f16d91" -[[package]] -name = "encode_unicode" -version = "0.3.6" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "a357d28ed41a50f9c765dbfe56cbc04a64e53e5fc58ba79fbc34c10ef3df831f" - [[package]] name = "enum_dispatch" version = "0.3.11" @@ -703,27 +597,6 @@ dependencies = [ "syn", ] -[[package]] -name = "errno" -version = "0.2.8" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "f639046355ee4f37944e44f60642c6f3a7efa3cf6b78c78a0d989a8ce6c396a1" -dependencies = [ - "errno-dragonfly", - "libc", - "winapi", -] - -[[package]] -name = "errno-dragonfly" -version = "0.1.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "aa68f1b12764fab894d2755d2518754e71b4fd80ecfb822714a1206c2aab39bf" -dependencies = [ - "cc", - "libc", -] - [[package]] name = "ethnum" version = "1.3.2" @@ -736,27 +609,6 @@ version = "0.1.9" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "7360491ce676a36bf9bb3c56c1aa791658183a54d2744120f27285738d90465a" -[[package]] -name = "fastrand" -version = "1.9.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "e51093e27b0797c359783294ca4f0a911c270184cb10f85783b118614a1501be" -dependencies = [ - "instant", -] - -[[package]] -name = "findshlibs" -version = "0.10.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "40b9e59cd0f7e0806cca4be089683ecb6434e602038df21fe6bf6711b2f07f64" -dependencies = [ - "cc", - "lazy_static", - "libc", - "winapi", -] - [[package]] name = "flate2" version = "1.0.25" @@ -875,12 +727,6 @@ dependencies = [ "wasm-bindgen", ] -[[package]] -name = "gimli" -version = "0.27.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "ad0a93d233ebf96623465aad4046a8d3aa4da22d4f4beba5388838c8a434bbb4" - [[package]] name = "glob" version = "0.3.1" @@ -939,12 +785,6 @@ dependencies = [ "libc", ] -[[package]] -name = "hermit-abi" -version = "0.3.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "fed44880c466736ef9a5c5b5facefb5ed0785676d0c02d612db14e54f0d84286" - [[package]] name = "iana-time-zone" version = "0.1.53" @@ -969,19 +809,6 @@ dependencies = [ "cxx-build", ] -[[package]] -name = "image" -version = "0.24.5" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "69b7ea949b537b0fd0af141fff8c77690f2ce96f4f41f042ccb6c69c6c965945" -dependencies = [ - "bytemuck", - "byteorder", - "color_quant", - "num-rational", - "num-traits", -] - [[package]] name = "indexmap" version = "1.9.2" @@ -992,43 +819,12 @@ dependencies = [ "hashbrown 0.12.3", ] -[[package]] -name = "indicatif" -version = "0.17.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "cef509aa9bc73864d6756f0d34d35504af3cf0844373afe9b8669a5b8005a729" -dependencies = [ - "console", - "number_prefix", - "portable-atomic", - "rayon", - "unicode-width", -] - [[package]] name = "indoc" version = "1.0.9" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "bfa799dd5ed20a7e349f3b4639aa80d74549c81716d9ec4f994c9b5815598306" -[[package]] -name = "inferno" -version = "0.11.15" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "2fb7c1b80a1dfa604bb4a649a5c5aeef3d913f7c520cb42b40e534e8a61bcdfc" -dependencies = [ - "ahash", - "indexmap", - "is-terminal", - "itoa", - "log", - "num-format", - "once_cell", - "quick-xml", - "rgb", - "str_stack", -] - [[package]] name = "instant" version = "0.1.12" @@ -1038,28 +834,6 @@ dependencies = [ "cfg-if", ] -[[package]] -name = "io-lifetimes" -version = "1.0.6" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "cfa919a82ea574332e2de6e74b4c36e74d41982b335080fa59d4ef31be20fdf3" -dependencies = [ - "libc", - "windows-sys 0.45.0", -] - -[[package]] -name = "is-terminal" -version = "0.4.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "21b6b32576413a8e69b90e952e4a026476040d81017b80445deda5f2d3921857" -dependencies = [ - "hermit-abi 0.3.1", - "io-lifetimes", - "rustix", - "windows-sys 0.45.0", -] - [[package]] name = "itertools" version = "0.10.5" @@ -1193,12 +967,6 @@ dependencies = [ "cc", ] -[[package]] -name = "linux-raw-sys" -version = "0.1.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "f051f77a7c8e6957c0696eac88f26b0117e54f52d3fc682ab19397a8812846a4" - [[package]] name = "lock_api" version = "0.4.9" @@ -1292,7 +1060,7 @@ dependencies = [ "libc", "log", "wasi 0.11.0+wasi-snapshot-preview1", - "windows-sys 0.45.0", + "windows-sys", ] [[package]] @@ -1315,28 +1083,12 @@ dependencies = [ "syn", ] -[[package]] -name = "nalgebra" -version = "0.30.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "4fb2d0de08694bed883320212c18ee3008576bfe8c306f4c3c4a58b4876998be" -dependencies = [ - "approx 0.5.1", - "matrixmultiply", - "num-complex", - "num-rational", - "num-traits", - "simba", - "typenum", -] - [[package]] name = "ndarray" version = "0.15.6" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "adb12d4e967ec485a5f71c6311fe28158e9d6f4bc4a447b474184d0f91a8fa32" dependencies = [ - "approx 0.4.0", "matrixmultiply", "num-complex", "num-integer", @@ -1345,30 +1097,6 @@ dependencies = [ "rayon", ] -[[package]] -name = "ndarray_einsum_beta" -version = "0.7.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "668b3abeae3e0637740340e0e32a9bf9308380e146ea6797950f9ff16e88d88a" -dependencies = [ - "lazy_static", - "ndarray", - "num-traits", - "regex", -] - -[[package]] -name = "nix" -version = "0.26.2" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "bfdda3d196821d6af13126e40375cdf7da646a96114af134d5f417a9a1dc8e1a" -dependencies = [ - "bitflags", - "cfg-if", - "libc", - "static_assertions", -] - [[package]] name = "now" version = "0.1.3" @@ -1378,17 +1106,6 @@ dependencies = [ "chrono", ] -[[package]] -name = "nshare" -version = "0.9.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "4447657cd40e3107416ec4f2ac3e61a18781b00061789e3b8f4bbcbccb26c4c6" -dependencies = [ - "image", - "nalgebra", - "ndarray", -] - [[package]] name = "ntapi" version = "0.4.0" @@ -1432,16 +1149,6 @@ dependencies = [ "num-traits", ] -[[package]] -name = "num-format" -version = "0.4.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "a652d9771a63711fd3c3deb670acfbe5c30a4072e664d7a3bf5a9e1056ac72c3" -dependencies = [ - "arrayvec", - "itoa", -] - [[package]] name = "num-integer" version = "0.1.45" @@ -1495,12 +1202,6 @@ dependencies = [ "libc", ] -[[package]] -name = "number_prefix" -version = "0.4.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "830b246a0e5f20af87141b25c173cd1b609bd7779a4617d6ec582abaf90870f3" - [[package]] name = "numpy" version = "0.18.0" @@ -1516,15 +1217,6 @@ dependencies = [ "rustc-hash", ] -[[package]] -name = "object" -version = "0.30.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "ea86265d3d3dcb6a27fc51bd29a4bf387fae9d2986b823079d4986af253eb439" -dependencies = [ - "memchr", -] - [[package]] name = "once_cell" version = "1.17.1" @@ -1588,7 +1280,7 @@ dependencies = [ "libc", "redox_syscall", "smallvec", - "windows-sys 0.45.0", + "windows-sys", ] [[package]] @@ -1619,54 +1311,6 @@ dependencies = [ "zstd", ] -[[package]] -name = "paste" -version = "1.0.12" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "9f746c4065a8fa3fe23974dd82f15431cc8d40779821001404d10d2e79ca7d79" - -[[package]] -name = "phf" -version = "0.11.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "928c6535de93548188ef63bb7c4036bd415cd8f36ad25af44b9789b2ee72a48c" -dependencies = [ - "phf_macros", - "phf_shared", -] - -[[package]] -name = "phf_generator" 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"26f6a7b87c2e435a3241addceeeff740ff8b7e76b74c13bf9acb17fa454ea00b" - -[[package]] -name = "pprof" -version = "0.11.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "196ded5d4be535690899a4631cc9f18cdc41b7ebf24a79400f46f48e49a11059" -dependencies = [ - "backtrace", - "cfg-if", - "criterion", - "findshlibs", - "inferno", - "libc", - "log", - "nix", - "once_cell", - "parking_lot 0.12.1", - "smallvec", - "symbolic-demangle", - "tempfile", - "thiserror", -] - [[package]] name = "ppv-lite86" version = "0.2.17" @@ -2025,15 +1641,6 @@ dependencies = [ "thiserror", ] -[[package]] -name = "quick-xml" -version = "0.26.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "7f50b1c63b38611e7d4d7f68b82d3ad0cc71a2ad2e7f61fc10f1328d917c93cd" -dependencies = [ - "memchr", -] - [[package]] name = "quote" version = "1.0.23" @@ -2148,21 +1755,6 @@ version = "0.6.28" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = 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= "1.0.13" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "f91339c0467de62360649f8d3e185ca8de4224ff281f66000de5eb2a77a79041" -[[package]] -name = "safe_arch" -version = "0.6.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "794821e4ccb0d9f979512f9c1973480123f9bd62a90d74ab0f9426fcf8f4a529" -dependencies = [ - "bytemuck", -] - [[package]] name = "same-file" version = "1.0.6" @@ -2307,31 +1876,12 @@ dependencies = [ "libc", ] -[[package]] -name = "simba" -version = "0.7.3" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "2f3fd720c48c53cace224ae62bef1bbff363a70c68c4802a78b5cc6159618176" -dependencies = [ - "approx 0.5.1", - "num-complex", - "num-traits", - "paste", - "wide", -] - [[package]] name = "simdutf8" version = "0.1.4" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "f27f6278552951f1f2b8cf9da965d10969b2efdea95a6ec47987ab46edfe263a" -[[package]] -name = "siphasher" 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- [[package]] name = "streaming-decompression" version = "0.1.2" @@ -2422,29 +1960,6 @@ dependencies = [ "syn", ] -[[package]] -name = "symbolic-common" -version = "10.2.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "1b55cdc318ede251d0957f07afe5fed912119b8c1bc5a7804151826db999e737" -dependencies = [ - "debugid", - "memmap2", - "stable_deref_trait", - "uuid", -] - -[[package]] -name = "symbolic-demangle" -version = "10.2.1" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "79be897be8a483a81fff6a3a4e195b4ac838ef73ca42d348b3f722da9902e489" -dependencies = [ - "cpp_demangle", - "rustc-demangle", - "symbolic-common", -] - [[package]] name = "syn" version = "1.0.109" @@ -2476,19 +1991,6 @@ version = "0.12.6" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "8ae9980cab1db3fceee2f6c6f643d5d8de2997c58ee8d25fb0cc8a9e9e7348e5" -[[package]] -name = "tempfile" -version = "3.4.0" -source = 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"version_check" version = "0.9.4" @@ -2713,16 +2203,6 @@ dependencies = [ "wasm-bindgen", ] -[[package]] -name = "wide" -version = "0.7.8" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "b689b6c49d6549434bf944e6b0f39238cf63693cb7a147e9d887507fffa3b223" -dependencies = [ - "bytemuck", - "safe_arch", -] - [[package]] name = "winapi" version = "0.3.9" @@ -2754,21 +2234,6 @@ version = "0.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "712e227841d057c1ee1cd2fb22fa7e5a5461ae8e48fa2ca79ec42cfc1931183f" -[[package]] -name = "windows-sys" -version = "0.42.0" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "5a3e1820f08b8513f676f7ab6c1f99ff312fb97b553d30ff4dd86f9f15728aa7" -dependencies = [ - "windows_aarch64_gnullvm", - "windows_aarch64_msvc", - "windows_i686_gnu", - "windows_i686_msvc", - "windows_x86_64_gnu", - "windows_x86_64_gnullvm", - "windows_x86_64_msvc", -] - [[package]] name = "windows-sys" version = "0.45.0" diff --git a/rust/Cargo.toml b/rust/Cargo.toml index e5084571..e5bb8789 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -15,33 +15,20 @@ crate-type = ["cdylib"] anyhow = "1.0.66" bincode = "1.3.3" criterion = "0.4.0" -dirs = "4.0.0" glob = "0.3.1" -indicatif = { version = "0.17.3", features = ["rayon"] } itertools = "0.10.5" ndarray = { version = "0.15.6", features = ["matrixmultiply-threading", "rayon"] } -ndarray_einsum_beta = "0.7.0" -nshare = "0.9.0" numpy = { version = "0.18.0" } -once_cell = "1.17.0" -phf = { version = "*", features = ["macros"] } +once_cell = "1.17.1" polars = { version = "0.27.2", features = [ "dtype-u8", - "dtype-u16", - "is_in", "lazy", "ndarray", "parquet", - "partition_by", "ipc", - "rows", "serde", ] } -pprof = { version = "0.11.0", features = ["criterion", "flamegraph"] } pyo3 = { version = "0.18.1", features = ["extension-module"] } pyo3-polars = { git = "https://github.com/benjaminrwilson/pyo3-polars" } rayon = "1.6.1" serde = "1.0.155" -strum = "0.24.1" -strum_macros = "0.24.3" -walkdir = "2.3.2" From afe9baf6c44e2ff1d8163757d2c4f0dc0f67e81d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:14:13 -0700 Subject: [PATCH 027/117] Add scene flow dataloader. --- src/av2/_r.pyi | 4 +- src/av2/torch/dataloaders/scene_flow.py | 102 ++++++++++++++++++++++++ src/av2/torch/dataloaders/sensor.py | 8 +- src/av2/torch/dataloaders/utils.py | 8 ++ tutorials/torch_dataloader.py | 8 +- 5 files changed, 122 insertions(+), 8 deletions(-) create mode 100644 src/av2/torch/dataloaders/scene_flow.py diff --git a/src/av2/_r.pyi b/src/av2/_r.pyi index 008c6aa9..0e9044f2 100644 --- a/src/av2/_r.pyi +++ b/src/av2/_r.pyi @@ -1,6 +1,6 @@ """Rust backend typing stubs.""" -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Tuple import polars as pl @@ -14,6 +14,8 @@ class Dataloader: num_accum_sweeps: int memory_map: bool + file_index: pl.DataFrame = field(init=False) + def get(self, index: int) -> Sweep: ... def __len__(self) -> int: ... diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py new file mode 100644 index 00000000..9f56f516 --- /dev/null +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -0,0 +1,102 @@ +"""Pytorch dataloader for the Argoverse 2 dataset.""" + +from __future__ import annotations + +import logging +from dataclasses import dataclass, field +from functools import cached_property +from math import inf +from typing import Optional, Tuple + +import pandas as pd +from torch.utils.data import Dataset + +import av2._r as r +from av2.torch.dataloaders.utils import Annotations, Lidar +from av2.utils.typing import PathType + +from .utils import Pose, Sweep + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +@dataclass +class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): + """Pytorch dataloader for the sensor dataset. + + Args: + root_dir: Path to the dataset directory. + dataset_name: Dataset name. + split_name: Name of the dataset split. + min_annotation_range: Min Euclidean distance between the egovehicle origin and the annotation cuboid centers. + max_annotation_range: Max Euclidean distance between the egovehicle origin and the annotation cuboid centers. + min_lidar_range: Min Euclidean distance between the egovehicle origin and the lidar points. + max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. + min_interior_pts: Min number of points inside each annotation. + num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). + file_caching_mode: File caching mode. + return_annotations: Boolean flag indicating whether to return annotations. + return_velocity_estimates: Boolean flag indicating whether to return annotations' velocity estimates. + """ + + root_dir: PathType + dataset_name: str + split_name: str + min_annotation_range: float = 0.0 + max_annotation_range: float = inf + min_lidar_range: float = 0.0 + max_lidar_range: float = inf + min_interior_pts: int = 0 + num_accum_sweeps: int = 1 + return_annotations: bool = False + return_velocity_estimates: bool = False + memory_map: bool = False + + _backend: r.Dataloader = field(init=False) + _current_idx: int = 0 + + def __post_init__(self) -> None: + """Build the file index.""" + if self.return_annotations and self.dataset_name == "lidar": + raise RuntimeError("The lidar dataset does not have annotations!") + if not self.return_annotations and self.return_velocity_estimates: + raise RuntimeError("with_annotations must be enabled to return annotations' velocities.") + + self._backend = r.Dataloader( + str(self.root_dir), + "sensor", + self.split_name, + self.dataset_name, + self.num_accum_sweeps, + self.memory_map, + ) + + @cached_property + def file_index(self) -> pd.DataFrame: + return self._backend.file_index.to_pandas() + + def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: + sweep = self._backend.get(index) + next_sweep = None + + next_index = index + 1 + if next_index < len(self): + candidate_log_id: str = self.file_index.loc[index + 1, ["log_id"]].item() + current_log_id = sweep.sweep_uuid[0] + if candidate_log_id == current_log_id: + next_sweep = Sweep.from_rust(self._backend.get(next_index)) + return Sweep.from_rust(sweep), next_sweep + + def __len__(self) -> int: + return self._backend.__len__() + + def __iter__(self): + return self + + def __next__(self): + if self._current_idx >= self.__len__(): + raise StopIteration + datum = self.__getitem__(self._current_idx) + self._current_idx += 1 + return datum diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 1caa4a4c..86168efa 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -72,11 +72,9 @@ def __post_init__(self) -> None: def __getitem__(self, index: int) -> Sweep: sweep = self._backend.get(index) annotations = Annotations(dataframe=sweep.annotations.to_pandas()) - city_pose = Pose(dataframe=sweep.city_pose) + city_pose = Pose(dataframe=sweep.city_pose.to_pandas()) lidar = Lidar(dataframe=sweep.lidar.to_pandas()) sweep = Sweep(annotations=annotations, city_pose=city_pose, lidar=lidar, sweep_uuid=sweep.sweep_uuid) - - self._current_idx += 1 return sweep def __len__(self) -> int: @@ -88,4 +86,6 @@ def __iter__(self): def __next__(self): if self._current_idx >= self.__len__(): raise StopIteration - return self.__getitem__(self._current_idx) + datum = self.__getitem__(self._current_idx) + self._current_idx += 1 + return datum diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 4bb22e6a..20ad9a23 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -15,6 +15,7 @@ import torch from torch import Tensor +import av2._r as r from av2.geometry.geometry import mat_to_xyz, quat_to_mat from av2.geometry.se3 import SE3 from av2.utils.typing import NDArrayFloat @@ -215,6 +216,13 @@ class Sweep: lidar: Lidar sweep_uuid: Tuple[str, int] + @classmethod + def from_rust(cls, sweep: r.Sweep) -> Sweep: + annotations = Annotations(dataframe=sweep.annotations.to_pandas()) + city_pose = Pose(dataframe=sweep.city_pose.to_pandas()) + lidar = Lidar(dataframe=sweep.lidar.to_pandas()) + return cls(annotations=annotations, city_pose=city_pose, lidar=lidar, sweep_uuid=sweep.sweep_uuid) + @dataclass(frozen=True) class Pose: diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index 85012017..e434ba3a 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -4,6 +4,7 @@ from tqdm import tqdm +from av2.torch.dataloaders.scene_flow import SceneFlowDataloader from av2.torch.dataloaders.sensor import Dataloader @@ -16,9 +17,10 @@ def main(): split_name = "val" num_accum_sweeps = 5 - dataloader = Dataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) - for sweep in tqdm(dataloader): - lidar = sweep.lidar.as_tensor(field_ordering=("x", "y", "z", "intensity")) + dataloader = SceneFlowDataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) + for sweep, next_sweep in tqdm(dataloader): + print(sweep, next_sweep) + if __name__ == "__main__": main() From a7103f3a959fc00cac93651134d0d017374da8b6 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:15:28 -0700 Subject: [PATCH 028/117] Remove imports / comments. --- src/av2/torch/dataloaders/scene_flow.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 9f56f516..2c91cdbf 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -12,10 +12,9 @@ from torch.utils.data import Dataset import av2._r as r -from av2.torch.dataloaders.utils import Annotations, Lidar from av2.utils.typing import PathType -from .utils import Pose, Sweep +from .utils import Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -35,9 +34,7 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. min_interior_pts: Min number of points inside each annotation. num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). - file_caching_mode: File caching mode. return_annotations: Boolean flag indicating whether to return annotations. - return_velocity_estimates: Boolean flag indicating whether to return annotations' velocity estimates. """ root_dir: PathType @@ -50,7 +47,6 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): min_interior_pts: int = 0 num_accum_sweeps: int = 1 return_annotations: bool = False - return_velocity_estimates: bool = False memory_map: bool = False _backend: r.Dataloader = field(init=False) From b8407ba7dff4ee3963c1faaa29b7d26f8b46e472 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:16:02 -0700 Subject: [PATCH 029/117] Use next index. --- src/av2/torch/dataloaders/scene_flow.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 2c91cdbf..2600f9be 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -78,7 +78,7 @@ def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: next_index = index + 1 if next_index < len(self): - candidate_log_id: str = self.file_index.loc[index + 1, ["log_id"]].item() + candidate_log_id: str = self.file_index.loc[next_index, ["log_id"]].item() current_log_id = sweep.sweep_uuid[0] if candidate_log_id == current_log_id: next_sweep = Sweep.from_rust(self._backend.get(next_index)) From 67e05c99b0abaec97b86afd5dc825ad47ebc83ad Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:17:57 -0700 Subject: [PATCH 030/117] Remove init check. --- src/av2/torch/dataloaders/scene_flow.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 2600f9be..467112c1 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -56,8 +56,6 @@ def __post_init__(self) -> None: """Build the file index.""" if self.return_annotations and self.dataset_name == "lidar": raise RuntimeError("The lidar dataset does not have annotations!") - if not self.return_annotations and self.return_velocity_estimates: - raise RuntimeError("with_annotations must be enabled to return annotations' velocities.") self._backend = r.Dataloader( str(self.root_dir), From 667086cfd09af4d67d3d15b671b7989dd36b5b3d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:18:46 -0700 Subject: [PATCH 031/117] Remove unused args. --- src/av2/torch/dataloaders/scene_flow.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 467112c1..657b3199 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -34,7 +34,6 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. min_interior_pts: Min number of points inside each annotation. num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). - return_annotations: Boolean flag indicating whether to return annotations. """ root_dir: PathType @@ -46,17 +45,13 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): max_lidar_range: float = inf min_interior_pts: int = 0 num_accum_sweeps: int = 1 - return_annotations: bool = False memory_map: bool = False _backend: r.Dataloader = field(init=False) _current_idx: int = 0 def __post_init__(self) -> None: - """Build the file index.""" - if self.return_annotations and self.dataset_name == "lidar": - raise RuntimeError("The lidar dataset does not have annotations!") - + """Initialize Rust backend.""" self._backend = r.Dataloader( str(self.root_dir), "sensor", From 9ffbf878aeb6c6696b408b15147ab90aef1d9350 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:20:34 -0700 Subject: [PATCH 032/117] Use from rust in sensor dataloader. --- src/av2/torch/dataloaders/sensor.py | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 86168efa..4314e235 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -9,10 +9,9 @@ from torch.utils.data import Dataset import av2._r as r -from av2.torch.dataloaders.utils import Annotations, Lidar from av2.utils.typing import PathType -from .utils import Pose, Sweep +from .utils import Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -71,11 +70,7 @@ def __post_init__(self) -> None: def __getitem__(self, index: int) -> Sweep: sweep = self._backend.get(index) - annotations = Annotations(dataframe=sweep.annotations.to_pandas()) - city_pose = Pose(dataframe=sweep.city_pose.to_pandas()) - lidar = Lidar(dataframe=sweep.lidar.to_pandas()) - sweep = Sweep(annotations=annotations, city_pose=city_pose, lidar=lidar, sweep_uuid=sweep.sweep_uuid) - return sweep + return Sweep.from_rust(sweep) def __len__(self) -> int: return self._backend.__len__() From 59c4f2b257e8ff389ae134527b9576036823afcd Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:23:57 -0700 Subject: [PATCH 033/117] Fix typing issues. --- src/av2/torch/dataloaders/scene_flow.py | 2 +- src/av2/torch/dataloaders/sensor.py | 2 +- tutorials/torch_dataloader.py | 3 +-- 3 files changed, 3 insertions(+), 4 deletions(-) diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 657b3199..a1a1cb08 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -80,7 +80,7 @@ def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: def __len__(self) -> int: return self._backend.__len__() - def __iter__(self): + def __iter__(self) -> SceneFlowDataloader: return self def __next__(self): diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 4314e235..a027b99a 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -75,7 +75,7 @@ def __getitem__(self, index: int) -> Sweep: def __len__(self) -> int: return self._backend.__len__() - def __iter__(self): + def __iter__(self) -> Dataloader: return self def __next__(self): diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index e434ba3a..ec1e5efc 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -5,10 +5,9 @@ from tqdm import tqdm from av2.torch.dataloaders.scene_flow import SceneFlowDataloader -from av2.torch.dataloaders.sensor import Dataloader -def main(): +def main() -> None: """Iterate over the dataloader.""" # Dataset should live at ~/data/datasets/{dataset_name}/{split_name} From e335594ec57edbdfb6d7a34df41da5c1dfbe53b0 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:27:04 -0700 Subject: [PATCH 034/117] Change example default to 1 accum sweep. --- tutorials/torch_dataloader.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index ec1e5efc..59550d21 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -14,7 +14,7 @@ def main() -> None: root_dir = Path.home() / "data" / "datasets" dataset_name = "av2" split_name = "val" - num_accum_sweeps = 5 + num_accum_sweeps = 1 dataloader = SceneFlowDataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) for sweep, next_sweep in tqdm(dataloader): From ab9abbfbda6bade90eb25aa046381b5652dac1e0 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 13:51:12 -0700 Subject: [PATCH 035/117] Switch from lazy to eager loading. --- rust/src/io.rs | 18 ++++++++++++------ 1 file changed, 12 insertions(+), 6 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 0e441e71..68bfbb85 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -8,7 +8,7 @@ use polars::prelude::NamedFrom; use polars::prelude::concat; use polars::prelude::LazyFrame; -use polars::prelude::ScanArgsIpc; +use polars::prelude::SerReader; use polars::prelude::TakeRandom; use polars::series::Series; @@ -19,14 +19,19 @@ use polars::{ }; use rayon::prelude::IntoParallelIterator; use rayon::prelude::ParallelIterator; +use std::fs::File; use std::path::PathBuf; use crate::se3::SE3; use crate::so3::quat_to_mat; -pub fn read_frame(path: &PathBuf, _memmap: bool) -> LazyFrame { - let args = ScanArgsIpc::default(); - LazyFrame::scan_ipc(path, args).unwrap() +pub fn read_frame(path: &PathBuf, memory_mapped: bool) -> DataFrame { + let file = File::open(path).expect("File not found"); + let frame = polars::io::ipc::IpcReader::new(file) + .memory_mapped(memory_mapped) + .finish() + .expect(format!("This IPC file is malformed: {:?}.", path).as_str()); + frame } pub fn read_lidar( @@ -41,7 +46,7 @@ pub fn read_lidar( let log_ids = file_index["log_id"].utf8().unwrap(); let timestamps = file_index["timestamp_ns"].u64().unwrap(); let poses_path = log_dir.join("city_SE3_egovehicle.feather"); - let poses = read_frame(&poses_path, true).collect().unwrap(); + let poses = read_frame(&poses_path, true); let pose_ref = frame_to_ndarray_with_filter( &poses, @@ -70,7 +75,7 @@ pub fn read_lidar( .map(|i| { let timestamp_ns_i = timestamps.get(i).unwrap(); let lidar_path = get_lidar_path(log_dir.clone(), timestamp_ns_i); - let mut lidar = read_frame(&lidar_path, true); + let mut lidar = read_frame(&lidar_path, true).lazy(); let xyz = frame_to_ndarray(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); let timedeltas = Series::new( @@ -136,6 +141,7 @@ pub fn read_filter_timestamp( memory_map: bool, ) -> LazyFrame { read_frame(path, memory_map) + .lazy() .filter(col("timestamp_ns").eq(*timestamp_ns)) .select(&[cols(columns)]) } From cdf92539025031ac4c110dfe738b82bbdb683bef Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 14:09:21 -0700 Subject: [PATCH 036/117] Add memory_mapped flag. --- rust/src/io.rs | 7 ++++--- rust/src/lib.rs | 11 ++++++----- src/av2/torch/dataloaders/utils.py | 22 ++++++++++++++++------ 3 files changed, 26 insertions(+), 14 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 68bfbb85..674659ae 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -41,6 +41,7 @@ pub fn read_lidar( timestamp_ns: u64, idx: usize, num_accum_sweeps: usize, + memory_mapped: bool, ) -> LazyFrame { let start_idx = i64::max(idx as i64 - num_accum_sweeps as i64 + 1, 0) as usize; let log_ids = file_index["log_id"].utf8().unwrap(); @@ -75,7 +76,7 @@ pub fn read_lidar( .map(|i| { let timestamp_ns_i = timestamps.get(i).unwrap(); let lidar_path = get_lidar_path(log_dir.clone(), timestamp_ns_i); - let mut lidar = read_frame(&lidar_path, true).lazy(); + let mut lidar = read_frame(&lidar_path, memory_mapped).lazy(); let xyz = frame_to_ndarray(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); let timedeltas = Series::new( @@ -138,9 +139,9 @@ pub fn read_filter_timestamp( path: &PathBuf, columns: &Vec<&str>, timestamp_ns: &u64, - memory_map: bool, + memory_mapped: bool, ) -> LazyFrame { - read_frame(path, memory_map) + read_frame(path, memory_mapped) .lazy() .filter(col("timestamp_ns").eq(*timestamp_ns)) .select(&[cols(columns)]) diff --git a/rust/src/lib.rs b/rust/src/lib.rs index b3725e3c..e8d7944d 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -90,7 +90,7 @@ pub struct Dataloader { #[pyo3(get, set)] pub current_idx: usize, #[pyo3(get, set)] - pub memory_map: bool, + pub memory_mapped: bool, } #[pymethods] @@ -102,7 +102,7 @@ impl Dataloader { split_name: &str, dataset_name: &str, num_accum_sweeps: usize, - memory_map: bool, + memory_mapped: bool, ) -> Dataloader { let root_dir = Path::new(root_dir); let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); @@ -115,7 +115,7 @@ impl Dataloader { num_accum_sweeps, file_index: PyDataFrame(file_index), current_idx, - memory_map, + memory_mapped, } } @@ -173,6 +173,7 @@ impl Dataloader { timestamp_ns, idx, self.num_accum_sweeps, + self.memory_mapped, ) .collect() .unwrap(); @@ -182,7 +183,7 @@ impl Dataloader { &annotations_path, &ANNOTATION_COLUMNS.to_vec(), ×tamp_ns, - self.memory_map, + self.memory_mapped, ) .filter(col("num_interior_pts").gt_eq(1.)) .collect() @@ -193,7 +194,7 @@ impl Dataloader { &city_pose_path, &POSE_COLUMNS.to_vec(), ×tamp_ns, - self.memory_map, + self.memory_mapped, ) .collect() .unwrap(); diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 20ad9a23..7dd91616 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -7,7 +7,7 @@ from dataclasses import dataclass from enum import Enum, unique from functools import cached_property -from typing import Final, Optional, Tuple +from typing import Final, List, Optional, Tuple import fsspec.asyn import numpy as np @@ -20,8 +20,6 @@ from av2.geometry.se3 import SE3 from av2.utils.typing import NDArrayFloat -MAX_STR_LEN: Final[int] = 32 - DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( "tx_m", "ty_m", @@ -137,20 +135,32 @@ class Annotations: dataframe: pd.DataFrame cuboid_mode: CuboidMode = CuboidMode.XYZLWH_QWXYZ + @property + def category_names(self) -> List[str]: + """Return the category names.""" + category_names: List[str] = self.dataframe["category"].to_list() + return category_names + + @property + def track_uuids(self) -> List[str]: + """Return the unique track identifiers.""" + category_names: List[str] = self.dataframe["track_uuid"].to_list() + return category_names + def as_tensor( self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_THETA, dtype: torch.dtype = torch.float32, ) -> Tensor: - """Return the lidar sweep as a dense tensor. + """Return the annotations as a tensor. Args: cuboid_mode: Target parameterization for the cuboids. dtype: Target datatype for casting. Returns: - (N,K) tensor where N is the number of lidar points and K - is the number of features. + (N,K) tensor where N is the number of annotations and K + is the number of annotation fields. """ dataframe = CuboidMode.convert(self.dataframe, self.cuboid_mode, cuboid_mode) return torch.as_tensor(dataframe.to_numpy(), dtype=dtype) From 85899126017a77b569da175ef89a61e62950431c Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 14:42:41 -0700 Subject: [PATCH 037/117] Add docstrings. --- rust/src/io.rs | 9 ++++++--- rust/src/lib.rs | 14 ++++++++++++++ rust/src/ops.rs | 4 ++++ rust/src/path.rs | 4 ++++ rust/src/se3.rs | 4 ++++ rust/src/so3.rs | 4 ++++ 6 files changed, 36 insertions(+), 3 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 674659ae..5eeb1c69 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -1,3 +1,7 @@ +//! # io +//! +//! Reading and writing operations. + use ndarray::s; use ndarray::Array2; @@ -27,11 +31,10 @@ use crate::so3::quat_to_mat; pub fn read_frame(path: &PathBuf, memory_mapped: bool) -> DataFrame { let file = File::open(path).expect("File not found"); - let frame = polars::io::ipc::IpcReader::new(file) + polars::io::ipc::IpcReader::new(file) .memory_mapped(memory_mapped) .finish() - .expect(format!("This IPC file is malformed: {:?}.", path).as_str()); - frame + .unwrap_or_else(|_| panic!("This IPC file is malformed: {:?}.", path)) } pub fn read_lidar( diff --git a/rust/src/lib.rs b/rust/src/lib.rs index e8d7944d..393da95b 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -1,3 +1,10 @@ +//! # av2 +//! +//! Argoverse rust library. + +#![warn(missing_docs)] +#![warn(missing_doc_code_examples)] + pub mod io; pub mod ops; pub mod path; @@ -24,6 +31,7 @@ use pyo3::types::PyBytes; use crate::ops::voxelize; +/// Annotation dataframe columns. pub const ANNOTATION_COLUMNS: [&str; 13] = [ "tx_m", "ty_m", @@ -40,16 +48,22 @@ pub const ANNOTATION_COLUMNS: [&str; 13] = [ "track_uuid", ]; +/// Pose dataframe columns. pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; +/// Data associated with a single lidar sweep. #[pyclass] pub struct Sweep { + /// Ground truth annotations. #[pyo3(get, set)] pub annotations: PyDataFrame, + /// Ego-vehicle city pose. #[pyo3(get, set)] pub city_pose: PyDataFrame, + /// Point cloud associated with the sweep. #[pyo3(get, set)] pub lidar: PyDataFrame, + /// Log id and nanosecond timestamp (unique identifier). #[pyo3(get, set)] pub sweep_uuid: (String, u64), } diff --git a/rust/src/ops.rs b/rust/src/ops.rs index fe683e3d..77282bff 100644 --- a/rust/src/ops.rs +++ b/rust/src/ops.rs @@ -1,3 +1,7 @@ +//! # ops +//! +//! Optimized operations for data processing. + use itertools::Itertools; use ndarray::{azip, par_azip, s, Array1, Array2, ArrayView2, Axis}; use std::{ diff --git a/rust/src/path.rs b/rust/src/path.rs index deb30b84..cfc4312c 100644 --- a/rust/src/path.rs +++ b/rust/src/path.rs @@ -1,3 +1,7 @@ +//! # path +//! +//! File path traversal utilities. + use anyhow::{Context, Result}; use std::fs; use std::path::PathBuf; diff --git a/rust/src/se3.rs b/rust/src/se3.rs index 547a6fe4..b148b0c3 100644 --- a/rust/src/se3.rs +++ b/rust/src/se3.rs @@ -1,3 +1,7 @@ +//! # SE3 +//! +//! Special Euclidean Group in 3 Dimensions. + use ndarray::{s, Array1, Array2, ArrayView2}; pub struct SE3 { diff --git a/rust/src/so3.rs b/rust/src/so3.rs index 417538d7..bb23509f 100644 --- a/rust/src/so3.rs +++ b/rust/src/so3.rs @@ -1,3 +1,7 @@ +//! # SO3 +//! +//! Special Orthogonal Group in 3 Dimensions. + use ndarray::{Array2, ArrayView1}; pub fn quat_to_mat(quat_wxyz: &ArrayView1) -> Array2 { From aadb725d0150479943fc1954b4fd694eb3d14c88 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:17:52 -0700 Subject: [PATCH 038/117] Add docstrings. --- src/av2/torch/dataloaders/scene_flow.py | 25 +++++++++-------------- src/av2/torch/dataloaders/sensor.py | 27 ++++++------------------- 2 files changed, 16 insertions(+), 36 deletions(-) diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index a1a1cb08..88afaac0 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -1,11 +1,10 @@ -"""Pytorch dataloader for the Argoverse 2 dataset.""" +"""Pytorch dataloader for the Argoverse 2 Scene Flow task.""" from __future__ import annotations import logging from dataclasses import dataclass, field from functools import cached_property -from math import inf from typing import Optional, Tuple import pandas as pd @@ -28,24 +27,15 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): root_dir: Path to the dataset directory. dataset_name: Dataset name. split_name: Name of the dataset split. - min_annotation_range: Min Euclidean distance between the egovehicle origin and the annotation cuboid centers. - max_annotation_range: Max Euclidean distance between the egovehicle origin and the annotation cuboid centers. - min_lidar_range: Min Euclidean distance between the egovehicle origin and the lidar points. - max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. - min_interior_pts: Min number of points inside each annotation. num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). + memory_mapped: Boolean flag indicating whether to memory map the dataframes. """ root_dir: PathType dataset_name: str split_name: str - min_annotation_range: float = 0.0 - max_annotation_range: float = inf - min_lidar_range: float = 0.0 - max_lidar_range: float = inf - min_interior_pts: int = 0 num_accum_sweeps: int = 1 - memory_map: bool = False + memory_mapped: bool = False _backend: r.Dataloader = field(init=False) _current_idx: int = 0 @@ -58,14 +48,16 @@ def __post_init__(self) -> None: self.split_name, self.dataset_name, self.num_accum_sweeps, - self.memory_map, + self.memory_mapped, ) @cached_property def file_index(self) -> pd.DataFrame: + """File index dataframe composed of (log_id, timestamp_ns).""" return self._backend.file_index.to_pandas() def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: + """Get a tuple of sweeps for scene flow.""" sweep = self._backend.get(index) next_sweep = None @@ -78,12 +70,15 @@ def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: return Sweep.from_rust(sweep), next_sweep def __len__(self) -> int: + """Length of the dataloader.""" return self._backend.__len__() def __iter__(self) -> SceneFlowDataloader: + """Iterate method for the dataloader.""" return self - def __next__(self): + def __next__(self) -> Tuple[Sweep, Optional[Sweep]]: + """Return a tuple of sweeps for scene flow.""" if self._current_idx >= self.__len__(): raise StopIteration datum = self.__getitem__(self._current_idx) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index a027b99a..78cc1ec4 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -25,40 +25,21 @@ class Dataloader(Dataset[Sweep]): root_dir: Path to the dataset directory. dataset_name: Dataset name. split_name: Name of the dataset split. - min_annotation_range: Min Euclidean distance between the egovehicle origin and the annotation cuboid centers. - max_annotation_range: Max Euclidean distance between the egovehicle origin and the annotation cuboid centers. - min_lidar_range: Min Euclidean distance between the egovehicle origin and the lidar points. - max_lidar_range: Max Euclidean distance between the egovehicle origin and the lidar points. - min_interior_pts: Min number of points inside each annotation. num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). - file_caching_mode: File caching mode. - return_annotations: Boolean flag indicating whether to return annotations. - return_velocity_estimates: Boolean flag indicating whether to return annotations' velocity estimates. + memory_mapped: Boolean flag indicating whether to memory map the dataframes. """ root_dir: PathType dataset_name: str split_name: str - min_annotation_range: float = 0.0 - max_annotation_range: float = inf - min_lidar_range: float = 0.0 - max_lidar_range: float = inf - min_interior_pts: int = 0 num_accum_sweeps: int = 1 - return_annotations: bool = False - return_velocity_estimates: bool = False memory_map: bool = False _backend: r.Dataloader = field(init=False) _current_idx: int = 0 def __post_init__(self) -> None: - """Build the file index.""" - if self.return_annotations and self.dataset_name == "lidar": - raise RuntimeError("The lidar dataset does not have annotations!") - if not self.return_annotations and self.return_velocity_estimates: - raise RuntimeError("with_annotations must be enabled to return annotations' velocities.") - + """Initialize Rust backend.""" self._backend = r.Dataloader( str(self.root_dir), "sensor", @@ -69,16 +50,20 @@ def __post_init__(self) -> None: ) def __getitem__(self, index: int) -> Sweep: + """Get a sweep from the sensor dataset.""" sweep = self._backend.get(index) return Sweep.from_rust(sweep) def __len__(self) -> int: + """Length of the sensor dataset (number of sweeps).""" return self._backend.__len__() def __iter__(self) -> Dataloader: + """Iterate method for the dataloader.""" return self def __next__(self): + """Return the next sweep.""" if self._current_idx >= self.__len__(): raise StopIteration datum = self.__getitem__(self._current_idx) From 1de301d0d0ecba0ceb1d215baa57e040f0bd18c5 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:18:45 -0700 Subject: [PATCH 039/117] Add type. --- src/av2/torch/dataloaders/sensor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 78cc1ec4..11c64665 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -62,7 +62,7 @@ def __iter__(self) -> Dataloader: """Iterate method for the dataloader.""" return self - def __next__(self): + def __next__(self) -> Sweep: """Return the next sweep.""" if self._current_idx >= self.__len__(): raise StopIteration From 2d12c302d9cfee2e6bf84c882a79ba1b15e7471e Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:18:59 -0700 Subject: [PATCH 040/117] Remove unused import. --- src/av2/torch/dataloaders/sensor.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/sensor.py index 11c64665..33fcb170 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/sensor.py @@ -4,7 +4,6 @@ import logging from dataclasses import dataclass, field -from math import inf from torch.utils.data import Dataset From 919fd8acb0ff06e816fdd1f41955cd4cb59e296c Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:34:34 -0700 Subject: [PATCH 041/117] Fix lint. --- tutorials/torch_dataloader.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/tutorials/torch_dataloader.py b/tutorials/torch_dataloader.py index 59550d21..0fec34cd 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/torch_dataloader.py @@ -4,21 +4,20 @@ from tqdm import tqdm -from av2.torch.dataloaders.scene_flow import SceneFlowDataloader +from av2.torch.dataloaders.sensor import Dataloader def main() -> None: """Iterate over the dataloader.""" - # Dataset should live at ~/data/datasets/{dataset_name}/{split_name} root_dir = Path.home() / "data" / "datasets" dataset_name = "av2" split_name = "val" num_accum_sweeps = 1 - dataloader = SceneFlowDataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) - for sweep, next_sweep in tqdm(dataloader): - print(sweep, next_sweep) + dataloader = Dataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) + for sweep in tqdm(dataloader): + print(sweep.lidar.as_tensor()) if __name__ == "__main__": From 0c62256af82b7ecb06cba64545f01b4d94e66107 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:37:09 -0700 Subject: [PATCH 042/117] Update naming + docstrings. --- src/av2/torch/dataloaders/{sensor.py => detection.py} | 6 +++--- src/av2/torch/dataloaders/scene_flow.py | 2 +- tutorials/{torch_dataloader.py => detection_dataloader.py} | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) rename src/av2/torch/dataloaders/{sensor.py => detection.py} (92%) rename tutorials/{torch_dataloader.py => detection_dataloader.py} (73%) diff --git a/src/av2/torch/dataloaders/sensor.py b/src/av2/torch/dataloaders/detection.py similarity index 92% rename from src/av2/torch/dataloaders/sensor.py rename to src/av2/torch/dataloaders/detection.py index 33fcb170..9ee89553 100644 --- a/src/av2/torch/dataloaders/sensor.py +++ b/src/av2/torch/dataloaders/detection.py @@ -1,4 +1,4 @@ -"""Pytorch dataloader for the Argoverse 2 dataset.""" +"""Pytorch dataloader for 3D object detection task.""" from __future__ import annotations @@ -17,7 +17,7 @@ @dataclass -class Dataloader(Dataset[Sweep]): +class DetectionDataloader(Dataset[Sweep]): """Pytorch dataloader for the sensor dataset. Args: @@ -57,7 +57,7 @@ def __len__(self) -> int: """Length of the sensor dataset (number of sweeps).""" return self._backend.__len__() - def __iter__(self) -> Dataloader: + def __iter__(self) -> DetectionDataloader: """Iterate method for the dataloader.""" return self diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 88afaac0..bfca5ecf 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -1,4 +1,4 @@ -"""Pytorch dataloader for the Argoverse 2 Scene Flow task.""" +"""Pytorch dataloader for the scene flow task.""" from __future__ import annotations diff --git a/tutorials/torch_dataloader.py b/tutorials/detection_dataloader.py similarity index 73% rename from tutorials/torch_dataloader.py rename to tutorials/detection_dataloader.py index 0fec34cd..66315cdd 100644 --- a/tutorials/torch_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -4,7 +4,7 @@ from tqdm import tqdm -from av2.torch.dataloaders.sensor import Dataloader +from av2.torch.dataloaders.detection import DetectionDataloader def main() -> None: @@ -15,7 +15,7 @@ def main() -> None: split_name = "val" num_accum_sweeps = 1 - dataloader = Dataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) + dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) for sweep in tqdm(dataloader): print(sweep.lidar.as_tensor()) From 415dda1f44a3c1b9473eb4ec4a143912fc6052c8 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:40:01 -0700 Subject: [PATCH 043/117] r -> rust. --- src/av2/torch/dataloaders/detection.py | 6 +++--- src/av2/torch/dataloaders/scene_flow.py | 6 +++--- src/av2/torch/dataloaders/utils.py | 4 ++-- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/src/av2/torch/dataloaders/detection.py b/src/av2/torch/dataloaders/detection.py index 9ee89553..a3ee40f9 100644 --- a/src/av2/torch/dataloaders/detection.py +++ b/src/av2/torch/dataloaders/detection.py @@ -7,7 +7,7 @@ from torch.utils.data import Dataset -import av2._r as r +import av2._r as rust from av2.utils.typing import PathType from .utils import Sweep @@ -34,12 +34,12 @@ class DetectionDataloader(Dataset[Sweep]): num_accum_sweeps: int = 1 memory_map: bool = False - _backend: r.Dataloader = field(init=False) + _backend: rust.Dataloader = field(init=False) _current_idx: int = 0 def __post_init__(self) -> None: """Initialize Rust backend.""" - self._backend = r.Dataloader( + self._backend = rust.Dataloader( str(self.root_dir), "sensor", self.split_name, diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index bfca5ecf..1fce8596 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -10,7 +10,7 @@ import pandas as pd from torch.utils.data import Dataset -import av2._r as r +import av2._r as rust from av2.utils.typing import PathType from .utils import Sweep @@ -37,12 +37,12 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): num_accum_sweeps: int = 1 memory_mapped: bool = False - _backend: r.Dataloader = field(init=False) + _backend: rust.Dataloader = field(init=False) _current_idx: int = 0 def __post_init__(self) -> None: """Initialize Rust backend.""" - self._backend = r.Dataloader( + self._backend = rust.Dataloader( str(self.root_dir), "sensor", self.split_name, diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 7dd91616..d023f5e6 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -15,7 +15,7 @@ import torch from torch import Tensor -import av2._r as r +import av2._r as rust from av2.geometry.geometry import mat_to_xyz, quat_to_mat from av2.geometry.se3 import SE3 from av2.utils.typing import NDArrayFloat @@ -227,7 +227,7 @@ class Sweep: sweep_uuid: Tuple[str, int] @classmethod - def from_rust(cls, sweep: r.Sweep) -> Sweep: + def from_rust(cls, sweep: rust.Sweep) -> Sweep: annotations = Annotations(dataframe=sweep.annotations.to_pandas()) city_pose = Pose(dataframe=sweep.city_pose.to_pandas()) lidar = Lidar(dataframe=sweep.lidar.to_pandas()) From f7c2f68c24899793ccc01476e444593074d28a7f Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 15:41:00 -0700 Subject: [PATCH 044/117] Minor docstring fixes. --- src/av2/torch/dataloaders/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index d023f5e6..9a71411a 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -1,4 +1,4 @@ -"""Pytorch sensor dataloader utilities.""" +"""Pytorch detection dataloader utilities.""" from __future__ import annotations @@ -115,7 +115,7 @@ def convert(dataframe: pd.DataFrame, src: CuboidMode, target: CuboidMode) -> pd. ) ) vertices = vertices.reshape(-1, len(unit_vertices_obj_xyz_m) * 3) - dataframe = dataframe[:, ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]] + dataframe = dataframe.loc[:, ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]] dataframe[:, columns] = vertices return dataframe else: From 6723578db2847e47ddf3bfe0c5e274571d20e9f6 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 18:41:42 -0700 Subject: [PATCH 045/117] Fix lint. --- src/av2/torch/dataloaders/utils.py | 32 +++++++----------------------- 1 file changed, 7 insertions(+), 25 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 9a71411a..dec68723 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -216,9 +216,10 @@ class Sweep: """Stores the annotations and lidar for one sweep. Args: - annotations: Object containing annotation parameters. - lidar: Object containing lidar parameters. - sweep_uuid: + annotations: Annotations parameterization. + city_pose: Rigid transformation describing the city pose of the ego-vehicle. + lidar: Lidar parameters. + sweep_uuid: Log id and nanosecond timestamp (unique identifier). """ annotations: Optional[Annotations] @@ -228,6 +229,7 @@ class Sweep: @classmethod def from_rust(cls, sweep: rust.Sweep) -> Sweep: + """Build a sweep from the Rust backend.""" annotations = Annotations(dataframe=sweep.annotations.to_pandas()) city_pose = Pose(dataframe=sweep.city_pose.to_pandas()) lidar = Lidar(dataframe=sweep.lidar.to_pandas()) @@ -236,12 +238,13 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: @dataclass(frozen=True) class Pose: - """Stores the annotations and lidar for one sweep.""" + """Pose class for rigid transformations.""" dataframe: pd.DataFrame @cached_property def Rt(self) -> Tuple[Tensor, Tensor]: + """Return a (3,3) rotation matrix and a (3,) translation vector.""" quat_wxyz: NDArrayFloat = self.dataframe[QUAT_WXYZ_FIELDS].to_numpy() translation: NDArrayFloat = self.dataframe[TRANSLATION_FIELDS].to_numpy() @@ -254,27 +257,6 @@ def prevent_fsspec_deadlock() -> None: fsspec.asyn.reset_lock() -def query_pose(poses: pd.DataFrame, timestamp_ns: int) -> SE3: - """Query the SE(3) transformation as the provided timestamp in nanoseconds. - - Args: - poses: DataFrame of quaternion and translation components. - timestamp_ns: Timestamp of interest in nanoseconds. - - Returns: - SE(3) at timestamp_ns. - """ - mask = poses.loc[:, "timestamp_ns"] == timestamp_ns - pose = poses.loc[mask, ["qw", "qx", "qy", "qz", "tx_m", "ty_m", "tz_m"]] - pose_npy: NDArrayFloat = pose.to_numpy().squeeze() - quat = pose_npy[:4] - translation = pose_npy[4:] - return SE3( - rotation=quat_to_mat(quat), - translation=translation, - ) - - def compute_interior_points_mask(xyz_m: Tensor, cuboid_vertices: Tensor) -> Tensor: r"""Compute the interior points within a set of _axis-aligned_ cuboids. From 46315355dcda9009d955e7daa6e498b45428265e Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 18:55:51 -0700 Subject: [PATCH 046/117] Fix lint. --- conda/environment.yml | 1 + pyproject.toml | 1 + src/av2/torch/dataloaders/conversions.py | 49 ------------------------ src/av2/torch/dataloaders/scene_flow.py | 2 +- src/av2/torch/dataloaders/utils.py | 7 ---- 5 files changed, 3 insertions(+), 57 deletions(-) delete mode 100644 src/av2/torch/dataloaders/conversions.py diff --git a/conda/environment.yml b/conda/environment.yml index 9aadd0ab..838f41ee 100644 --- a/conda/environment.yml +++ b/conda/environment.yml @@ -12,6 +12,7 @@ dependencies: - numpy - opencv - pandas + - pandas-stubs - pip - polars - pyarrow diff --git a/pyproject.toml b/pyproject.toml index f10e72c6..8b8ad377 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,6 +22,7 @@ dependencies = [ "numpy", "opencv-python", "pandas", + "pandas-stubs", "polars", "pyarrow", "pyproj", diff --git a/src/av2/torch/dataloaders/conversions.py b/src/av2/torch/dataloaders/conversions.py deleted file mode 100644 index 565c2bde..00000000 --- a/src/av2/torch/dataloaders/conversions.py +++ /dev/null @@ -1,49 +0,0 @@ -"""Pytorch rigid body transformations.""" - -import math - -import torch -from torch import Tensor - - -def quat_to_xyz(quat_wxyz: Tensor, singularity_value: float = math.pi / 2) -> Tensor: - """Convert scalar first quaternion to Tait-Bryan angles. - - Reference: - https://en.wikipedia.org/wiki/Conversion_between_quaternions_and_Euler_angles#Source_code_2 - - Args: - quat_wxyz: (...,4) Scalar first quaternions. - singularity_value: Value that's set at the singularities. - - Returns: - (...,3) The Tait-Bryan angles --- roll, pitch, and yaw. - """ - qw = quat_wxyz[..., 0] - qx = quat_wxyz[..., 1] - qy = quat_wxyz[..., 2] - qz = quat_wxyz[..., 3] - - # roll (x-axis rotation) - sinr_cosp = 2 * (qw * qx + qy * qz) - cosr_cosp = 1 - 2 * (qx * qx + qy * qy) - roll = torch.atan2(sinr_cosp, cosr_cosp) - - # pitch (y-axis rotation) - pitch = 2 * (qw * qy - qz * qx) - is_out_of_range = torch.abs(pitch) >= 1 - pitch[is_out_of_range] = torch.copysign(torch.as_tensor(singularity_value), pitch[is_out_of_range]) - pitch[~is_out_of_range] = torch.asin(pitch[~is_out_of_range]) - - # yaw (z-axis rotation) - siny_cosp = 2 * (qw * qz + qx * qy) - cosy_cosp = 1 - 2 * (qy * qy + qz * qz) - yaw = torch.atan2(siny_cosp, cosy_cosp) - xyz = torch.stack([roll, pitch, yaw], dim=-1) - return xyz - - -def quat_to_yaw(quat_wxyz: Tensor) -> Tensor: - """Scalar-first quaternion to rotation around the gravity aligned axis in radians.""" - xyz: Tensor = quat_to_xyz(quat_wxyz)[:, -1] - return xyz diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 1fce8596..94e24200 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -63,7 +63,7 @@ def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: next_index = index + 1 if next_index < len(self): - candidate_log_id: str = self.file_index.loc[next_index, ["log_id"]].item() + candidate_log_id: str = self.file_index["log_id"][next_index] current_log_id = sweep.sweep_uuid[0] if candidate_log_id == current_log_id: next_sweep = Sweep.from_rust(self._backend.get(next_index)) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index dec68723..43fb7bdb 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -9,7 +9,6 @@ from functools import cached_property from typing import Final, List, Optional, Tuple -import fsspec.asyn import numpy as np import pandas as pd import torch @@ -17,7 +16,6 @@ import av2._r as rust from av2.geometry.geometry import mat_to_xyz, quat_to_mat -from av2.geometry.se3 import SE3 from av2.utils.typing import NDArrayFloat DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( @@ -252,11 +250,6 @@ def Rt(self) -> Tuple[Tensor, Tensor]: return torch.as_tensor(rotation, dtype=torch.float32), torch.as_tensor(translation, dtype=torch.float32) -def prevent_fsspec_deadlock() -> None: - """Reset the fsspec global lock to prevent deadlocking in forked processes.""" - fsspec.asyn.reset_lock() - - def compute_interior_points_mask(xyz_m: Tensor, cuboid_vertices: Tensor) -> Tensor: r"""Compute the interior points within a set of _axis-aligned_ cuboids. From 3be0f60634eaf24ff9192133df5a8452d2600e57 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 18:57:28 -0700 Subject: [PATCH 047/117] Remove test data. --- .../annotations.feather | Bin 642618 -> 0 bytes .../city_SE3_egovehicle.feather | Bin 161634 -> 0 bytes ...5b0-a2fa-b4cea13a6d76___img_Sim2_city.json | 1 - ...ea13a6d76_ground_height_surface____PIT.npy | Bin 1135548 -> 0 bytes ...0-a2fa-b4cea13a6d76____PIT_city_57819.json | 1 - .../sensors/lidar/315973157959879000.feather | Bin 1048066 -> 0 bytes tests/torch/dataloaders/test_sensor.py | 15 --------------- 7 files changed, 17 deletions(-) delete mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/annotations.feather delete mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/city_SE3_egovehicle.feather delete mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/adcf7d18-0510-35b0-a2fa-b4cea13a6d76___img_Sim2_city.json delete mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/adcf7d18-0510-35b0-a2fa-b4cea13a6d76_ground_height_surface____PIT.npy delete mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/log_map_archive_adcf7d18-0510-35b0-a2fa-b4cea13a6d76____PIT_city_57819.json delete mode 100644 tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/sensors/lidar/315973157959879000.feather delete mode 100644 tests/torch/dataloaders/test_sensor.py diff --git a/tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/annotations.feather b/tests/torch/dataloaders/test_data/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/annotations.feather deleted file mode 100644 index 4ed097ba2a5a333097f7ade24632fb14ce5833c2..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 642618 zcmdqqahPlQA;A6YZd7QrK@g-B>teBLRq3MG+m;5SlWGuz&9>P#OS+qG(>85Wf*@t8 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a/tests/torch/dataloaders/test_sensor.py +++ /dev/null @@ -1,15 +0,0 @@ -"""Pytorch dataloader tests for the AV2 sensor dataset.""" - -from pathlib import Path -from typing import Final - -TEST_DATA_DIR: Final[Path] = Path(__file__).parent.resolve() / "test_data" - - -def test_av2_sensor_dataloader() -> None: - """Test the av2 sensor dataloader.""" - pass - - -if __name__ == "__main__": - test_av2_sensor_dataloader() From 0be4d6dfd4c2328824fd6ee7859d7f292d5af0e1 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 22:25:12 -0700 Subject: [PATCH 048/117] Remove pandas stubs. --- conda/environment.yml | 1 - pyproject.toml | 1 - src/av2/torch/dataloaders/utils.py | 2 +- 3 files changed, 1 insertion(+), 3 deletions(-) diff --git a/conda/environment.yml b/conda/environment.yml index 838f41ee..9aadd0ab 100644 --- a/conda/environment.yml +++ b/conda/environment.yml @@ -12,7 +12,6 @@ dependencies: - numpy - opencv - pandas - - pandas-stubs - pip - polars - pyarrow diff --git a/pyproject.toml b/pyproject.toml index 8b8ad377..f10e72c6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,7 +22,6 @@ dependencies = [ "numpy", "opencv-python", "pandas", - "pandas-stubs", "polars", "pyarrow", "pyproj", diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 43fb7bdb..adf79599 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -1,4 +1,4 @@ -"""Pytorch detection dataloader utilities.""" +"""Pytorch dataloader utilities.""" from __future__ import annotations From fcbd2f10776c032716747ab2229e5f4dad9a3fef Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 23:02:26 -0700 Subject: [PATCH 049/117] Add docstrings. --- rust/src/lib.rs | 52 +++++++++++++++++++++++++++++++++++++------------ 1 file changed, 40 insertions(+), 12 deletions(-) diff --git a/rust/src/lib.rs b/rust/src/lib.rs index 393da95b..c2063e3b 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -32,6 +32,7 @@ use pyo3::types::PyBytes; use crate::ops::voxelize; /// Annotation dataframe columns. +/// Found in `annotations.feather`. pub const ANNOTATION_COLUMNS: [&str; 13] = [ "tx_m", "ty_m", @@ -49,6 +50,7 @@ pub const ANNOTATION_COLUMNS: [&str; 13] = [ ]; /// Pose dataframe columns. +/// Found in `city_SE3_egovehicle`. pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; /// Data associated with a single lidar sweep. @@ -68,8 +70,10 @@ pub struct Sweep { pub sweep_uuid: (String, u64), } +/// Encapsulates sensor data associated with a single sweep. #[pymethods] impl Sweep { + /// Initialize a sweep object. #[new] pub fn new( annotations: PyDataFrame, @@ -86,29 +90,39 @@ impl Sweep { } } +/// Sensor dataloader for `av2`. #[derive(Serialize, Deserialize)] #[pyclass(module = "av2._r")] pub struct Dataloader { + /// Root dataset directory. #[pyo3(get, set)] pub root_dir: PathBuf, + /// Dataset name (e.g., `av2`). #[pyo3(get, set)] pub dataset_name: String, + /// Root dataset type (e.g., `sensor`). #[pyo3(get, set)] pub dataset_type: String, + /// Root dataset split name (e.g., `train`). #[pyo3(get, set)] pub split_name: String, + /// Number of accumulated lidar sweeps. #[pyo3(get, set)] - pub num_accum_sweeps: usize, + pub num_accumulated_sweeps: usize, + /// Dataframe consisting of `log_id`, `timestamp_ns`, and `city_name`. #[pyo3(get, set)] pub file_index: PyDataFrame, + /// Current index of the dataloader. #[pyo3(get, set)] - pub current_idx: usize, + pub current_index: usize, + /// Boolean flag to enable memory-mapped dataframe loading. #[pyo3(get, set)] pub memory_mapped: bool, } #[pymethods] impl Dataloader { + /// Initialize the dataloader and build the file index. #[new] pub fn new( root_dir: &str, @@ -126,13 +140,14 @@ impl Dataloader { dataset_name: dataset_name.to_string(), dataset_type: dataset_type.to_string(), split_name: split_name.to_string(), - num_accum_sweeps, + num_accumulated_sweeps: num_accum_sweeps, file_index: PyDataFrame(file_index), - current_idx, + current_index: current_idx, memory_mapped, } } + /// Get the dataset split directory. pub fn split_dir(&self) -> PathBuf { self.root_dir .join(&self.dataset_name) @@ -140,10 +155,12 @@ impl Dataloader { .join(&self.split_name) } + /// Get the log directory corresponding to `log_id`. pub fn log_dir(&self, log_id: &str) -> PathBuf { self.split_dir().join(log_id) } + /// Get the lidar path corresponding to the `log_id` and `timestamp_ns`. pub fn lidar_path(&self, log_id: &str, timestamp_ns: u64) -> PathBuf { let file_name = format!("{timestamp_ns}.feather"); let lidar_path = [ @@ -157,36 +174,40 @@ impl Dataloader { lidar_path } + /// Get the annotations path correcponding to the `log_id`. pub fn annotations_path(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("annotations.feather") } + /// Get the city pose path correcponding to the `log_id`. pub fn city_pose_path(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("city_SE3_egovehicle.feather") } + /// Get the map directory correcponding to the `log_id`. pub fn map_dir(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("map") } - pub fn get(&self, idx: usize) -> Sweep { + /// Get the sweep at `index`. + pub fn get(&self, index: usize) -> Sweep { let log_id = self.file_index.0["log_id"] .utf8() .unwrap() - .get(idx) + .get(index) .unwrap(); let timestamp_ns = self.file_index.0["timestamp_ns"] .u64() .unwrap() - .get(idx) + .get(index) .unwrap(); let lidar = read_lidar( self.log_dir(log_id), &self.file_index.0, log_id, timestamp_ns, - idx, - self.num_accum_sweeps, + index, + self.num_accumulated_sweeps, self.memory_mapped, ) .collect() @@ -235,20 +256,25 @@ impl Dataloader { slf.file_index.0.shape().0 } + /// Used for python pickling. pub fn __setstate__(&mut self, state: &PyBytes) -> PyResult<()> { *self = deserialize(state.as_bytes()).unwrap(); Ok(()) } + + /// Used for python pickling. pub fn __getstate__<'py>(&self, py: Python<'py>) -> PyResult<&'py PyBytes> { Ok(PyBytes::new(py, &serialize(&self).unwrap())) } + + /// Used for python pickling. pub fn __getnewargs__(&self) -> PyResult<(PathBuf, String, String, String, usize)> { Ok(( self.root_dir.clone(), self.dataset_type.clone(), self.split_name.clone(), self.dataset_name.clone(), - self.num_accum_sweeps, + self.num_accumulated_sweeps, )) } } @@ -257,14 +283,15 @@ impl Iterator for Dataloader { type Item = Sweep; fn next(&mut self) -> Option { - let idx = self.current_idx; + let idx = self.current_index; let sweep_data = self.get(idx); - self.current_idx += 1; + self.current_index += 1; Some(sweep_data) } } +/// Build the dataset file index. pub fn build_file_index( root_dir: &Path, dataset_name: &str, @@ -319,6 +346,7 @@ pub fn build_file_index( .unwrap() } +/// Python bindings for `voxelize`. #[pyfunction] #[pyo3(name = "voxelize")] fn py_voxelize<'py>( From 07140a09b945a5fc92112b1100d7c5ae724369b4 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 23:19:16 -0700 Subject: [PATCH 050/117] Add docstrings. --- rust/src/io.rs | 47 ++++++++++++++++++++++++----------------------- rust/src/lib.rs | 13 +++++++------ rust/src/ops.rs | 2 ++ rust/src/path.rs | 6 ++++-- rust/src/se3.rs | 11 ++++++++++- rust/src/so3.rs | 1 + 6 files changed, 48 insertions(+), 32 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 5eeb1c69..ba0f1053 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -29,7 +29,8 @@ use std::path::PathBuf; use crate::se3::SE3; use crate::so3::quat_to_mat; -pub fn read_frame(path: &PathBuf, memory_mapped: bool) -> DataFrame { +/// Read a feather file and load into a `polars` dataframe. +pub fn read_feather(path: &PathBuf, memory_mapped: bool) -> DataFrame { let file = File::open(path).expect("File not found"); polars::io::ipc::IpcReader::new(file) .memory_mapped(memory_mapped) @@ -37,22 +38,25 @@ pub fn read_frame(path: &PathBuf, memory_mapped: bool) -> DataFrame { .unwrap_or_else(|_| panic!("This IPC file is malformed: {:?}.", path)) } -pub fn read_lidar( +/// Read and accumulate lidar sweeps. +/// Accumulation will only occur if `num_accumulated_sweeps` > 1. +/// Sweeps are motion-compensated to the most recent sweep (i.e., at `timestamp_ns`). +pub fn read_accumulate_lidar( log_dir: PathBuf, file_index: &DataFrame, log_id: &str, timestamp_ns: u64, idx: usize, - num_accum_sweeps: usize, + num_accumulated_sweeps: usize, memory_mapped: bool, ) -> LazyFrame { - let start_idx = i64::max(idx as i64 - num_accum_sweeps as i64 + 1, 0) as usize; + let start_idx = i64::max(idx as i64 - num_accumulated_sweeps as i64 + 1, 0) as usize; let log_ids = file_index["log_id"].utf8().unwrap(); let timestamps = file_index["timestamp_ns"].u64().unwrap(); let poses_path = log_dir.join("city_SE3_egovehicle.feather"); - let poses = read_frame(&poses_path, true); + let poses = read_feather(&poses_path, true); - let pose_ref = frame_to_ndarray_with_filter( + let pose_ref = dataframe_to_nd_and_filter( &poses, cols(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]), col("timestamp_ns").eq(timestamp_ns), @@ -78,16 +82,17 @@ pub fn read_lidar( }) .map(|i| { let timestamp_ns_i = timestamps.get(i).unwrap(); - let lidar_path = get_lidar_path(log_dir.clone(), timestamp_ns_i); - let mut lidar = read_frame(&lidar_path, memory_mapped).lazy(); + let lidar_path = build_lidar_file_path(log_dir.clone(), timestamp_ns_i); + let mut lidar = read_feather(&lidar_path, memory_mapped).lazy(); - let xyz = frame_to_ndarray(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); + let xyz = + convert_dataframe_to_nd(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); let timedeltas = Series::new( "timedelta_ns", vec![(timestamp_ns - timestamp_ns_i) as f32 * 1e-9; xyz.shape()[0]], ); if timestamp_ns_i != timestamp_ns { - let pose_i = frame_to_ndarray_with_filter( + let pose_i = dataframe_to_nd_and_filter( &poses, cols(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]), col("timestamp_ns").eq(timestamp_ns_i), @@ -138,19 +143,21 @@ pub fn read_lidar( concat(lidar_list, true, true).unwrap() } -pub fn read_filter_timestamp( +/// Read a dataframe, but filter for the specified timestamp. +pub fn read_timestamped_feather( path: &PathBuf, columns: &Vec<&str>, timestamp_ns: &u64, memory_mapped: bool, ) -> LazyFrame { - read_frame(path, memory_mapped) + read_feather(path, memory_mapped) .lazy() .filter(col("timestamp_ns").eq(*timestamp_ns)) .select(&[cols(columns)]) } -pub fn get_lidar_path(log_dir: PathBuf, timestamp_ns: u64) -> PathBuf { +/// Build the lidar file path. +pub fn build_lidar_file_path(log_dir: PathBuf, timestamp_ns: u64) -> PathBuf { let file_name = format!("{timestamp_ns}.feather"); let lidar_path = [ log_dir, @@ -163,15 +170,8 @@ pub fn get_lidar_path(log_dir: PathBuf, timestamp_ns: u64) -> PathBuf { lidar_path } -pub fn get_split_dir(root_dir: PathBuf, dataset_type: &str, split_name: &str) -> PathBuf { - root_dir.join(dataset_type).join(split_name) -} - -pub fn get_log_dir(split_dir: PathBuf, log_id: &str) -> PathBuf { - split_dir.join(log_id) -} - -pub fn frame_to_ndarray(frame: &DataFrame, exprs: Expr) -> Array2 { +/// Convert a dataframe to `ndarray`. +pub fn convert_dataframe_to_nd(frame: &DataFrame, exprs: Expr) -> Array2 { frame .clone() .lazy() @@ -184,7 +184,8 @@ pub fn frame_to_ndarray(frame: &DataFrame, exprs: Expr) -> Array2 { .to_owned() } -pub fn frame_to_ndarray_with_filter( +/// Convert a dataframe to `ndarray` and filter. +pub fn dataframe_to_nd_and_filter( frame: &DataFrame, select_exprs: Expr, filter_exprs: Expr, diff --git a/rust/src/lib.rs b/rust/src/lib.rs index c2063e3b..202447f1 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -11,11 +11,11 @@ pub mod path; pub mod se3; pub mod so3; -use io::{read_filter_timestamp, read_lidar}; +use io::{read_accumulate_lidar, read_timestamped_feather}; use itertools::{multiunzip, Itertools}; use ndarray::Dim; use numpy::{IntoPyArray, PyArray}; -use path::{file_stem, walk_dir}; +use path::{extract_file_stem, walk_dir}; use pyo3::prelude::*; use pyo3_polars::PyDataFrame; use rayon::slice::ParallelSliceMut; @@ -201,7 +201,7 @@ impl Dataloader { .unwrap() .get(index) .unwrap(); - let lidar = read_lidar( + let lidar = read_accumulate_lidar( self.log_dir(log_id), &self.file_index.0, log_id, @@ -214,7 +214,7 @@ impl Dataloader { .unwrap(); let annotations_path = self.annotations_path(log_id); - let annotations = read_filter_timestamp( + let annotations = read_timestamped_feather( &annotations_path, &ANNOTATION_COLUMNS.to_vec(), ×tamp_ns, @@ -225,7 +225,7 @@ impl Dataloader { .unwrap(); let city_pose_path = self.city_pose_path(log_id); - let city_pose = read_filter_timestamp( + let city_pose = read_timestamped_feather( &city_pose_path, &POSE_COLUMNS.to_vec(), ×tamp_ns, @@ -305,7 +305,7 @@ pub fn build_file_index( let (log_ids, timestamp_nss, city_names): (Vec<_>, Vec<_>, Vec<_>) = multiunzip(entry_set.into_iter().map(|log_path| { - let log_id = file_stem(&log_path).unwrap(); + let log_id = extract_file_stem(&log_path).unwrap(); let lidar_dir = log_path.join("sensors/lidar"); let x = log_path.join("map/log_map_archive_*.json"); let city_name = glob(x.to_str().unwrap()) @@ -349,6 +349,7 @@ pub fn build_file_index( /// Python bindings for `voxelize`. #[pyfunction] #[pyo3(name = "voxelize")] +#[allow(clippy::type_complexity)] fn py_voxelize<'py>( py: Python<'py>, indices: PyReadonlyArray2, diff --git a/rust/src/ops.rs b/rust/src/ops.rs index 77282bff..dd03a484 100644 --- a/rust/src/ops.rs +++ b/rust/src/ops.rs @@ -9,6 +9,7 @@ use std::{ ops::{AddAssign, DivAssign}, }; +/// Convert unraveled coordinates (i.e., multi-dimensional indices) to a linear index. pub fn ravel_multi_index(unraveled_coords: &ArrayView2, size: Vec) -> Array2 { let shape_arr = Array1::::from_vec( size.into_iter() @@ -30,6 +31,7 @@ pub fn ravel_multi_index(unraveled_coords: &ArrayView2, size: Vec) .insert_axis(Axis(1)) } +/// Cluster a group of features into a set of voxels based on their indices. pub fn voxelize( indices: &ArrayView2, features: &ArrayView2, diff --git a/rust/src/path.rs b/rust/src/path.rs index cfc4312c..0d31a0f6 100644 --- a/rust/src/path.rs +++ b/rust/src/path.rs @@ -4,9 +4,10 @@ use anyhow::{Context, Result}; use std::fs; -use std::path::PathBuf; use std::path::Path; +use std::path::PathBuf; +/// Walk a directory and filter invalid paths. pub fn walk_dir(dir: &PathBuf) -> Result> { let files: Vec<_> = fs::read_dir(dir)? .filter_map(|x| x.ok()) @@ -15,7 +16,8 @@ pub fn walk_dir(dir: &PathBuf) -> Result> { Ok(files) } -pub fn file_stem(dir: &Path) -> Result { +/// Extract the file stem from a path. +pub fn extract_file_stem(dir: &Path) -> Result { let file_stem = dir .file_stem() .context("Cannot parse file stem.")? diff --git a/rust/src/se3.rs b/rust/src/se3.rs index b148b0c3..0bcea089 100644 --- a/rust/src/se3.rs +++ b/rust/src/se3.rs @@ -1,15 +1,20 @@ //! # SE3 //! -//! Special Euclidean Group in 3 Dimensions. +//! Special Euclidean Group 3. use ndarray::{s, Array1, Array2, ArrayView2}; +/// Special Euclidean Group 3 (SE(3)). +/// Rigid transformation parameterized by a rotation and translation in $R^3$. pub struct SE3 { + /// (3,3) Orthonormal rotation matrix. pub rotation: Array2, + /// (3,) Translation vector. pub translation: Array1, } impl SE3 { + /// Get the (4,4) homogeneous transformation matrix associated with the rigid transformation. pub fn transform_matrix(&self) -> Array2 { let mut transform_matrix = Array2::eye(4); transform_matrix @@ -20,10 +25,13 @@ impl SE3 { .assign(&self.translation); transform_matrix } + + /// Transform the point cloud from its reference from to the SE(3) destination. pub fn transform_from(&self, point_cloud: &ArrayView2) -> Array2 { point_cloud.dot(&self.rotation.t()) + &self.translation } + /// Invert the SE(3) transformation. pub fn inverse(&self) -> SE3 { let rotation = self.rotation.t().as_standard_layout().to_owned(); let translation = rotation.dot(&(-&self.translation)); @@ -33,6 +41,7 @@ impl SE3 { } } + /// Compose (right multiply) an SE(3) with another SE(3). pub fn compose(&self, right_se3: &SE3) -> SE3 { let chained_transform_matrix = self.transform_matrix().dot(&right_se3.transform_matrix()); SE3 { diff --git a/rust/src/so3.rs b/rust/src/so3.rs index bb23509f..ee9e72d2 100644 --- a/rust/src/so3.rs +++ b/rust/src/so3.rs @@ -4,6 +4,7 @@ use ndarray::{Array2, ArrayView1}; +/// Convert a quaternion in scalar-first format to a rotation matrix. pub fn quat_to_mat(quat_wxyz: &ArrayView1) -> Array2 { let w = quat_wxyz[0]; let x = quat_wxyz[1]; From de6ba7ab49ae6094fb37ab0a4efeb730e09e9742 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Mon, 13 Mar 2023 23:28:51 -0700 Subject: [PATCH 051/117] Reorganize files. --- rust/src/constants.rs | 25 ++++ rust/src/dataloader.rs | 314 ++++++++++++++++++++++++++++++++++++++ rust/src/lib.rs | 332 +---------------------------------------- 3 files changed, 343 insertions(+), 328 deletions(-) create mode 100644 rust/src/constants.rs create mode 100644 rust/src/dataloader.rs diff --git a/rust/src/constants.rs b/rust/src/constants.rs new file mode 100644 index 00000000..d9302f48 --- /dev/null +++ b/rust/src/constants.rs @@ -0,0 +1,25 @@ +//! # constants +//! +//! Common constants used throughout the library. + +/// Annotation dataframe columns. +/// Found in `annotations.feather`. +pub const ANNOTATION_COLUMNS: [&str; 13] = [ + "tx_m", + "ty_m", + "tz_m", + "length_m", + "width_m", + "height_m", + "qw", + "qx", + "qy", + "qz", + "num_interior_pts", + "category", + "track_uuid", +]; + +/// Pose dataframe columns. +/// Found in `city_SE3_egovehicle`. +pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs new file mode 100644 index 00000000..0e8b3b30 --- /dev/null +++ b/rust/src/dataloader.rs @@ -0,0 +1,314 @@ +//! # dataloaders +//! +//! Dataloader for loading the sensor dataset. + +use constants::{ANNOTATION_COLUMNS, POSE_COLUMNS}; +use io::{read_accumulate_lidar, read_timestamped_feather}; +use itertools::{multiunzip, Itertools}; +use path::{extract_file_stem, walk_dir}; +use pyo3::prelude::*; +use pyo3_polars::PyDataFrame; +use rayon::slice::ParallelSliceMut; +use serde::{Deserialize, Serialize}; +use std::path::{Path, PathBuf}; + +use anyhow::Result; +use bincode::{deserialize, serialize}; +use glob::glob; +use polars::prelude::*; +use pyo3::types::PyBytes; + +use crate::{constants, io, path}; + +/// Data associated with a single lidar sweep. +#[pyclass] +pub struct Sweep { + /// Ground truth annotations. + #[pyo3(get, set)] + pub annotations: PyDataFrame, + /// Ego-vehicle city pose. + #[pyo3(get, set)] + pub city_pose: PyDataFrame, + /// Point cloud associated with the sweep. + #[pyo3(get, set)] + pub lidar: PyDataFrame, + /// Log id and nanosecond timestamp (unique identifier). + #[pyo3(get, set)] + pub sweep_uuid: (String, u64), +} + +/// Encapsulates sensor data associated with a single sweep. +#[pymethods] +impl Sweep { + /// Initialize a sweep object. + #[new] + pub fn new( + annotations: PyDataFrame, + city_pose: PyDataFrame, + lidar: PyDataFrame, + sweep_uuid: (String, u64), + ) -> Sweep { + Sweep { + annotations, + city_pose, + lidar, + sweep_uuid, + } + } +} + +/// Sensor dataloader for `av2`. +#[derive(Serialize, Deserialize)] +#[pyclass(module = "av2._r")] +pub struct Dataloader { + /// Root dataset directory. + #[pyo3(get, set)] + pub root_dir: PathBuf, + /// Dataset name (e.g., `av2`). + #[pyo3(get, set)] + pub dataset_name: String, + /// Root dataset type (e.g., `sensor`). + #[pyo3(get, set)] + pub dataset_type: String, + /// Root dataset split name (e.g., `train`). + #[pyo3(get, set)] + pub split_name: String, + /// Number of accumulated lidar sweeps. + #[pyo3(get, set)] + pub num_accumulated_sweeps: usize, + /// Dataframe consisting of `log_id`, `timestamp_ns`, and `city_name`. + #[pyo3(get, set)] + pub file_index: PyDataFrame, + /// Current index of the dataloader. + #[pyo3(get, set)] + pub current_index: usize, + /// Boolean flag to enable memory-mapped dataframe loading. + #[pyo3(get, set)] + pub memory_mapped: bool, +} + +#[pymethods] +impl Dataloader { + /// Initialize the dataloader and build the file index. + #[new] + pub fn new( + root_dir: &str, + dataset_type: &str, + split_name: &str, + dataset_name: &str, + num_accum_sweeps: usize, + memory_mapped: bool, + ) -> Dataloader { + let root_dir = Path::new(root_dir); + let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); + let current_idx = 0; + Dataloader { + root_dir: root_dir.to_path_buf(), + dataset_name: dataset_name.to_string(), + dataset_type: dataset_type.to_string(), + split_name: split_name.to_string(), + num_accumulated_sweeps: num_accum_sweeps, + file_index: PyDataFrame(file_index), + current_index: current_idx, + memory_mapped, + } + } + + /// Get the dataset split directory. + pub fn split_dir(&self) -> PathBuf { + self.root_dir + .join(&self.dataset_name) + .join(&self.dataset_type) + .join(&self.split_name) + } + + /// Get the log directory corresponding to `log_id`. + pub fn log_dir(&self, log_id: &str) -> PathBuf { + self.split_dir().join(log_id) + } + + /// Get the lidar path corresponding to the `log_id` and `timestamp_ns`. + pub fn lidar_path(&self, log_id: &str, timestamp_ns: u64) -> PathBuf { + let file_name = format!("{timestamp_ns}.feather"); + let lidar_path = [ + self.log_dir(log_id), + "sensors".to_string().into(), + "lidar".to_string().into(), + file_name.into(), + ] + .iter() + .collect(); + lidar_path + } + + /// Get the annotations path correcponding to the `log_id`. + pub fn annotations_path(&self, log_id: &str) -> PathBuf { + self.log_dir(log_id).join("annotations.feather") + } + + /// Get the city pose path correcponding to the `log_id`. + pub fn city_pose_path(&self, log_id: &str) -> PathBuf { + self.log_dir(log_id).join("city_SE3_egovehicle.feather") + } + + /// Get the map directory correcponding to the `log_id`. + pub fn map_dir(&self, log_id: &str) -> PathBuf { + self.log_dir(log_id).join("map") + } + + /// Get the sweep at `index`. + pub fn get(&self, index: usize) -> Sweep { + let log_id = self.file_index.0["log_id"] + .utf8() + .unwrap() + .get(index) + .unwrap(); + let timestamp_ns = self.file_index.0["timestamp_ns"] + .u64() + .unwrap() + .get(index) + .unwrap(); + let lidar = read_accumulate_lidar( + self.log_dir(log_id), + &self.file_index.0, + log_id, + timestamp_ns, + index, + self.num_accumulated_sweeps, + self.memory_mapped, + ) + .collect() + .unwrap(); + + let annotations_path = self.annotations_path(log_id); + let annotations = read_timestamped_feather( + &annotations_path, + &ANNOTATION_COLUMNS.to_vec(), + ×tamp_ns, + self.memory_mapped, + ) + .filter(col("num_interior_pts").gt_eq(1.)) + .collect() + .unwrap(); + + let city_pose_path = self.city_pose_path(log_id); + let city_pose = read_timestamped_feather( + &city_pose_path, + &POSE_COLUMNS.to_vec(), + ×tamp_ns, + self.memory_mapped, + ) + .collect() + .unwrap(); + + let sweep_uuid = (log_id.to_string(), timestamp_ns); + + Sweep { + annotations: PyDataFrame(annotations), + city_pose: PyDataFrame(city_pose), + lidar: PyDataFrame(lidar), + sweep_uuid, + } + } + + fn __iter__(slf: PyRef<'_, Self>) -> PyRef<'_, Self> { + slf + } + + fn __next__(mut slf: PyRefMut<'_, Self>) -> Option { + slf.next() + } + + fn __len__(slf: PyRef<'_, Self>) -> usize { + slf.file_index.0.shape().0 + } + + /// Used for python pickling. + pub fn __setstate__(&mut self, state: &PyBytes) -> PyResult<()> { + *self = deserialize(state.as_bytes()).unwrap(); + Ok(()) + } + + /// Used for python pickling. + pub fn __getstate__<'py>(&self, py: Python<'py>) -> PyResult<&'py PyBytes> { + Ok(PyBytes::new(py, &serialize(&self).unwrap())) + } + + /// Used for python pickling. + pub fn __getnewargs__(&self) -> PyResult<(PathBuf, String, String, String, usize)> { + Ok(( + self.root_dir.clone(), + self.dataset_type.clone(), + self.split_name.clone(), + self.dataset_name.clone(), + self.num_accumulated_sweeps, + )) + } +} + +impl Iterator for Dataloader { + type Item = Sweep; + + fn next(&mut self) -> Option { + let idx = self.current_index; + let sweep_data = self.get(idx); + self.current_index += 1; + + Some(sweep_data) + } +} + +/// Build the dataset file index. +pub fn build_file_index( + root_dir: &Path, + dataset_name: &str, + dataset_type: &str, + split_name: &str, +) -> DataFrame { + let split_dir = root_dir.join(format!("{dataset_name}/{dataset_type}/{split_name}")); + let mut entry_set: Vec<_> = walk_dir(&split_dir) + .unwrap_or_else(|_| panic!("Cannot walk the following directory: {split_dir:?}")); + entry_set.par_sort(); + + let (log_ids, timestamp_nss, city_names): (Vec<_>, Vec<_>, Vec<_>) = + multiunzip(entry_set.into_iter().map(|log_path| { + let log_id = extract_file_stem(&log_path).unwrap(); + let lidar_dir = log_path.join("sensors/lidar"); + let x = log_path.join("map/log_map_archive_*.json"); + let city_name = glob(x.to_str().unwrap()) + .unwrap() + .find_map(Result::ok) + .unwrap_or("log_map_archive___DEFAULT_city_00000.json".into()) + .to_str() + .unwrap() + .split('_') + .collect::>()[7] + .to_string(); + + let mut lidar_entry_set: Vec<_> = glob(lidar_dir.join("*.feather").to_str().unwrap()) + .unwrap() + .filter_map(|x| x.ok()) + .map(|x| x.as_path().to_owned()) + .collect(); + lidar_entry_set.par_sort(); + + let num_entries = lidar_entry_set.len(); + ( + vec![log_id; num_entries], + lidar_entry_set + .into_iter() + .map(|lidar_path| { + let lidar_path = lidar_path.file_stem().unwrap().to_str(); + lidar_path.unwrap().parse::().unwrap() + }) + .collect::>(), + vec![city_name; num_entries], + ) + })); + df!( + "log_id" => log_ids.into_iter().flatten().collect_vec(), + "timestamp_ns" => timestamp_nss.into_iter().flatten().collect_vec(), + "city_name" => city_names.into_iter().flatten().collect_vec(), + ) + .unwrap() +} diff --git a/rust/src/lib.rs b/rust/src/lib.rs index 202447f1..aea21484 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -1,351 +1,27 @@ //! # av2 //! -//! Argoverse rust library. +//! Argoverse 2 Rust library. #![warn(missing_docs)] #![warn(missing_doc_code_examples)] +pub mod constants; +pub mod dataloader; pub mod io; pub mod ops; pub mod path; pub mod se3; pub mod so3; -use io::{read_accumulate_lidar, read_timestamped_feather}; -use itertools::{multiunzip, Itertools}; +use dataloader::{Dataloader, Sweep}; use ndarray::Dim; use numpy::{IntoPyArray, PyArray}; -use path::{extract_file_stem, walk_dir}; use pyo3::prelude::*; -use pyo3_polars::PyDataFrame; -use rayon::slice::ParallelSliceMut; -use serde::{Deserialize, Serialize}; -use std::path::{Path, PathBuf}; -use anyhow::Result; -use bincode::{deserialize, serialize}; -use glob::glob; use numpy::PyReadonlyArray2; -use polars::prelude::*; -use pyo3::types::PyBytes; use crate::ops::voxelize; -/// Annotation dataframe columns. -/// Found in `annotations.feather`. -pub const ANNOTATION_COLUMNS: [&str; 13] = [ - "tx_m", - "ty_m", - "tz_m", - "length_m", - "width_m", - "height_m", - "qw", - "qx", - "qy", - "qz", - "num_interior_pts", - "category", - "track_uuid", -]; - -/// Pose dataframe columns. -/// Found in `city_SE3_egovehicle`. -pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; - -/// Data associated with a single lidar sweep. -#[pyclass] -pub struct Sweep { - /// Ground truth annotations. - #[pyo3(get, set)] - pub annotations: PyDataFrame, - /// Ego-vehicle city pose. - #[pyo3(get, set)] - pub city_pose: PyDataFrame, - /// Point cloud associated with the sweep. - #[pyo3(get, set)] - pub lidar: PyDataFrame, - /// Log id and nanosecond timestamp (unique identifier). - #[pyo3(get, set)] - pub sweep_uuid: (String, u64), -} - -/// Encapsulates sensor data associated with a single sweep. -#[pymethods] -impl Sweep { - /// Initialize a sweep object. - #[new] - pub fn new( - annotations: PyDataFrame, - city_pose: PyDataFrame, - lidar: PyDataFrame, - sweep_uuid: (String, u64), - ) -> Sweep { - Sweep { - annotations, - city_pose, - lidar, - sweep_uuid, - } - } -} - -/// Sensor dataloader for `av2`. -#[derive(Serialize, Deserialize)] -#[pyclass(module = "av2._r")] -pub struct Dataloader { - /// Root dataset directory. - #[pyo3(get, set)] - pub root_dir: PathBuf, - /// Dataset name (e.g., `av2`). - #[pyo3(get, set)] - pub dataset_name: String, - /// Root dataset type (e.g., `sensor`). - #[pyo3(get, set)] - pub dataset_type: String, - /// Root dataset split name (e.g., `train`). - #[pyo3(get, set)] - pub split_name: String, - /// Number of accumulated lidar sweeps. - #[pyo3(get, set)] - pub num_accumulated_sweeps: usize, - /// Dataframe consisting of `log_id`, `timestamp_ns`, and `city_name`. - #[pyo3(get, set)] - pub file_index: PyDataFrame, - /// Current index of the dataloader. - #[pyo3(get, set)] - pub current_index: usize, - /// Boolean flag to enable memory-mapped dataframe loading. - #[pyo3(get, set)] - pub memory_mapped: bool, -} - -#[pymethods] -impl Dataloader { - /// Initialize the dataloader and build the file index. - #[new] - pub fn new( - root_dir: &str, - dataset_type: &str, - split_name: &str, - dataset_name: &str, - num_accum_sweeps: usize, - memory_mapped: bool, - ) -> Dataloader { - let root_dir = Path::new(root_dir); - let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); - let current_idx = 0; - Dataloader { - root_dir: root_dir.to_path_buf(), - dataset_name: dataset_name.to_string(), - dataset_type: dataset_type.to_string(), - split_name: split_name.to_string(), - num_accumulated_sweeps: num_accum_sweeps, - file_index: PyDataFrame(file_index), - current_index: current_idx, - memory_mapped, - } - } - - /// Get the dataset split directory. - pub fn split_dir(&self) -> PathBuf { - self.root_dir - .join(&self.dataset_name) - .join(&self.dataset_type) - .join(&self.split_name) - } - - /// Get the log directory corresponding to `log_id`. - pub fn log_dir(&self, log_id: &str) -> PathBuf { - self.split_dir().join(log_id) - } - - /// Get the lidar path corresponding to the `log_id` and `timestamp_ns`. - pub fn lidar_path(&self, log_id: &str, timestamp_ns: u64) -> PathBuf { - let file_name = format!("{timestamp_ns}.feather"); - let lidar_path = [ - self.log_dir(log_id), - "sensors".to_string().into(), - "lidar".to_string().into(), - file_name.into(), - ] - .iter() - .collect(); - lidar_path - } - - /// Get the annotations path correcponding to the `log_id`. - pub fn annotations_path(&self, log_id: &str) -> PathBuf { - self.log_dir(log_id).join("annotations.feather") - } - - /// Get the city pose path correcponding to the `log_id`. - pub fn city_pose_path(&self, log_id: &str) -> PathBuf { - self.log_dir(log_id).join("city_SE3_egovehicle.feather") - } - - /// Get the map directory correcponding to the `log_id`. - pub fn map_dir(&self, log_id: &str) -> PathBuf { - self.log_dir(log_id).join("map") - } - - /// Get the sweep at `index`. - pub fn get(&self, index: usize) -> Sweep { - let log_id = self.file_index.0["log_id"] - .utf8() - .unwrap() - .get(index) - .unwrap(); - let timestamp_ns = self.file_index.0["timestamp_ns"] - .u64() - .unwrap() - .get(index) - .unwrap(); - let lidar = read_accumulate_lidar( - self.log_dir(log_id), - &self.file_index.0, - log_id, - timestamp_ns, - index, - self.num_accumulated_sweeps, - self.memory_mapped, - ) - .collect() - .unwrap(); - - let annotations_path = self.annotations_path(log_id); - let annotations = read_timestamped_feather( - &annotations_path, - &ANNOTATION_COLUMNS.to_vec(), - ×tamp_ns, - self.memory_mapped, - ) - .filter(col("num_interior_pts").gt_eq(1.)) - .collect() - .unwrap(); - - let city_pose_path = self.city_pose_path(log_id); - let city_pose = read_timestamped_feather( - &city_pose_path, - &POSE_COLUMNS.to_vec(), - ×tamp_ns, - self.memory_mapped, - ) - .collect() - .unwrap(); - - let sweep_uuid = (log_id.to_string(), timestamp_ns); - - Sweep { - annotations: PyDataFrame(annotations), - city_pose: PyDataFrame(city_pose), - lidar: PyDataFrame(lidar), - sweep_uuid, - } - } - - fn __iter__(slf: PyRef<'_, Self>) -> PyRef<'_, Self> { - slf - } - - fn __next__(mut slf: PyRefMut<'_, Self>) -> Option { - slf.next() - } - - fn __len__(slf: PyRef<'_, Self>) -> usize { - slf.file_index.0.shape().0 - } - - /// Used for python pickling. - pub fn __setstate__(&mut self, state: &PyBytes) -> PyResult<()> { - *self = deserialize(state.as_bytes()).unwrap(); - Ok(()) - } - - /// Used for python pickling. - pub fn __getstate__<'py>(&self, py: Python<'py>) -> PyResult<&'py PyBytes> { - Ok(PyBytes::new(py, &serialize(&self).unwrap())) - } - - /// Used for python pickling. - pub fn __getnewargs__(&self) -> PyResult<(PathBuf, String, String, String, usize)> { - Ok(( - self.root_dir.clone(), - self.dataset_type.clone(), - self.split_name.clone(), - self.dataset_name.clone(), - self.num_accumulated_sweeps, - )) - } -} - -impl Iterator for Dataloader { - type Item = Sweep; - - fn next(&mut self) -> Option { - let idx = self.current_index; - let sweep_data = self.get(idx); - self.current_index += 1; - - Some(sweep_data) - } -} - -/// Build the dataset file index. -pub fn build_file_index( - root_dir: &Path, - dataset_name: &str, - dataset_type: &str, - split_name: &str, -) -> DataFrame { - let split_dir = root_dir.join(format!("{dataset_name}/{dataset_type}/{split_name}")); - let mut entry_set: Vec<_> = walk_dir(&split_dir) - .unwrap_or_else(|_| panic!("Cannot walk the following directory: {split_dir:?}")); - entry_set.par_sort(); - - let (log_ids, timestamp_nss, city_names): (Vec<_>, Vec<_>, Vec<_>) = - multiunzip(entry_set.into_iter().map(|log_path| { - let log_id = extract_file_stem(&log_path).unwrap(); - let lidar_dir = log_path.join("sensors/lidar"); - let x = log_path.join("map/log_map_archive_*.json"); - let city_name = glob(x.to_str().unwrap()) - .unwrap() - .find_map(Result::ok) - .unwrap_or("log_map_archive___DEFAULT_city_00000.json".into()) - .to_str() - .unwrap() - .split('_') - .collect::>()[7] - .to_string(); - - let mut lidar_entry_set: Vec<_> = glob(lidar_dir.join("*.feather").to_str().unwrap()) - .unwrap() - .filter_map(|x| x.ok()) - .map(|x| x.as_path().to_owned()) - .collect(); - lidar_entry_set.par_sort(); - - let num_entries = lidar_entry_set.len(); - ( - vec![log_id; num_entries], - lidar_entry_set - .into_iter() - .map(|lidar_path| { - let lidar_path = lidar_path.file_stem().unwrap().to_str(); - lidar_path.unwrap().parse::().unwrap() - }) - .collect::>(), - vec![city_name; num_entries], - ) - })); - df!( - "log_id" => log_ids.into_iter().flatten().collect_vec(), - "timestamp_ns" => timestamp_nss.into_iter().flatten().collect_vec(), - "city_name" => city_names.into_iter().flatten().collect_vec(), - ) - .unwrap() -} - /// Python bindings for `voxelize`. #[pyfunction] #[pyo3(name = "voxelize")] From 8e50166cfc2ffcead4c6ad4c257b2fb4ae6b826c Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 00:27:05 -0700 Subject: [PATCH 052/117] Cleanup dataloader get method. --- rust/Cargo.toml | 5 +- rust/src/constants.rs | 3 + rust/src/dataloader.rs | 134 ++++++++++++++++++++++------------------- 3 files changed, 79 insertions(+), 63 deletions(-) diff --git a/rust/Cargo.toml b/rust/Cargo.toml index e5bb8789..f11a5000 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -17,7 +17,10 @@ bincode = "1.3.3" criterion = "0.4.0" glob = "0.3.1" itertools = "0.10.5" -ndarray = { version = "0.15.6", features = ["matrixmultiply-threading", "rayon"] } +ndarray = { version = "0.15.6", features = [ + "matrixmultiply-threading", + "rayon", +] } numpy = { version = "0.18.0" } once_cell = "1.17.1" polars = { version = "0.27.2", features = [ diff --git a/rust/src/constants.rs b/rust/src/constants.rs index d9302f48..98fa980f 100644 --- a/rust/src/constants.rs +++ b/rust/src/constants.rs @@ -23,3 +23,6 @@ pub const ANNOTATION_COLUMNS: [&str; 13] = [ /// Pose dataframe columns. /// Found in `city_SE3_egovehicle`. pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; + +/// Unknown map file name for use if the map doesn't exist. +pub const DEFAULT_MAP_FILE_NAME: &str = "log_map_archive___DEFAULT_city_00000.json"; diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index 0e8b3b30..cf7eef18 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -18,7 +18,12 @@ use glob::glob; use polars::prelude::*; use pyo3::types::PyBytes; -use crate::{constants, io, path}; +use crate::{ + constants::{self, DEFAULT_MAP_FILE_NAME}, + io, path, +}; + +const MIN_NUM_LIDAR_PTS: u64 = 1; /// Data associated with a single lidar sweep. #[pyclass] @@ -114,21 +119,18 @@ impl Dataloader { } } - /// Get the dataset split directory. - pub fn split_dir(&self) -> PathBuf { + fn split_dir(&self) -> PathBuf { self.root_dir .join(&self.dataset_name) .join(&self.dataset_type) .join(&self.split_name) } - /// Get the log directory corresponding to `log_id`. - pub fn log_dir(&self, log_id: &str) -> PathBuf { + fn log_dir(&self, log_id: &str) -> PathBuf { self.split_dir().join(log_id) } - /// Get the lidar path corresponding to the `log_id` and `timestamp_ns`. - pub fn lidar_path(&self, log_id: &str, timestamp_ns: u64) -> PathBuf { + fn lidar_path(&self, log_id: &str, timestamp_ns: u64) -> PathBuf { let file_name = format!("{timestamp_ns}.feather"); let lidar_path = [ self.log_dir(log_id), @@ -141,72 +143,80 @@ impl Dataloader { lidar_path } - /// Get the annotations path correcponding to the `log_id`. - pub fn annotations_path(&self, log_id: &str) -> PathBuf { + fn annotations_path(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("annotations.feather") } - /// Get the city pose path correcponding to the `log_id`. - pub fn city_pose_path(&self, log_id: &str) -> PathBuf { + fn city_pose_path(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("city_SE3_egovehicle.feather") } - /// Get the map directory correcponding to the `log_id`. - pub fn map_dir(&self, log_id: &str) -> PathBuf { + fn map_dir(&self, log_id: &str) -> PathBuf { self.log_dir(log_id).join("map") } - /// Get the sweep at `index`. - pub fn get(&self, index: usize) -> Sweep { - let log_id = self.file_index.0["log_id"] - .utf8() - .unwrap() - .get(index) - .unwrap(); - let timestamp_ns = self.file_index.0["timestamp_ns"] - .u64() - .unwrap() - .get(index) - .unwrap(); - let lidar = read_accumulate_lidar( - self.log_dir(log_id), - &self.file_index.0, - log_id, - timestamp_ns, - index, - self.num_accumulated_sweeps, - self.memory_mapped, + fn read_city_pose(&self, log_id: &str, timestamp_ns: u64) -> PyDataFrame { + PyDataFrame( + read_timestamped_feather( + &self.city_pose_path(log_id), + &POSE_COLUMNS.to_vec(), + ×tamp_ns, + self.memory_mapped, + ) + .collect() + .unwrap(), ) - .collect() - .unwrap(); - - let annotations_path = self.annotations_path(log_id); - let annotations = read_timestamped_feather( - &annotations_path, - &ANNOTATION_COLUMNS.to_vec(), - ×tamp_ns, - self.memory_mapped, + } + + fn read_lidar(&self, log_id: &str, timestamp_ns: u64, index: usize) -> PyDataFrame { + PyDataFrame( + read_accumulate_lidar( + self.log_dir(log_id), + &self.file_index.0, + log_id, + timestamp_ns, + index, + self.num_accumulated_sweeps, + self.memory_mapped, + ) + .collect() + .unwrap(), ) - .filter(col("num_interior_pts").gt_eq(1.)) - .collect() - .unwrap(); - - let city_pose_path = self.city_pose_path(log_id); - let city_pose = read_timestamped_feather( - &city_pose_path, - &POSE_COLUMNS.to_vec(), - ×tamp_ns, - self.memory_mapped, + } + + fn read_annotations(&self, log_id: &str, timestamp_ns: u64) -> PyDataFrame { + PyDataFrame( + read_timestamped_feather( + &self.annotations_path(log_id), + &ANNOTATION_COLUMNS.to_vec(), + ×tamp_ns, + self.memory_mapped, + ) + .filter(col("num_interior_pts").gt_eq(MIN_NUM_LIDAR_PTS)) + .collect() + .unwrap(), ) - .collect() - .unwrap(); + } + + /// Get the sweep at `index`. + pub fn get(&self, index: usize) -> Sweep { + let row = self.file_index.0.get_row(index).unwrap().0; + let (log_id, timestamp_ns) = unsafe { + ( + row.get_unchecked(0).get_str().unwrap(), + row.get_unchecked(1).try_extract::().unwrap(), + ) + }; + let annotations = self.read_annotations(log_id, timestamp_ns); + let city_pose = self.read_city_pose(log_id, timestamp_ns); + let lidar = self.read_lidar(log_id, timestamp_ns, index); let sweep_uuid = (log_id.to_string(), timestamp_ns); Sweep { - annotations: PyDataFrame(annotations), - city_pose: PyDataFrame(city_pose), - lidar: PyDataFrame(lidar), + annotations, + city_pose, + lidar, sweep_uuid, } } @@ -258,8 +268,7 @@ impl Iterator for Dataloader { } } -/// Build the dataset file index. -pub fn build_file_index( +fn build_file_index( root_dir: &Path, dataset_name: &str, dataset_type: &str, @@ -270,6 +279,7 @@ pub fn build_file_index( .unwrap_or_else(|_| panic!("Cannot walk the following directory: {split_dir:?}")); entry_set.par_sort(); + let city_name_index = 7; let (log_ids, timestamp_nss, city_names): (Vec<_>, Vec<_>, Vec<_>) = multiunzip(entry_set.into_iter().map(|log_path| { let log_id = extract_file_stem(&log_path).unwrap(); @@ -278,11 +288,11 @@ pub fn build_file_index( let city_name = glob(x.to_str().unwrap()) .unwrap() .find_map(Result::ok) - .unwrap_or("log_map_archive___DEFAULT_city_00000.json".into()) + .unwrap_or(DEFAULT_MAP_FILE_NAME.into()) .to_str() .unwrap() .split('_') - .collect::>()[7] + .collect_vec()[city_name_index] .to_string(); let mut lidar_entry_set: Vec<_> = glob(lidar_dir.join("*.feather").to_str().unwrap()) @@ -301,7 +311,7 @@ pub fn build_file_index( let lidar_path = lidar_path.file_stem().unwrap().to_str(); lidar_path.unwrap().parse::().unwrap() }) - .collect::>(), + .collect_vec(), vec![city_name; num_entries], ) })); From 9e3092596f463c2b92e5fa0793c7f1528807b64d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 00:31:30 -0700 Subject: [PATCH 053/117] Minor fixes on docstrings. --- rust/src/lib.rs | 1 - src/av2/torch/dataloaders/scene_flow.py | 9 ++++++++- 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/rust/src/lib.rs b/rust/src/lib.rs index aea21484..e6e6f34a 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -22,7 +22,6 @@ use numpy::PyReadonlyArray2; use crate::ops::voxelize; -/// Python bindings for `voxelize`. #[pyfunction] #[pyo3(name = "voxelize")] #[allow(clippy::type_complexity)] diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 94e24200..9b8ca9d0 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -57,7 +57,14 @@ def file_index(self) -> pd.DataFrame: return self._backend.file_index.to_pandas() def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: - """Get a tuple of sweeps for scene flow.""" + """Get a pair of sweeps for scene flow computation. + + Args: + index: Index in [0, num_sweeps - 1]. + + Returns: + Current sweep and the next sweep (if it exists). + """ sweep = self._backend.get(index) next_sweep = None From 9df40e0d1595f8cfa4e9d73c41c803fd1fc4be40 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 00:39:57 -0700 Subject: [PATCH 054/117] Fix args ordering. --- rust/src/dataloader.rs | 14 +++++++------- src/av2/torch/dataloaders/detection.py | 16 ++++++++-------- src/av2/torch/dataloaders/scene_flow.py | 12 ++++++------ 3 files changed, 21 insertions(+), 21 deletions(-) diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index cf7eef18..29d97629 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -81,15 +81,15 @@ pub struct Dataloader { /// Number of accumulated lidar sweeps. #[pyo3(get, set)] pub num_accumulated_sweeps: usize, + /// Boolean flag to enable memory-mapped dataframe loading. + #[pyo3(get, set)] + pub memory_mapped: bool, /// Dataframe consisting of `log_id`, `timestamp_ns`, and `city_name`. #[pyo3(get, set)] pub file_index: PyDataFrame, /// Current index of the dataloader. #[pyo3(get, set)] pub current_index: usize, - /// Boolean flag to enable memory-mapped dataframe loading. - #[pyo3(get, set)] - pub memory_mapped: bool, } #[pymethods] @@ -98,10 +98,10 @@ impl Dataloader { #[new] pub fn new( root_dir: &str, + dataset_name: &str, dataset_type: &str, split_name: &str, - dataset_name: &str, - num_accum_sweeps: usize, + num_accumulated_sweeps: usize, memory_mapped: bool, ) -> Dataloader { let root_dir = Path::new(root_dir); @@ -112,10 +112,10 @@ impl Dataloader { dataset_name: dataset_name.to_string(), dataset_type: dataset_type.to_string(), split_name: split_name.to_string(), - num_accumulated_sweeps: num_accum_sweeps, + num_accumulated_sweeps, + memory_mapped, file_index: PyDataFrame(file_index), current_index: current_idx, - memory_mapped, } } diff --git a/src/av2/torch/dataloaders/detection.py b/src/av2/torch/dataloaders/detection.py index a3ee40f9..eaf59dc1 100644 --- a/src/av2/torch/dataloaders/detection.py +++ b/src/av2/torch/dataloaders/detection.py @@ -22,17 +22,17 @@ class DetectionDataloader(Dataset[Sweep]): Args: root_dir: Path to the dataset directory. - dataset_name: Dataset name. - split_name: Name of the dataset split. - num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). + dataset_name: Dataset name (e.g., "av2"). + split_name: Name of the dataset split (e.g., "train"). + num_accum_sweeps: Number of temporally accumulated sweeps (accounting for ego-vehicle motion). memory_mapped: Boolean flag indicating whether to memory map the dataframes. """ root_dir: PathType dataset_name: str split_name: str - num_accum_sweeps: int = 1 - memory_map: bool = False + num_accumulated_sweeps: int = 1 + memory_mapped: bool = False _backend: rust.Dataloader = field(init=False) _current_idx: int = 0 @@ -41,11 +41,11 @@ def __post_init__(self) -> None: """Initialize Rust backend.""" self._backend = rust.Dataloader( str(self.root_dir), + self.dataset_name, "sensor", self.split_name, - self.dataset_name, - self.num_accum_sweeps, - self.memory_map, + self.num_accumulated_sweeps, + self.memory_mapped, ) def __getitem__(self, index: int) -> Sweep: diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index 9b8ca9d0..bea5fc44 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -25,16 +25,16 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): Args: root_dir: Path to the dataset directory. - dataset_name: Dataset name. - split_name: Name of the dataset split. - num_accum_sweeps: Number of temporally accumulated sweeps (accounting for egovehicle motion). + dataset_name: Dataset name (e.g., "av2"). + split_name: Name of the dataset split (e.g., "train"). + num_accum_sweeps: Number of temporally accumulated sweeps (accounting for ego-vehicle motion). memory_mapped: Boolean flag indicating whether to memory map the dataframes. """ root_dir: PathType dataset_name: str split_name: str - num_accum_sweeps: int = 1 + num_accumulated_sweeps: int = 1 memory_mapped: bool = False _backend: rust.Dataloader = field(init=False) @@ -44,10 +44,10 @@ def __post_init__(self) -> None: """Initialize Rust backend.""" self._backend = rust.Dataloader( str(self.root_dir), + self.dataset_name, "sensor", self.split_name, - self.dataset_name, - self.num_accum_sweeps, + self.num_accumulated_sweeps, self.memory_mapped, ) From 688c4b14288e013be5e50760be8f649338aa7043 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 00:46:33 -0700 Subject: [PATCH 055/117] Add additional comments. --- src/av2/torch/dataloaders/detection.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/src/av2/torch/dataloaders/detection.py b/src/av2/torch/dataloaders/detection.py index eaf59dc1..a7712788 100644 --- a/src/av2/torch/dataloaders/detection.py +++ b/src/av2/torch/dataloaders/detection.py @@ -20,6 +20,14 @@ class DetectionDataloader(Dataset[Sweep]): """Pytorch dataloader for the sensor dataset. + The sensor dataset should exist somewhere such as `~/data/datasets/{dataset_name}/{dataset_type}/{split_name}`, + where + dataset_name = "av2", + dataset_type = "sensor, + split_name = "train". + + This dataloader backend is implemented in Rust for speed. Each iteration will yield a new sweep. + Args: root_dir: Path to the dataset directory. dataset_name: Dataset name (e.g., "av2"). From 3f6848cf3d74c85f49a1d1e1640d6aea5e8f65c8 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 00:51:39 -0700 Subject: [PATCH 056/117] Update docstring. --- rust/src/so3.rs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/rust/src/so3.rs b/rust/src/so3.rs index ee9e72d2..a7615d91 100644 --- a/rust/src/so3.rs +++ b/rust/src/so3.rs @@ -1,6 +1,6 @@ //! # SO3 //! -//! Special Orthogonal Group in 3 Dimensions. +//! Special Orthogonal Group 3 (SO(3)). use ndarray::{Array2, ArrayView1}; From 02d680486c7ba24f6c79dfd9939504cecdac6167 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 00:53:52 -0700 Subject: [PATCH 057/117] Add image deps. --- Cargo.lock | 271 +++++++++++++++++++++++++++++++++++++++++++++++- rust/Cargo.toml | 2 + 2 files changed, 272 insertions(+), 1 deletion(-) diff --git a/Cargo.lock b/Cargo.lock index 461d6f6d..6c937196 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -66,6 +66,15 @@ version = "1.0.69" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "224afbd727c3d6e4b90103ece64b8d1b67fbb1973b1046c2281eed3f3803f800" +[[package]] +name = "approx" +version = "0.5.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6" +dependencies = [ + "num-traits", +] + [[package]] name = "array-init-cursor" version = "0.2.0" @@ -171,8 +180,10 @@ dependencies = [ "bincode", "criterion", "glob", + "image", "itertools", "ndarray", + "nshare", "numpy", "once_cell", "polars", @@ -197,6 +208,12 @@ dependencies = [ "serde", ] +[[package]] +name = "bit_field" +version = "0.10.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "dc827186963e592360843fb5ba4b973e145841266c1357f7180c43526f2e5b61" + [[package]] name = "bitflags" version = "1.3.2" @@ -250,6 +267,12 @@ dependencies = [ "syn", ] +[[package]] +name = "byteorder" +version = "1.4.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "14c189c53d098945499cdfa7ecc63567cf3886b3332b312a5b4585d8d3a6a610" + [[package]] name = "bytes" version = "1.4.0" @@ -316,7 +339,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "213030a2b5a4e0c0892b6652260cf6ccac84827b83a85a534e178e3906c4cf1b" dependencies = [ "ciborium-io", - "half", + "half 1.8.2", ] [[package]] @@ -350,6 +373,12 @@ dependencies = [ "unicode-width", ] +[[package]] +name = "color_quant" +version = "1.1.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "3d7b894f5411737b7867f4827955924d7c254fc9f4d91a6aad6b097804b1018b" + [[package]] name = "comfy-table" version = "6.1.4" @@ -603,6 +632,22 @@ version = "1.3.2" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "0198b9d0078e0f30dedc7acbb21c974e838fc8fae3ee170128658a98cb2c1c04" +[[package]] +name = "exr" +version = "1.6.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "bdd2162b720141a91a054640662d3edce3d50a944a50ffca5313cd951abb35b4" +dependencies = [ + "bit_field", + "flume", + "half 2.2.1", + "lebe", + "miniz_oxide", + "rayon-core", + "smallvec", + "zune-inflate", +] + [[package]] name = "fallible-streaming-iterator" version = "0.1.9" @@ -619,6 +664,19 @@ dependencies = [ "miniz_oxide", ] +[[package]] +name = "flume" +version = "0.10.14" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "1657b4441c3403d9f7b3409e47575237dac27b1b5726df654a6ecbf92f0f7577" +dependencies = [ + "futures-core", + "futures-sink", + "nanorand", + "pin-project", + "spin", +] + [[package]] name = "foreign_vec" version = "0.1.0" @@ -727,6 +785,16 @@ dependencies = [ "wasm-bindgen", ] +[[package]] +name = "gif" +version = "0.11.4" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "3edd93c6756b4dfaf2709eafcc345ba2636565295c198a9cfbf75fa5e3e00b06" +dependencies = [ + "color_quant", + "weezl", +] + [[package]] name = "glob" version = "0.3.1" @@ -739,6 +807,15 @@ version = "1.8.2" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "eabb4a44450da02c90444cf74558da904edde8fb4e9035a9a6a4e15445af0bd7" +[[package]] +name = "half" +version = "2.2.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "02b4af3693f1b705df946e9fe5631932443781d0aabb423b62fcd4d73f6d2fd0" +dependencies = [ + "crunchy", +] + [[package]] name = "hash_hasher" version = "2.0.3" @@ -809,6 +886,25 @@ dependencies = [ "cxx-build", ] +[[package]] +name = "image" +version = "0.24.5" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "69b7ea949b537b0fd0af141fff8c77690f2ce96f4f41f042ccb6c69c6c965945" +dependencies = [ + "bytemuck", + "byteorder", + "color_quant", + "exr", + "gif", + "jpeg-decoder", + "num-rational", + "num-traits", + "png", + "scoped_threadpool", + "tiff", +] + [[package]] name = "indexmap" version = "1.9.2" @@ -858,6 +954,15 @@ dependencies = [ "libc", ] +[[package]] +name = "jpeg-decoder" +version = "0.3.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "bc0000e42512c92e31c2252315bda326620a4e034105e900c98ec492fa077b3e" +dependencies = [ + "rayon", +] + [[package]] name = "js-sys" version = "0.3.61" @@ -873,6 +978,12 @@ version = "1.4.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "e2abad23fbc42b3700f2f279844dc832adb2b2eb069b2df918f455c4e18cc646" +[[package]] +name = "lebe" +version = "0.5.2" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "03087c2bad5e1034e8cace5926dec053fb3790248370865f5117a7d0213354c8" + [[package]] name = "lexical" version = "6.1.1" @@ -1083,6 +1194,30 @@ dependencies = [ "syn", ] +[[package]] +name = "nalgebra" +version = "0.30.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "4fb2d0de08694bed883320212c18ee3008576bfe8c306f4c3c4a58b4876998be" +dependencies = [ + "approx", + "matrixmultiply", + "num-complex", + "num-rational", + "num-traits", + "simba", + "typenum", +] + +[[package]] +name = "nanorand" +version = "0.7.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "6a51313c5820b0b02bd422f4b44776fbf47961755c74ce64afc73bfad10226c3" +dependencies = [ + "getrandom", +] + [[package]] name = "ndarray" version = "0.15.6" @@ -1106,6 +1241,17 @@ dependencies = [ "chrono", ] +[[package]] +name = "nshare" +version = "0.9.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "4447657cd40e3107416ec4f2ac3e61a18781b00061789e3b8f4bbcbccb26c4c6" +dependencies = [ + "image", + "nalgebra", + "ndarray", +] + [[package]] name = "ntapi" version = "0.4.0" @@ -1311,6 +1457,32 @@ dependencies = [ "zstd", ] +[[package]] +name = "paste" +version = "1.0.12" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "9f746c4065a8fa3fe23974dd82f15431cc8d40779821001404d10d2e79ca7d79" + +[[package]] +name = "pin-project" +version = "1.0.12" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "ad29a609b6bcd67fee905812e544992d216af9d755757c05ed2d0e15a74c6ecc" +dependencies = [ + "pin-project-internal", +] + +[[package]] +name = "pin-project-internal" +version = "1.0.12" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "069bdb1e05adc7a8990dce9cc75370895fbe4e3d58b9b73bf1aee56359344a55" +dependencies = [ + "proc-macro2", + "quote", + "syn", +] + [[package]] name = "pin-project-lite" version = "0.2.9" @@ -1366,6 +1538,18 @@ dependencies = [ "plotters-backend", ] +[[package]] +name = "png" +version = "0.17.7" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "5d708eaf860a19b19ce538740d2b4bdeeb8337fa53f7738455e706623ad5c638" +dependencies = [ + "bitflags", + "crc32fast", + "flate2", + "miniz_oxide", +] + [[package]] name = "polars" version = "0.27.2" @@ -1782,6 +1966,15 @@ version = "1.0.13" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "f91339c0467de62360649f8d3e185ca8de4224ff281f66000de5eb2a77a79041" +[[package]] +name = "safe_arch" +version = "0.6.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "794821e4ccb0d9f979512f9c1973480123f9bd62a90d74ab0f9426fcf8f4a529" +dependencies = [ + "bytemuck", +] + [[package]] name = "same-file" version = "1.0.6" @@ -1791,6 +1984,12 @@ dependencies = [ "winapi-util", ] +[[package]] +name = "scoped_threadpool" +version = "0.1.9" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "1d51f5df5af43ab3f1360b429fa5e0152ac5ce8c0bd6485cae490332e96846a8" + [[package]] name = "scopeguard" version = "1.1.0" @@ -1876,6 +2075,25 @@ dependencies = [ "libc", ] +[[package]] +name = "simba" +version = "0.7.3" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "2f3fd720c48c53cace224ae62bef1bbff363a70c68c4802a78b5cc6159618176" +dependencies = [ + "approx", + "num-complex", + "num-traits", + "paste", + "wide", +] + +[[package]] +name = "simd-adler32" +version = "0.3.5" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "238abfbb77c1915110ad968465608b68e869e0772622c9656714e73e5a1a522f" + [[package]] name = "simdutf8" version = "0.1.4" @@ -1914,6 +2132,15 @@ version = "1.1.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "5e9f0ab6ef7eb7353d9119c170a436d1bf248eea575ac42d19d12f4e34130831" +[[package]] +name = "spin" +version = "0.9.6" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "b5d6e0250b93c8427a177b849d144a96d5acc57006149479403d7861ab721e34" +dependencies = [ + "lock_api", +] + [[package]] name = "static_assertions" version = "1.1.0" @@ -2035,6 +2262,17 @@ dependencies = [ "crossbeam-channel", ] +[[package]] +name = "tiff" +version = "0.8.1" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "7449334f9ff2baf290d55d73983a7d6fa15e01198faef72af07e2a8db851e471" +dependencies = [ + "flate2", + "jpeg-decoder", + "weezl", +] + [[package]] name = "time" version = "0.1.45" @@ -2065,6 +2303,12 @@ dependencies = [ "serde_json", ] +[[package]] +name = "typenum" +version = "1.16.0" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "497961ef93d974e23eb6f433eb5fe1b7930b659f06d12dec6fc44a8f554c0bba" + [[package]] name = "unicode-ident" version = "1.0.8" @@ -2203,6 +2447,22 @@ dependencies = [ "wasm-bindgen", ] +[[package]] +name = "weezl" +version = "0.1.7" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "9193164d4de03a926d909d3bc7c30543cecb35400c02114792c2cae20d5e2dbb" + +[[package]] +name = "wide" +version = "0.7.8" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "b689b6c49d6549434bf944e6b0f39238cf63693cb7a147e9d887507fffa3b223" +dependencies = [ + "bytemuck", + "safe_arch", +] + [[package]] name = "winapi" version = "0.3.9" @@ -2335,3 +2595,12 @@ dependencies = [ "libc", "pkg-config", ] + +[[package]] +name = "zune-inflate" +version = "0.2.51" +source = "registry+https://github.com/rust-lang/crates.io-index" +checksum = "a01728b79fb9b7e28a8c11f715e1cd8dc2cda7416a007d66cac55cebb3a8ac6b" +dependencies = [ + "simd-adler32", +] diff --git a/rust/Cargo.toml b/rust/Cargo.toml index f11a5000..aef4a0ec 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -16,11 +16,13 @@ anyhow = "1.0.66" bincode = "1.3.3" criterion = "0.4.0" glob = "0.3.1" +image = "0.24.5" itertools = "0.10.5" ndarray = { version = "0.15.6", features = [ "matrixmultiply-threading", "rayon", ] } +nshare = "0.9.0" numpy = { version = "0.18.0" } once_cell = "1.17.1" polars = { version = "0.27.2", features = [ From e2848c3796c285971f52a88628162b6b9b8568d9 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 09:45:49 -0700 Subject: [PATCH 058/117] Update arg. --- tutorials/detection_dataloader.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_dataloader.py index 66315cdd..f3b18497 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -13,9 +13,9 @@ def main() -> None: root_dir = Path.home() / "data" / "datasets" dataset_name = "av2" split_name = "val" - num_accum_sweeps = 1 + num_accumulated_sweeps = 1 - dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accum_sweeps=num_accum_sweeps) + dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) for sweep in tqdm(dataloader): print(sweep.lidar.as_tensor()) From 1e02e33911337a21d062814ecbd1783bce4e1fe9 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 10:00:49 -0700 Subject: [PATCH 059/117] Update readmes. --- README.md | 6 ++++-- conda/INSTALL.md | 15 +++++++++++++++ 2 files changed, 19 insertions(+), 2 deletions(-) create mode 100644 conda/INSTALL.md diff --git a/README.md b/README.md index 6444b23b..85cb69ea 100644 --- a/README.md +++ b/README.md @@ -39,12 +39,14 @@ If you have any questions or run into any problems with either the data or API, ### Setup -The easiest way to install the API is via [pip](https://pypi.org/project/av2/) by running the following command: +The easiest way to install the API is via [conda](https://conda-forge.org/) by running the following command: ```bash -pip install av2 +bash conda/install.sh ``` +Additional information can be found in: [INSTALL](conda/INSTALL.md). + ### Datasets The _Argoverse 2_ family consists of **four** distinct datasets: diff --git a/conda/INSTALL.md b/conda/INSTALL.md new file mode 100644 index 00000000..7ffff135 --- /dev/null +++ b/conda/INSTALL.md @@ -0,0 +1,15 @@ +# Conda Install + +We _highly_ recommend using `conda` for package management. To install `av2-api`, simply run: + +```bash +bash install.sh +``` + +which will install _all_ of the necessary dependencies in a conda environment named `av2`. + +To activate your environment (i.e., update your system paths), run: + +```bash +conda activate av2 +``` \ No newline at end of file From c6146d15ec777dbcf18ee6f99ca769843d22acda Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 12:28:55 -0700 Subject: [PATCH 060/117] Add additional readme + remove unused code. --- README.md | 2 +- conda/INSTALL.md | 8 +- src/av2/torch/dataloaders/scene_flow.py | 2 +- src/av2/torch/dataloaders/utils.py | 152 +----------------------- 4 files changed, 15 insertions(+), 149 deletions(-) diff --git a/README.md b/README.md index 85cb69ea..9d602ac1 100644 --- a/README.md +++ b/README.md @@ -23,7 +23,7 @@ If you have any questions or run into any problems with either the data or API, ## TL;DR -- Install the API: `pip install av2` +- Install the API: `bash conda/install.sh` - Read the [instructions](DOWNLOAD.md) to download the data. ## Overview diff --git a/conda/INSTALL.md b/conda/INSTALL.md index 7ffff135..3b5bb9ae 100644 --- a/conda/INSTALL.md +++ b/conda/INSTALL.md @@ -12,4 +12,10 @@ To activate your environment (i.e., update your system paths), run: ```bash conda activate av2 -``` \ No newline at end of file +``` + +## FAQ + +> Why `conda` instead of `pip`? + +`conda` enables package management outside of the `python` ecosystem. This enables us to specify all necessary dependencies in `environment.yml`. Further, gpu-based packages (e.g., `torch`) are handled better through `conda`. \ No newline at end of file diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/dataloaders/scene_flow.py index bea5fc44..d1301334 100644 --- a/src/av2/torch/dataloaders/scene_flow.py +++ b/src/av2/torch/dataloaders/scene_flow.py @@ -58,7 +58,7 @@ def file_index(self) -> pd.DataFrame: def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: """Get a pair of sweeps for scene flow computation. - + Args: index: Index in [0, num_sweeps - 1]. diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index adf79599..78c760a7 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -2,20 +2,17 @@ from __future__ import annotations -import itertools -import sys from dataclasses import dataclass from enum import Enum, unique from functools import cached_property from typing import Final, List, Optional, Tuple -import numpy as np import pandas as pd import torch from torch import Tensor import av2._r as rust -from av2.geometry.geometry import mat_to_xyz, quat_to_mat +from av2.geometry.geometry import quat_to_mat from av2.utils.typing import NDArrayFloat DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( @@ -43,95 +40,15 @@ class OrientationMode(str, Enum): YAW = "YAW" -@unique -class CuboidMode(str, Enum): - """Box mode (parameterization) of ground truth annotations.""" - - XYZLWH_THETA = "XYZLWH_THETA" - XYZLWH_QWXYZ = "XYZLWH_QWXYZ" - XYZ = "XYZ" - - @staticmethod - def convert(dataframe: pd.DataFrame, src: CuboidMode, target: CuboidMode) -> pd.DataFrame: - """Convert an annotations dataframe from src to target cuboid parameterization. - - Args: - dataframe: Annotations dataframe. - src: Cuboid parameterization of the dataframe. - target: Desired parameterization of the dataframe. - - Returns: - The dataframe in the new parameterization format. - - Raises: - NotImplementedError: If the cuboid mode conversion isn't supported. - """ - if src == target: - return dataframe - if src == CuboidMode.XYZLWH_QWXYZ and target == CuboidMode.XYZLWH_THETA: - quaternions = dataframe.loc[:, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float64) - rotation = quat_to_mat(quaternions) - yaw = mat_to_xyz(rotation)[:, -1] - - first_occurence = min( - i if field_name in QUAT_WXYZ_FIELDS else sys.maxsize - for (i, field_name) in enumerate(DEFAULT_ANNOTATIONS_TENSOR_FIELDS) - ) - field_ordering = tuple( - filter(lambda field_name: field_name not in QUAT_WXYZ_FIELDS, DEFAULT_ANNOTATIONS_TENSOR_FIELDS) - ) - field_ordering = field_ordering[:first_occurence] + ("yaw",) + field_ordering[first_occurence:] - dataframe["yaw"] = yaw - dataframe = dataframe[list(field_ordering)] - elif src == CuboidMode.XYZLWH_QWXYZ and target == CuboidMode.XYZ: - unit_vertices_obj_xyz_m = np.array( - [ - [+1, +1, +1], # 0 - [+1, -1, +1], # 1 - [+1, -1, -1], # 2 - [+1, +1, -1], # 3 - [-1, +1, +1], # 4 - [-1, -1, +1], # 5 - [-1, -1, -1], # 6 - [-1, +1, -1], # 7 - ], - ) - - dims_lwh_m = dataframe.loc[:, ["length_m", "width_m", "height_m"]].to_numpy().astype(np.float64) - - # Transform unit polygons. - vertices_obj_xyz_m = (dims_lwh_m[:, None] / 2.0) * unit_vertices_obj_xyz_m[None] - - quat = dataframe.loc[:, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float64) - rotation = quat_to_mat(quat) - translation = dataframe.loc[:, ["tx_m", "ty_m", "tz_m"]].to_numpy().astype(np.float64) - - vertices = (rotation @ vertices_obj_xyz_m.transpose(0, 2, 1)).transpose(0, 2, 1) + translation[:, None] - columns = list( - itertools.chain.from_iterable( - [(f"tx_{i}", f"ty_{i}", f"tz_{i}") for i in range(len(unit_vertices_obj_xyz_m))] - ) - ) - vertices = vertices.reshape(-1, len(unit_vertices_obj_xyz_m) * 3) - dataframe = dataframe.loc[:, ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]] - dataframe[:, columns] = vertices - return dataframe - else: - raise NotImplementedError("This conversion is not implemented!") - return dataframe - - @dataclass(frozen=True) class Annotations: """Dataclass for ground truth annotations. Args: dataframe: Dataframe containing the annotations and their attributes. - cuboid_mode: Cuboid parameterization mode. """ dataframe: pd.DataFrame - cuboid_mode: CuboidMode = CuboidMode.XYZLWH_QWXYZ @property def category_names(self) -> List[str]: @@ -147,39 +64,21 @@ def track_uuids(self) -> List[str]: def as_tensor( self, - cuboid_mode: CuboidMode = CuboidMode.XYZLWH_THETA, + field_ordering: Tuple[str, ...] = DEFAULT_ANNOTATIONS_TENSOR_FIELDS, dtype: torch.dtype = torch.float32, ) -> Tensor: """Return the annotations as a tensor. Args: - cuboid_mode: Target parameterization for the cuboids. + field_ordering: Feature ordering for the tensor. dtype: Target datatype for casting. Returns: (N,K) tensor where N is the number of annotations and K is the number of annotation fields. """ - dataframe = CuboidMode.convert(self.dataframe, self.cuboid_mode, cuboid_mode) - return torch.as_tensor(dataframe.to_numpy(), dtype=dtype) - - def compute_interior_points(self, lidar: Lidar) -> Tensor: - """Compute a pairwise interior point mask. - - Args: - lidar: Lidar object. - - Returns: - (num_annotations,num_points) boolean tensor indicating whether the point - falls into the kth cuboid. - """ - dataframe = CuboidMode.convert(self.dataframe, self.cuboid_mode, CuboidMode.XYZ) - points_xyz = lidar.as_tensor() - - columns = list(itertools.chain.from_iterable([(f"tx_{i}", f"ty_{i}", f"tz_{i}") for i in range(8)])) - cuboid_vertices = torch.as_tensor(dataframe[columns].to_numpy(), dtype=torch.float32).reshape(-1, 8, 3) - pairwise_point_masks = compute_interior_points_mask(points_xyz, cuboid_vertices) - return pairwise_point_masks + dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy() + return torch.as_tensor(dataframe_npy, dtype=dtype) @dataclass(frozen=True) @@ -195,7 +94,7 @@ class Lidar: def as_tensor( self, field_ordering: Tuple[str, ...] = DEFAULT_LIDAR_TENSOR_FIELDS, dtype: torch.dtype = torch.float32 ) -> Tensor: - """Return the lidar sweep as a dense tensor. + """Return the lidar sweep as a tensor. Args: field_ordering: Feature ordering for the tensor. @@ -248,42 +147,3 @@ def Rt(self) -> Tuple[Tensor, Tensor]: rotation = quat_to_mat(quat_wxyz) return torch.as_tensor(rotation, dtype=torch.float32), torch.as_tensor(translation, dtype=torch.float32) - - -def compute_interior_points_mask(xyz_m: Tensor, cuboid_vertices: Tensor) -> Tensor: - r"""Compute the interior points within a set of _axis-aligned_ cuboids. - - Reference: - https://math.stackexchange.com/questions/1472049/check-if-a-point-is-inside-a-rectangular-shaped-area-3d - 5------4 - |\\ |\\ - | \\ | \\ - 6--\\--7 \\ - \\ \\ \\ \\ - l \\ 1-------0 h - e \\ || \\ || e - n \\|| \\|| i - g \\2------3 g - t width. h - h. t. - - Args: - xyz_m: (N,3) Points in Cartesian space. - cuboid_vertices: (K,8,3) Vertices of the cuboids. - - Returns: - (N,) A tensor of boolean flags indicating whether the points - are interior to the cuboid. - """ - vertices = cuboid_vertices[:, [6, 3, 1]] - uvw = cuboid_vertices[:, 2:3] - vertices - reference_vertex = cuboid_vertices[:, 2:3] - - dot_uvw_reference = uvw @ reference_vertex.transpose(1, 2) - dot_uvw_vertices = torch.diagonal(uvw @ vertices.transpose(1, 2), 0, 2)[..., None] - dot_uvw_points = uvw @ xyz_m.T - - constraint_a = torch.logical_and(dot_uvw_reference <= dot_uvw_points, dot_uvw_points <= dot_uvw_vertices) - constraint_b = torch.logical_and(dot_uvw_reference >= dot_uvw_points, dot_uvw_points >= dot_uvw_vertices) - is_interior: Tensor = torch.logical_or(constraint_a, constraint_b).all(dim=1) - return is_interior From a51e369476119e74f7232d66ea8507771f05505d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 13:42:45 -0700 Subject: [PATCH 061/117] Fix lint. --- integration_tests/verify_tbv_download.py | 1 - noxfile.py | 1 - src/av2/datasets/motion_forecasting/scenario_serialization.py | 2 -- src/av2/rendering/map.py | 2 -- tests/geometry/test_geometry.py | 1 - tutorials/generate_egoview_overlaid_vector_map.py | 1 - tutorials/map_tutorial.ipynb | 1 - 7 files changed, 9 deletions(-) diff --git a/integration_tests/verify_tbv_download.py b/integration_tests/verify_tbv_download.py index ddba7063..6fbf4983 100644 --- a/integration_tests/verify_tbv_download.py +++ b/integration_tests/verify_tbv_download.py @@ -195,7 +195,6 @@ def verify_logs_using_dataloader(data_root: Path, log_ids: Tuple[str, ...]) -> N """ loader = AV2SensorDataLoader(data_dir=data_root, labels_dir=data_root) for log_id in track(log_ids, description="Verify logs using an AV2 dataloader object"): - logger.info("Verifying log %s", log_id) # city abbreviation should be parsable from every vector map file name, and should fall into 1 of 6 cities city_name = loader.get_city_name(log_id=log_id) diff --git a/noxfile.py b/noxfile.py index b1ed5d00..e2a40335 100644 --- a/noxfile.py +++ b/noxfile.py @@ -22,7 +22,6 @@ def _setup(session: Session) -> None: session: `nox` session. """ if isinstance(session.virtualenv, CondaEnv): - # Load environment.yml file and install conda dependencies. env = yaml.safe_load(Path("conda/environment.yml").read_text()) diff --git a/src/av2/datasets/motion_forecasting/scenario_serialization.py b/src/av2/datasets/motion_forecasting/scenario_serialization.py index bb38c82a..3c185657 100644 --- a/src/av2/datasets/motion_forecasting/scenario_serialization.py +++ b/src/av2/datasets/motion_forecasting/scenario_serialization.py @@ -90,7 +90,6 @@ def _convert_tracks_to_tabular_format(tracks: List[Track]) -> pd.DataFrame: track_dfs: List[pd.DataFrame] = [] for track in tracks: - track_df = pd.DataFrame() observed_states: List[bool] = [] @@ -138,7 +137,6 @@ def _load_tracks_from_tabular_format(tracks_df: pd.DataFrame) -> List[Track]: tracks: List[Track] = [] for track_id, track_df in tracks_df.groupby("track_id"): - observed_states: List[bool] = track_df.loc[:, "observed"].values.tolist() object_type: ObjectType = ObjectType(track_df["object_type"].iloc[0]) object_category: TrackCategory = TrackCategory(track_df["object_category"].iloc[0]) diff --git a/src/av2/rendering/map.py b/src/av2/rendering/map.py index 990a677f..79e6052e 100644 --- a/src/av2/rendering/map.py +++ b/src/av2/rendering/map.py @@ -171,7 +171,6 @@ def draw_dashed_polyline_egoview( """ interp_polyline, num_waypts = polyline_utils.interp_polyline_by_fixed_waypt_interval(polyline, dash_interval_m) for i in range(num_waypts - 1): - # every other segment is a gap # (first the next dash interval is a line, and then the dash interval is empty, ...) if (i % dash_frequency) != 0: @@ -254,7 +253,6 @@ def draw_visible_polyline_segments_cv2( """ line_segments_arr_int: NDArrayInt = np.round(line_segments_arr).astype(int) for i in range(len(line_segments_arr_int) - 1): - if (not valid_pts_bool[i]) or (not valid_pts_bool[i + 1]): continue diff --git a/tests/geometry/test_geometry.py b/tests/geometry/test_geometry.py index 637a37fa..a12f93ac 100644 --- a/tests/geometry/test_geometry.py +++ b/tests/geometry/test_geometry.py @@ -494,7 +494,6 @@ def test_xyz_to_mat_vs_gtsam() -> None: """Compare our implementation (using Scipy) vs. the GTSAM derivation.""" num_iters = 10000 for _ in range(num_iters): - # in [-pi, pi] x = 2 * np.pi * (np.random.rand() - 0.5) z = 2 * np.pi * (np.random.rand() - 0.5) diff --git a/tutorials/generate_egoview_overlaid_vector_map.py b/tutorials/generate_egoview_overlaid_vector_map.py index b5aa678b..584bd2de 100644 --- a/tutorials/generate_egoview_overlaid_vector_map.py +++ b/tutorials/generate_egoview_overlaid_vector_map.py @@ -204,7 +204,6 @@ def render_egoview_with_occlusion_checks( img_canvas = egoview_renderer.render_lane_boundary_egoview(img_canvas, ls, "left", line_width_px) for pc in egoview_renderer.avm.get_scenario_ped_crossings(): - EPS = 1e-5 crosswalk_color = BLUE_BGR # render ped crossings (pc's) diff --git a/tutorials/map_tutorial.ipynb b/tutorials/map_tutorial.ipynb index f68e27b6..6367577a 100644 --- a/tutorials/map_tutorial.ipynb +++ b/tutorials/map_tutorial.ipynb @@ -109,7 +109,6 @@ " ax = fig.add_subplot()\n", "\n", " for _, ls in avm.vector_lane_segments.items():\n", - "\n", " # right_ln_bnd\n", " # left_ln_bnd\n", " vector_plotting_utils.draw_polygon_mpl(ax, ls.polygon_boundary, color=\"g\", linewidth=0.5)\n", From e6d1a97f25daa72b32494dcfffa9f5303573025f Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 14:07:57 -0700 Subject: [PATCH 062/117] Add option type for annotations. --- rust/src/dataloader.rs | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index 29d97629..a441ca66 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -30,7 +30,7 @@ const MIN_NUM_LIDAR_PTS: u64 = 1; pub struct Sweep { /// Ground truth annotations. #[pyo3(get, set)] - pub annotations: PyDataFrame, + pub annotations: Option, /// Ego-vehicle city pose. #[pyo3(get, set)] pub city_pose: PyDataFrame, @@ -54,7 +54,7 @@ impl Sweep { sweep_uuid: (String, u64), ) -> Sweep { Sweep { - annotations, + annotations: Some(annotations), city_pose, lidar, sweep_uuid, @@ -208,7 +208,12 @@ impl Dataloader { ) }; - let annotations = self.read_annotations(log_id, timestamp_ns); + // Annotations aren't available for the test set. + let annotations = match self.split_name.as_str() { + "test" => None, + _ => Some(self.read_annotations(log_id, timestamp_ns)), + }; + let city_pose = self.read_city_pose(log_id, timestamp_ns); let lidar = self.read_lidar(log_id, timestamp_ns, index); let sweep_uuid = (log_id.to_string(), timestamp_ns); From afe0cf71a2d0b1133ab0deb2f3d1432e2ea08c9e Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 15:38:19 -0700 Subject: [PATCH 063/117] Remove hard-coded mmap. --- rust/src/io.rs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index ba0f1053..59a799b2 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -54,7 +54,7 @@ pub fn read_accumulate_lidar( let log_ids = file_index["log_id"].utf8().unwrap(); let timestamps = file_index["timestamp_ns"].u64().unwrap(); let poses_path = log_dir.join("city_SE3_egovehicle.feather"); - let poses = read_feather(&poses_path, true); + let poses = read_feather(&poses_path, memory_mapped); let pose_ref = dataframe_to_nd_and_filter( &poses, From 19384c91951c3a1e5a7687cde1f694b8337ff25f Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 15:59:35 -0700 Subject: [PATCH 064/117] Update readmes. --- README.md | 2 +- conda/INSTALL.md | 20 ++++++++++++++++---- 2 files changed, 17 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 9d602ac1..0647c871 100644 --- a/README.md +++ b/README.md @@ -39,7 +39,7 @@ If you have any questions or run into any problems with either the data or API, ### Setup -The easiest way to install the API is via [conda](https://conda-forge.org/) by running the following command: +The easiest way to install the API is via [conda](https://docs.conda.io/en/latest/) by running the following command: ```bash bash conda/install.sh diff --git a/conda/INSTALL.md b/conda/INSTALL.md index 3b5bb9ae..6723d23d 100644 --- a/conda/INSTALL.md +++ b/conda/INSTALL.md @@ -1,6 +1,14 @@ -# Conda Install +# Installation -We _highly_ recommend using `conda` for package management. To install `av2-api`, simply run: +We _highly_ recommend using `conda` with the `conda-forge` channel for package management. + +## Install `conda` + +You will need to install `conda` on your machine. We recommend to install the `conda-forge` version of `conda` found at https://github.com/conda-forge/miniforge#install. + +## Install `av2` + +Simply run: ```bash bash install.sh @@ -16,6 +24,10 @@ conda activate av2 ## FAQ -> Why `conda` instead of `pip`? +> Why manage dependencies in `conda` instead of `pip`? + +`conda` enables package management outside of the `python` ecosystem. This enables us to specify all necessary dependencies in `environment.yml`. Further, gpu-based packages (e.g., `torch`) are handled better through `conda`. + +> Why `conda-forge`? -`conda` enables package management outside of the `python` ecosystem. This enables us to specify all necessary dependencies in `environment.yml`. Further, gpu-based packages (e.g., `torch`) are handled better through `conda`. \ No newline at end of file +`conda-forge` is a community-driven channel of conda recipes. It includes a large number of packages which can all be properly tracked in the `conda` resolver allowing for consistent environments without conflicts. \ No newline at end of file From 5c560bdf7f8600d3040148c4e71f4485b7bc29de Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 16:02:07 -0700 Subject: [PATCH 065/117] Update torch init. --- src/av2/torch/__init__.py | 11 +---------- 1 file changed, 1 insertion(+), 10 deletions(-) diff --git a/src/av2/torch/__init__.py b/src/av2/torch/__init__.py index 80913cb6..44b45e6b 100644 --- a/src/av2/torch/__init__.py +++ b/src/av2/torch/__init__.py @@ -1,10 +1 @@ -"""AV2 Pytorch interface.""" - -import logging - -logger = logging.getLogger(__name__) - -try: - import torch -except ImportError as _: - logger.error("Please install Pytorch to use this module.") +"""AV2 Pytorch api.""" From 07b7eff2930bca025be8cadf67fac218fb027138 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 17:44:31 -0700 Subject: [PATCH 066/117] Fix utils shapes. --- src/av2/torch/dataloaders/utils.py | 23 +++++++++++------------ 1 file changed, 11 insertions(+), 12 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 78c760a7..76f532c8 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -7,13 +7,14 @@ from functools import cached_property from typing import Final, List, Optional, Tuple +import numpy as np import pandas as pd import torch from torch import Tensor import av2._r as rust from av2.geometry.geometry import quat_to_mat -from av2.utils.typing import NDArrayFloat +from av2.utils.typing import NDArrayFloat, NDArrayFloat32 DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( "tx_m", @@ -65,20 +66,18 @@ def track_uuids(self) -> List[str]: def as_tensor( self, field_ordering: Tuple[str, ...] = DEFAULT_ANNOTATIONS_TENSOR_FIELDS, - dtype: torch.dtype = torch.float32, ) -> Tensor: """Return the annotations as a tensor. Args: field_ordering: Feature ordering for the tensor. - dtype: Target datatype for casting. Returns: (N,K) tensor where N is the number of annotations and K is the number of annotation fields. """ - dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy() - return torch.as_tensor(dataframe_npy, dtype=dtype) + dataframe_npy: NDArrayFloat32 = self.dataframe.loc[:, list(field_ordering)].to_numpy(np.float32) + return torch.as_tensor(dataframe_npy) @dataclass(frozen=True) @@ -92,20 +91,20 @@ class Lidar: dataframe: pd.DataFrame def as_tensor( - self, field_ordering: Tuple[str, ...] = DEFAULT_LIDAR_TENSOR_FIELDS, dtype: torch.dtype = torch.float32 + self, + field_ordering: Tuple[str, ...] = DEFAULT_LIDAR_TENSOR_FIELDS, ) -> Tensor: """Return the lidar sweep as a tensor. Args: field_ordering: Feature ordering for the tensor. - dtype: Target datatype for casting. Returns: (N,K) tensor where N is the number of lidar points and K is the number of features. """ - dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy() - return torch.as_tensor(dataframe_npy, dtype=dtype) + dataframe_npy: NDArrayFloat32 = self.dataframe.loc[:, list(field_ordering)].to_numpy(np.float32) + return torch.as_tensor(dataframe_npy) @dataclass(frozen=True) @@ -142,8 +141,8 @@ class Pose: @cached_property def Rt(self) -> Tuple[Tensor, Tensor]: """Return a (3,3) rotation matrix and a (3,) translation vector.""" - quat_wxyz: NDArrayFloat = self.dataframe[QUAT_WXYZ_FIELDS].to_numpy() - translation: NDArrayFloat = self.dataframe[TRANSLATION_FIELDS].to_numpy() + quat_wxyz: NDArrayFloat = self.dataframe.loc[0, list(QUAT_WXYZ_FIELDS)].to_numpy(np.float32) + translation: NDArrayFloat = self.dataframe.loc[0, list(TRANSLATION_FIELDS)].to_numpy(np.float32) rotation = quat_to_mat(quat_wxyz) - return torch.as_tensor(rotation, dtype=torch.float32), torch.as_tensor(translation, dtype=torch.float32) + return torch.as_tensor(rotation), torch.as_tensor(translation) From e5fea8a3529f8ed1287dfba470f32a8637acc3a7 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 17:46:29 -0700 Subject: [PATCH 067/117] Update typing. --- src/av2/torch/dataloaders/utils.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 76f532c8..ed9dd619 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -14,7 +14,6 @@ import av2._r as rust from av2.geometry.geometry import quat_to_mat -from av2.utils.typing import NDArrayFloat, NDArrayFloat32 DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( "tx_m", @@ -76,7 +75,7 @@ def as_tensor( (N,K) tensor where N is the number of annotations and K is the number of annotation fields. """ - dataframe_npy: NDArrayFloat32 = self.dataframe.loc[:, list(field_ordering)].to_numpy(np.float32) + dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy().astype(np.float32) return torch.as_tensor(dataframe_npy) @@ -103,7 +102,7 @@ def as_tensor( (N,K) tensor where N is the number of lidar points and K is the number of features. """ - dataframe_npy: NDArrayFloat32 = self.dataframe.loc[:, list(field_ordering)].to_numpy(np.float32) + dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy().astype(np.float32) return torch.as_tensor(dataframe_npy) @@ -141,8 +140,8 @@ class Pose: @cached_property def Rt(self) -> Tuple[Tensor, Tensor]: """Return a (3,3) rotation matrix and a (3,) translation vector.""" - quat_wxyz: NDArrayFloat = self.dataframe.loc[0, list(QUAT_WXYZ_FIELDS)].to_numpy(np.float32) - translation: NDArrayFloat = self.dataframe.loc[0, list(TRANSLATION_FIELDS)].to_numpy(np.float32) + quat_wxyz = self.dataframe.loc[0, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float32) + translation = self.dataframe.loc[0, list(TRANSLATION_FIELDS)].to_numpy().astype(np.float32) rotation = quat_to_mat(quat_wxyz) return torch.as_tensor(rotation), torch.as_tensor(translation) From 2309934231a2e7fbbaf3ae05340038a7b14161a9 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Tue, 14 Mar 2023 17:47:03 -0700 Subject: [PATCH 068/117] Modify docstring. --- src/av2/torch/dataloaders/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index ed9dd619..31a25a78 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -34,7 +34,7 @@ @unique class OrientationMode(str, Enum): - """Orientation (pose) modes for the ground truth annotations.""" + """Orientation modes for the ground truth annotations.""" QUATERNION_WXYZ = "QUATERNION_WXYZ" YAW = "YAW" From 9baffc666d299fc0cb40384ca4cf4b9899e5a3a4 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Wed, 15 Mar 2023 11:21:51 -0700 Subject: [PATCH 069/117] Update utils.py Remove cast. --- src/av2/evaluation/detection/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/av2/evaluation/detection/utils.py b/src/av2/evaluation/detection/utils.py index 66fd07a9..653696f8 100644 --- a/src/av2/evaluation/detection/utils.py +++ b/src/av2/evaluation/detection/utils.py @@ -13,7 +13,7 @@ import logging from dataclasses import dataclass from pathlib import Path -from typing import Dict, List, Optional, Tuple, Union, cast +from typing import Dict, List, Optional, Tuple, Union import numpy as np from joblib import Parallel, delayed @@ -316,7 +316,7 @@ def compute_average_precision( # Evaluate precision at different recalls. precision_interpolated: NDArrayFloat = np.interp(recall_interpolated, recall, precision, right=0) - average_precision: float = cast(float, np.mean(precision_interpolated)) + average_precision = np.mean(precision_interpolated).astype(float) return average_precision, precision_interpolated From c618359cc055e1ff9eb8ab60493409f215dae097 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Fri, 17 Mar 2023 11:10:34 -0700 Subject: [PATCH 070/117] Add maximize build space. --- .github/workflows/ci.yml | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index ff39f09b..572c9653 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -18,6 +18,12 @@ jobs: shell: bash -l {0} steps: + - name: Maximize build space. + uses: easimon/maximize-build-space@master + with: + root-reserve-mb: 512 + swap-size-mb: 1024 + remove-dotnet: 'true' - uses: actions/checkout@v2 - uses: conda-incubator/setup-miniconda@v2 with: From 027b21a2cab0e76fa76f553c93489d415cb9f8d1 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Fri, 17 Mar 2023 12:10:31 -0700 Subject: [PATCH 071/117] Comment out torch temporarily. --- .github/workflows/ci.yml | 6 ------ pyproject.toml | 2 +- 2 files changed, 1 insertion(+), 7 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 572c9653..ff39f09b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -18,12 +18,6 @@ jobs: shell: bash -l {0} steps: - - name: Maximize build space. - uses: easimon/maximize-build-space@master - with: - root-reserve-mb: 512 - swap-size-mb: 1024 - remove-dotnet: 'true' - uses: actions/checkout@v2 - uses: conda-incubator/setup-miniconda@v2 with: diff --git a/pyproject.toml b/pyproject.toml index f10e72c6..0f6a9339 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -27,7 +27,7 @@ dependencies = [ "pyproj", "rich", "scipy", - "torch", + # "torch", "universal_pathlib", ] From 455baca9d3cc38af7619eae7020f1f32f25b87db Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Fri, 17 Mar 2023 13:48:40 -0700 Subject: [PATCH 072/117] Restructure torch dataloader. --- conda/environment.yml | 1 + pyproject.toml | 1 + src/av2/torch/dataloaders/utils.py | 98 +++++++++++++++--------------- 3 files changed, 52 insertions(+), 48 deletions(-) diff --git a/conda/environment.yml b/conda/environment.yml index 9aadd0ab..0ee542db 100644 --- a/conda/environment.yml +++ b/conda/environment.yml @@ -5,6 +5,7 @@ dependencies: - av - click - joblib + - kornia - matplotlib-base - maturin - nox diff --git a/pyproject.toml b/pyproject.toml index 0f6a9339..c1e520f8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,6 +16,7 @@ dependencies = [ "av", "click", "joblib", + "kornia", "matplotlib", "nox", "numba", diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 31a25a78..c9d04e27 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -4,16 +4,16 @@ from dataclasses import dataclass from enum import Enum, unique -from functools import cached_property from typing import Final, List, Optional, Tuple import numpy as np import pandas as pd import torch +from kornia.geometry.liegroup import Se3, So3 +from kornia.geometry.quaternion import Quaternion from torch import Tensor import av2._r as rust -from av2.geometry.geometry import quat_to_mat DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( "tx_m", @@ -27,7 +27,7 @@ "qy", "qz", ) -DEFAULT_LIDAR_TENSOR_FIELDS: Final = ("x", "y", "z") +DEFAULT_LIDAR_TENSOR_FIELDS: Final = ("x", "y", "z", "intensity") QUAT_WXYZ_FIELDS: Final = ("qw", "qx", "qy", "qz") TRANSLATION_FIELDS: Final = ("tx_m", "ty_m", "tz_m") @@ -79,69 +79,71 @@ def as_tensor( return torch.as_tensor(dataframe_npy) -@dataclass(frozen=True) -class Lidar: - """Dataclass for lidar sweeps. - - Args: - dataframe: Dataframe containing the lidar and its attributes. - """ - - dataframe: pd.DataFrame - - def as_tensor( - self, - field_ordering: Tuple[str, ...] = DEFAULT_LIDAR_TENSOR_FIELDS, - ) -> Tensor: - """Return the lidar sweep as a tensor. - - Args: - field_ordering: Feature ordering for the tensor. - - Returns: - (N,K) tensor where N is the number of lidar points and K - is the number of features. - """ - dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy().astype(np.float32) - return torch.as_tensor(dataframe_npy) - - @dataclass(frozen=True) class Sweep: """Stores the annotations and lidar for one sweep. + Notation: + N: Number of lidar points. + Args: annotations: Annotations parameterization. - city_pose: Rigid transformation describing the city pose of the ego-vehicle. - lidar: Lidar parameters. + city_SE3_ego: Rigid transformation describing the city pose of the ego-vehicle. + lidar_xyzi: (N,4) Tensor of lidar points containing (x,y,z) in meters and intensity (i). sweep_uuid: Log id and nanosecond timestamp (unique identifier). """ annotations: Optional[Annotations] - city_pose: Pose - lidar: Lidar + city_SE3_ego: Se3 + lidar_xyzi: Tensor sweep_uuid: Tuple[str, int] @classmethod def from_rust(cls, sweep: rust.Sweep) -> Sweep: """Build a sweep from the Rust backend.""" annotations = Annotations(dataframe=sweep.annotations.to_pandas()) - city_pose = Pose(dataframe=sweep.city_pose.to_pandas()) - lidar = Lidar(dataframe=sweep.lidar.to_pandas()) - return cls(annotations=annotations, city_pose=city_pose, lidar=lidar, sweep_uuid=sweep.sweep_uuid) + city_SE3_ego = frame_to_SE3(frame=sweep.city_pose.to_pandas()) + lidar_xyzi = frame_to_tensor(sweep.lidar.to_pandas()) + return cls( + annotations=annotations, city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid + ) -@dataclass(frozen=True) -class Pose: - """Pose class for rigid transformations.""" - dataframe: pd.DataFrame +def frame_to_tensor(frame: pd.DataFrame) -> Tensor: + """Build lidar `torch` tensor from `pandas` dataframe. + + Notation: + N: Number of lidar points. + K: Number of lidar attributes. + + Args: + frame: (N,K) Pandas DataFrame containing lidar fields. + + Returns: + (N,4) Tensor of (x,y,z) in meters and intensity (i). + """ + lidar_npy = frame.loc[:, list(DEFAULT_LIDAR_TENSOR_FIELDS)].to_numpy().astype(np.float32) + return torch.as_tensor(lidar_npy) + - @cached_property - def Rt(self) -> Tuple[Tensor, Tensor]: - """Return a (3,3) rotation matrix and a (3,) translation vector.""" - quat_wxyz = self.dataframe.loc[0, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(np.float32) - translation = self.dataframe.loc[0, list(TRANSLATION_FIELDS)].to_numpy().astype(np.float32) +def frame_to_SE3(frame: pd.DataFrame) -> Se3: + """Build SE(3) object from `pandas` DataFrame. - rotation = quat_to_mat(quat_wxyz) - return torch.as_tensor(rotation), torch.as_tensor(translation) + Notation: + N: Number of rigid transformations. + + Args: + frame: (N,4) Pandas DataFrame containing quaternion coefficients. + + Returns: + Kornia Se3 object representing a (N,4,4) tensor of homogeneous transformations. + """ + quaternion_npy = frame.loc[0, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(float) + quat_wxyz = Quaternion(torch.as_tensor(quaternion_npy, dtype=torch.float32)) + rotation = So3(quat_wxyz) + + translation_npy = frame.loc[0, list(TRANSLATION_FIELDS)].to_numpy().astype(np.float32) + translation = torch.as_tensor(translation_npy, dtype=torch.float32) + dst_SE3_src = Se3(rotation[None], translation[None]) + return dst_SE3_src From 6344744f1a329abbc45a0a85361af6813b675321 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Fri, 17 Mar 2023 14:26:27 -0700 Subject: [PATCH 073/117] Update ci. --- .github/workflows/ci.yml | 7 +++++++ pyproject.toml | 2 +- 2 files changed, 8 insertions(+), 1 deletion(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index ff39f09b..100695cf 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -25,6 +25,13 @@ jobs: miniforge-version: latest python-version: ${{ matrix.python_version }} + - name: Reclaim space. + run: | + sudo rm -rf /usr/share/dotnet + sudo rm -rf /opt/ghc + sudo rm -rf "/usr/local/share/boost" + sudo rm -rf "$AGENT_TOOLSDIRECTORY" + - name: Install prerequisites. run: | mamba install -y nox pip pyyaml diff --git a/pyproject.toml b/pyproject.toml index c1e520f8..cc172da4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -28,7 +28,7 @@ dependencies = [ "pyproj", "rich", "scipy", - # "torch", + "torch", "universal_pathlib", ] From c37f2f4a9f6bc60225630ed750386b4a4708648b Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Fri, 17 Mar 2023 14:33:19 -0700 Subject: [PATCH 074/117] Update ci. --- .github/workflows/ci.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 100695cf..0f154730 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -27,10 +27,10 @@ jobs: - name: Reclaim space. run: | - sudo rm -rf /usr/share/dotnet - sudo rm -rf /opt/ghc - sudo rm -rf "/usr/local/share/boost" - sudo rm -rf "$AGENT_TOOLSDIRECTORY" + rm -rf /usr/share/dotnet + rm -rf /opt/ghc + rm -rf "/usr/local/share/boost" + rm -rf "$AGENT_TOOLSDIRECTORY" - name: Install prerequisites. run: | From f62cb091895dbbe83948972254ab8bd59ad266c1 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 15:38:00 -0700 Subject: [PATCH 075/117] Remove explicit final types. --- src/av2/evaluation/detection/constants.py | 26 +++++++++++------------ 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/src/av2/evaluation/detection/constants.py b/src/av2/evaluation/detection/constants.py index f0181adb..877abd9e 100644 --- a/src/av2/evaluation/detection/constants.py +++ b/src/av2/evaluation/detection/constants.py @@ -3,30 +3,30 @@ """3D object detection evaluation constants.""" from enum import Enum, unique -from typing import Final, List +from typing import Final from av2.utils.constants import PI -MAX_SCALE_ERROR: Final[float] = 1.0 -MAX_YAW_RAD_ERROR: Final[float] = PI +MAX_SCALE_ERROR: Final = 1.0 +MAX_YAW_RAD_ERROR: Final = PI # Higher is better. -MIN_AP: Final[float] = 0.0 -MIN_CDS: Final[float] = 0.0 +MIN_AP: Final = 0.0 +MIN_CDS: Final = 0.0 # Lower is better. -MAX_NORMALIZED_ATE: Final[float] = 1.0 -MAX_NORMALIZED_ASE: Final[float] = 1.0 -MAX_NORMALIZED_AOE: Final[float] = 1.0 +MAX_NORMALIZED_ATE: Final = 1.0 +MAX_NORMALIZED_ASE: Final = 1.0 +MAX_NORMALIZED_AOE: Final = 1.0 # Max number of boxes considered per class per scene. -MAX_NUM_BOXES: Final[int] = 500 +MAX_NUM_BOXES: Final = 500 -NUM_DECIMALS: Final[int] = 3 +NUM_DECIMALS: Final = 3 -TRANSLATION_COLS: Final[List[str]] = ["tx_m", "ty_m", "tz_m"] -DIMENSION_COLS: Final[List[str]] = ["length_m", "width_m", "height_m"] -QUAT_WXYZ_COLS: Final[List[str]] = ["qw", "qx", "qy", "qz"] +TRANSLATION_COLS: Final = ["tx_m", "ty_m", "tz_m"] +DIMENSION_COLS: Final = ["length_m", "width_m", "height_m"] +QUAT_WXYZ_COLS: Final = ["qw", "qx", "qy", "qz"] @unique From f82c083e00caeab2a1bcdaeb32c20a880699d3ce Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 17:55:41 -0700 Subject: [PATCH 076/117] Update object types. --- rust/src/dataloader.rs | 10 ++- src/av2/evaluation/detection/eval.py | 2 - src/av2/torch/dataloaders/utils.py | 102 ++++++++++++++------------- tutorials/detection_dataloader.py | 4 +- 4 files changed, 60 insertions(+), 58 deletions(-) diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index a441ca66..4adb2214 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -201,12 +201,10 @@ impl Dataloader { /// Get the sweep at `index`. pub fn get(&self, index: usize) -> Sweep { let row = self.file_index.0.get_row(index).unwrap().0; - let (log_id, timestamp_ns) = unsafe { - ( - row.get_unchecked(0).get_str().unwrap(), - row.get_unchecked(1).try_extract::().unwrap(), - ) - }; + let (log_id, timestamp_ns) = ( + row.get(0).unwrap().get_str().unwrap(), + row.get(1).unwrap().try_extract::().unwrap(), + ); // Annotations aren't available for the test set. let annotations = match self.split_name.as_str() { diff --git a/src/av2/evaluation/detection/eval.py b/src/av2/evaluation/detection/eval.py index 7a9453ee..66f334a8 100644 --- a/src/av2/evaluation/detection/eval.py +++ b/src/av2/evaluation/detection/eval.py @@ -170,8 +170,6 @@ def evaluate( with mp.get_context("spawn").Pool(processes=n_jobs) as p: outputs: Optional[List[Tuple[NDArrayFloat, NDArrayFloat]]] = p.starmap(accumulate, args_list) - if outputs is None: - raise RuntimeError("Accumulation has failed! Please check the integrity of your detections and annotations.") dts_list, gts_list = zip(*outputs) METRIC_COLUMN_NAMES = cfg.affinity_thresholds_m + TP_ERROR_COLUMNS + ("is_evaluated",) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index c9d04e27..46c1b6ea 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -3,12 +3,13 @@ from __future__ import annotations from dataclasses import dataclass -from enum import Enum, unique +from functools import cached_property from typing import Final, List, Optional, Tuple import numpy as np import pandas as pd import torch +from kornia.geometry.conversions import euler_from_quaternion from kornia.geometry.liegroup import Se3, So3 from kornia.geometry.quaternion import Quaternion from torch import Tensor @@ -32,51 +33,49 @@ TRANSLATION_FIELDS: Final = ("tx_m", "ty_m", "tz_m") -@unique -class OrientationMode(str, Enum): - """Orientation modes for the ground truth annotations.""" - - QUATERNION_WXYZ = "QUATERNION_WXYZ" - YAW = "YAW" - - @dataclass(frozen=True) -class Annotations: - """Dataclass for ground truth annotations. +class Cuboids: + """Object containing metadata for cuboids. Args: - dataframe: Dataframe containing the annotations and their attributes. + _frame: Dataframe containing the annotations and their attributes. """ - dataframe: pd.DataFrame + _frame: pd.DataFrame - @property - def category_names(self) -> List[str]: + @cached_property + def categories(self) -> List[str]: """Return the category names.""" - category_names: List[str] = self.dataframe["category"].to_list() - return category_names - - @property - def track_uuids(self) -> List[str]: - """Return the unique track identifiers.""" - category_names: List[str] = self.dataframe["track_uuid"].to_list() + category_names: List[str] = self._frame["category"].to_list() return category_names - def as_tensor( - self, - field_ordering: Tuple[str, ...] = DEFAULT_ANNOTATIONS_TENSOR_FIELDS, - ) -> Tensor: - """Return the annotations as a tensor. + @cached_property + def as_tensor(self) -> Tensor: + """Return cuboids as a (N,7) tensor. - Args: - field_ordering: Feature ordering for the tensor. + Parameterization (7,): + tx_m: Translation in the x-axis in meters. + ty_m: Translation in the y-axis in meters. + tz_m: Translation in the z-axis in meters. + length_m: Length in meters. + width_m: Width in meters. + height_m: Height in meters. + yaw_radians: Counter-clock rotation measured from the x-axis. Returns: - (N,K) tensor where N is the number of annotations and K - is the number of annotation fields. + (N,7) Cuboids parameterized as (tx_m,ty_m,tz_m,length_m,width_m,height_m,yaw_radians). """ - dataframe_npy = self.dataframe.loc[:, list(field_ordering)].to_numpy().astype(np.float32) - return torch.as_tensor(dataframe_npy) + cuboids_qwxyz = frame_to_tensor(self._frame, list(DEFAULT_ANNOTATIONS_TENSOR_FIELDS)) + quat_wxyz = cuboids_qwxyz[:, 6:10] + w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] + _, _, yaw = euler_from_quaternion(w, x, y, z) + return torch.concat([cuboids_qwxyz[:, :6], yaw[:, None]], dim=-1) + + @cached_property + def track_uuids(self) -> List[str]: + """Return the unique track identifiers.""" + category_names: List[str] = self._frame["track_uuid"].to_list() + return category_names @dataclass(frozen=True) @@ -87,44 +86,49 @@ class Sweep: N: Number of lidar points. Args: - annotations: Annotations parameterization. city_SE3_ego: Rigid transformation describing the city pose of the ego-vehicle. lidar_xyzi: (N,4) Tensor of lidar points containing (x,y,z) in meters and intensity (i). sweep_uuid: Log id and nanosecond timestamp (unique identifier). + cuboids: Cuboids representing objects in the scene. """ - annotations: Optional[Annotations] city_SE3_ego: Se3 lidar_xyzi: Tensor sweep_uuid: Tuple[str, int] + cuboids: Optional[Cuboids] @classmethod def from_rust(cls, sweep: rust.Sweep) -> Sweep: - """Build a sweep from the Rust backend.""" - annotations = Annotations(dataframe=sweep.annotations.to_pandas()) - city_SE3_ego = frame_to_SE3(frame=sweep.city_pose.to_pandas()) - lidar_xyzi = frame_to_tensor(sweep.lidar.to_pandas()) + """Build a sweep from the Rust backend. - return cls( - annotations=annotations, city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid - ) + Args: + sweep: Sweep object from the Rust backend dataloader. + Returns: + Sweep object. + """ + cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) + city_SE3_ego = frame_to_SE3(frame=sweep.city_pose.to_pandas()) + lidar_xyzi = frame_to_tensor(sweep.lidar.to_pandas(), list(DEFAULT_LIDAR_TENSOR_FIELDS)) + return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) -def frame_to_tensor(frame: pd.DataFrame) -> Tensor: + +def frame_to_tensor(frame: pd.DataFrame, columns: List[str]) -> Tensor: """Build lidar `torch` tensor from `pandas` dataframe. Notation: - N: Number of lidar points. - K: Number of lidar attributes. + N: Number of rows. + K: Number of columns. Args: - frame: (N,K) Pandas DataFrame containing lidar fields. + frame: (N,K) Pandas DataFrame containing N rows with K columns. + fields: List of DataFrame columns. Returns: - (N,4) Tensor of (x,y,z) in meters and intensity (i). + (N,K) tensor containing the frame data. """ - lidar_npy = frame.loc[:, list(DEFAULT_LIDAR_TENSOR_FIELDS)].to_numpy().astype(np.float32) - return torch.as_tensor(lidar_npy) + frame_npy = frame.loc[:, columns].to_numpy().astype(np.float32) + return torch.as_tensor(frame_npy) def frame_to_SE3(frame: pd.DataFrame) -> Se3: diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_dataloader.py index f3b18497..a9bd50ed 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -2,6 +2,7 @@ from pathlib import Path +from kornia.geometry.linalg import transform_points from tqdm import tqdm from av2.torch.dataloaders.detection import DetectionDataloader @@ -17,7 +18,8 @@ def main() -> None: dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) for sweep in tqdm(dataloader): - print(sweep.lidar.as_tensor()) + city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() + lidar_xyz_city = transform_points(city_SE3_ego_4x4, sweep.lidar_xyzi[:, :3]) if __name__ == "__main__": From e6d1d78ac7d12673d56f0578a8d0e65a926a87d2 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 17:57:47 -0700 Subject: [PATCH 077/117] Docstring improvements. --- src/av2/torch/dataloaders/utils.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 46c1b6ea..4cc7825f 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -43,17 +43,11 @@ class Cuboids: _frame: pd.DataFrame - @cached_property - def categories(self) -> List[str]: - """Return the category names.""" - category_names: List[str] = self._frame["category"].to_list() - return category_names - @cached_property def as_tensor(self) -> Tensor: """Return cuboids as a (N,7) tensor. - Parameterization (7,): + Cuboid parameterization: tx_m: Translation in the x-axis in meters. ty_m: Translation in the y-axis in meters. tz_m: Translation in the z-axis in meters. @@ -63,7 +57,7 @@ def as_tensor(self) -> Tensor: yaw_radians: Counter-clock rotation measured from the x-axis. Returns: - (N,7) Cuboids parameterized as (tx_m,ty_m,tz_m,length_m,width_m,height_m,yaw_radians). + (N,7) Center-based (in meters) cuboid parameterization with extents + yaw (in radians). """ cuboids_qwxyz = frame_to_tensor(self._frame, list(DEFAULT_ANNOTATIONS_TENSOR_FIELDS)) quat_wxyz = cuboids_qwxyz[:, 6:10] @@ -71,6 +65,12 @@ def as_tensor(self) -> Tensor: _, _, yaw = euler_from_quaternion(w, x, y, z) return torch.concat([cuboids_qwxyz[:, :6], yaw[:, None]], dim=-1) + @cached_property + def categories(self) -> List[str]: + """Return the category names.""" + category_names: List[str] = self._frame["category"].to_list() + return category_names + @cached_property def track_uuids(self) -> List[str]: """Return the unique track identifiers.""" From bf1ef2a68994c7c516b677e6a9866130c336f92e Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 18:31:17 -0700 Subject: [PATCH 078/117] Update dataloader helpers. --- rust/src/io.rs | 6 +-- rust/src/so3.rs | 6 +-- src/av2/torch/dataloaders/utils.py | 64 ++++++++++++++++++------------ 3 files changed, 44 insertions(+), 32 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 59a799b2..6da0a1c1 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -27,7 +27,7 @@ use std::fs::File; use std::path::PathBuf; use crate::se3::SE3; -use crate::so3::quat_to_mat; +use crate::so3::quat_to_mat3; /// Read a feather file and load into a `polars` dataframe. pub fn read_feather(path: &PathBuf, memory_mapped: bool) -> DataFrame { @@ -64,7 +64,7 @@ pub fn read_accumulate_lidar( let translation = pose_ref.slice(s![0, ..3]).as_standard_layout().to_owned(); let quat_wxyz = pose_ref.slice(s![0, 3..]).as_standard_layout().to_owned(); - let rotation = quat_to_mat(&quat_wxyz.view()); + let rotation = quat_to_mat3(&quat_wxyz.view()); let city_se3_ego = SE3 { rotation, translation, @@ -100,7 +100,7 @@ pub fn read_accumulate_lidar( let translation_i = pose_i.slice(s![0, ..3]).as_standard_layout().to_owned(); let quat_wxyz = pose_i.slice(s![0, 3..]).as_standard_layout().to_owned(); - let rotation_i = quat_to_mat(&quat_wxyz.view()); + let rotation_i = quat_to_mat3(&quat_wxyz.view()); let city_se3_ego_i = SE3 { rotation: rotation_i, translation: translation_i, diff --git a/rust/src/so3.rs b/rust/src/so3.rs index a7615d91..b964578d 100644 --- a/rust/src/so3.rs +++ b/rust/src/so3.rs @@ -1,11 +1,11 @@ -//! # SO3 +//! # SO(3) //! //! Special Orthogonal Group 3 (SO(3)). use ndarray::{Array2, ArrayView1}; -/// Convert a quaternion in scalar-first format to a rotation matrix. -pub fn quat_to_mat(quat_wxyz: &ArrayView1) -> Array2 { +/// Convert a quaternion in scalar-first format to a 3x3 rotation matrix. +pub fn quat_to_mat3(quat_wxyz: &ArrayView1) -> Array2 { let w = quat_wxyz[0]; let x = quat_wxyz[1]; let y = quat_wxyz[2]; diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 4cc7825f..0a64079a 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -3,6 +3,7 @@ from __future__ import annotations from dataclasses import dataclass +from enum import Enum from functools import cached_property from typing import Final, List, Optional, Tuple @@ -16,7 +17,8 @@ import av2._r as rust -DEFAULT_ANNOTATIONS_TENSOR_FIELDS: Final = ( +# Cuboids represented as (x,y,z) in meters, (l,w,h) in meters, and theta (in radians). +CUBOID_XYZLWHT_COLUMN_NAMES: Final = ( "tx_m", "ty_m", "tz_m", @@ -33,9 +35,18 @@ TRANSLATION_FIELDS: Final = ("tx_m", "ty_m", "tz_m") +class CuboidMode(str, Enum): + """Cuboid parameterization modes.""" + + # (x,y,z) translation (meters), + # (l,w,h) extents (meters), + # (t,) theta counter-clockwise rotation from the x-axis (in radians). + XYZLWHT = "XYZLWHT" + + @dataclass(frozen=True) class Cuboids: - """Object containing metadata for cuboids. + """Cuboid representation for objects in the scene. Args: _frame: Dataframe containing the annotations and their attributes. @@ -44,30 +55,31 @@ class Cuboids: _frame: pd.DataFrame @cached_property - def as_tensor(self) -> Tensor: - """Return cuboids as a (N,7) tensor. - - Cuboid parameterization: - tx_m: Translation in the x-axis in meters. - ty_m: Translation in the y-axis in meters. - tz_m: Translation in the z-axis in meters. - length_m: Length in meters. - width_m: Width in meters. - height_m: Height in meters. - yaw_radians: Counter-clock rotation measured from the x-axis. + def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWHT) -> Tensor: + """Return object cuboids as an (N,K) tensor. + + Notation: + N: Number of objects. + K: Length of the cuboid mode parameterization. + + Args: + cuboid_mode: Cuboid parameterization mode. Defaults to (N,7) tensor. Returns: - (N,7) Center-based (in meters) cuboid parameterization with extents + yaw (in radians). + (N,K) tensor of cuboids with the specified cuboid_mode parameterization. """ - cuboids_qwxyz = frame_to_tensor(self._frame, list(DEFAULT_ANNOTATIONS_TENSOR_FIELDS)) - quat_wxyz = cuboids_qwxyz[:, 6:10] - w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] - _, _, yaw = euler_from_quaternion(w, x, y, z) - return torch.concat([cuboids_qwxyz[:, :6], yaw[:, None]], dim=-1) + if cuboid_mode == CuboidMode.XYZLWHT: + cuboids_qwxyz = tensor_from_frame(self._frame, list(CUBOID_XYZLWHT_COLUMN_NAMES)) + quat_wxyz = cuboids_qwxyz[:, 6:10] + w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] + _, _, yaw = euler_from_quaternion(w, x, y, z) + return torch.concat([cuboids_qwxyz[:, :6], yaw[:, None]], dim=-1) + else: + raise NotImplementedError("{orientation_mode} orientation mode is not implemented.") @cached_property - def categories(self) -> List[str]: - """Return the category names.""" + def category_names(self) -> List[str]: + """Return the object category names.""" category_names: List[str] = self._frame["category"].to_list() return category_names @@ -108,12 +120,12 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: Sweep object. """ cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) - city_SE3_ego = frame_to_SE3(frame=sweep.city_pose.to_pandas()) - lidar_xyzi = frame_to_tensor(sweep.lidar.to_pandas(), list(DEFAULT_LIDAR_TENSOR_FIELDS)) + city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) + lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(DEFAULT_LIDAR_TENSOR_FIELDS)) return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) -def frame_to_tensor(frame: pd.DataFrame, columns: List[str]) -> Tensor: +def tensor_from_frame(frame: pd.DataFrame, columns: List[str]) -> Tensor: """Build lidar `torch` tensor from `pandas` dataframe. Notation: @@ -122,7 +134,7 @@ def frame_to_tensor(frame: pd.DataFrame, columns: List[str]) -> Tensor: Args: frame: (N,K) Pandas DataFrame containing N rows with K columns. - fields: List of DataFrame columns. + columns: List of DataFrame columns. Returns: (N,K) tensor containing the frame data. @@ -131,7 +143,7 @@ def frame_to_tensor(frame: pd.DataFrame, columns: List[str]) -> Tensor: return torch.as_tensor(frame_npy) -def frame_to_SE3(frame: pd.DataFrame) -> Se3: +def SE3_from_frame(frame: pd.DataFrame) -> Se3: """Build SE(3) object from `pandas` DataFrame. Notation: From 708caf67f6487502cf0c19707bce5e57e6731c2f Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 18:40:58 -0700 Subject: [PATCH 079/117] Update dataloader helpers. --- src/av2/torch/dataloaders/utils.py | 21 ++++++++++----------- 1 file changed, 10 insertions(+), 11 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 0a64079a..36857e5b 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -18,7 +18,7 @@ import av2._r as rust # Cuboids represented as (x,y,z) in meters, (l,w,h) in meters, and theta (in radians). -CUBOID_XYZLWHT_COLUMN_NAMES: Final = ( +XYZLWH_QWXYZ_COLUMN_NAMES: Final = ( "tx_m", "ty_m", "tz_m", @@ -38,10 +38,8 @@ class CuboidMode(str, Enum): """Cuboid parameterization modes.""" - # (x,y,z) translation (meters), - # (l,w,h) extents (meters), - # (t,) theta counter-clockwise rotation from the x-axis (in radians). - XYZLWHT = "XYZLWHT" + XYZLWH_YAW = "XYZLWH_YAW" # 1-DOF orientation. + XYZLWH_QWXYZ = "XYZLWH_QWXYZ" # 3-DOF orientation. @dataclass(frozen=True) @@ -54,8 +52,7 @@ class Cuboids: _frame: pd.DataFrame - @cached_property - def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWHT) -> Tensor: + def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: """Return object cuboids as an (N,K) tensor. Notation: @@ -68,12 +65,14 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWHT) -> Tensor: Returns: (N,K) tensor of cuboids with the specified cuboid_mode parameterization. """ - if cuboid_mode == CuboidMode.XYZLWHT: - cuboids_qwxyz = tensor_from_frame(self._frame, list(CUBOID_XYZLWHT_COLUMN_NAMES)) - quat_wxyz = cuboids_qwxyz[:, 6:10] + xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMN_NAMES)) + if cuboid_mode == CuboidMode.XYZLWH_YAW: + quat_wxyz = xyzlwh_qwxyz[:, 6:10] w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] _, _, yaw = euler_from_quaternion(w, x, y, z) - return torch.concat([cuboids_qwxyz[:, :6], yaw[:, None]], dim=-1) + return torch.concat([xyzlwh_qwxyz[:, :6], yaw[:, None]], dim=-1) + elif cuboid_mode == CuboidMode.XYZLWH_QWXYZ: + return xyzlwh_qwxyz else: raise NotImplementedError("{orientation_mode} orientation mode is not implemented.") From b5ab938a4d69e90ad7de8580fb8af8b4a075bd65 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 18:43:43 -0700 Subject: [PATCH 080/117] Minor updates on cuboids. --- src/av2/torch/dataloaders/utils.py | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 36857e5b..71d48b77 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -15,7 +15,7 @@ from kornia.geometry.quaternion import Quaternion from torch import Tensor -import av2._r as rust +import av2._r as rust # Rust extension. # Cuboids represented as (x,y,z) in meters, (l,w,h) in meters, and theta (in radians). XYZLWH_QWXYZ_COLUMN_NAMES: Final = ( @@ -52,6 +52,18 @@ class Cuboids: _frame: pd.DataFrame + @cached_property + def category(self) -> List[str]: + """Return the object category names.""" + category_names: List[str] = self._frame["category"].to_list() + return category_names + + @cached_property + def track_uuid(self) -> List[str]: + """Return the unique track identifiers.""" + category_names: List[str] = self._frame["track_uuid"].to_list() + return category_names + def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: """Return object cuboids as an (N,K) tensor. @@ -76,18 +88,6 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: else: raise NotImplementedError("{orientation_mode} orientation mode is not implemented.") - @cached_property - def category_names(self) -> List[str]: - """Return the object category names.""" - category_names: List[str] = self._frame["category"].to_list() - return category_names - - @cached_property - def track_uuids(self) -> List[str]: - """Return the unique track identifiers.""" - category_names: List[str] = self._frame["track_uuid"].to_list() - return category_names - @dataclass(frozen=True) class Sweep: From 65483d5b8009fc7c4551593ce1870727af9a9445 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sat, 18 Mar 2023 18:57:56 -0700 Subject: [PATCH 081/117] Update detection dataloader + rust nits. --- rust/src/constants.rs | 4 ++-- rust/src/dataloader.rs | 6 +++--- rust/src/io.rs | 5 +++-- tutorials/detection_dataloader.py | 31 +++++++++++++++++++++++-------- 4 files changed, 31 insertions(+), 15 deletions(-) diff --git a/rust/src/constants.rs b/rust/src/constants.rs index 98fa980f..3ce19eb1 100644 --- a/rust/src/constants.rs +++ b/rust/src/constants.rs @@ -4,7 +4,7 @@ /// Annotation dataframe columns. /// Found in `annotations.feather`. -pub const ANNOTATION_COLUMNS: [&str; 13] = [ +pub const ANNOTATION_COLUMN_NAMES: [&str; 13] = [ "tx_m", "ty_m", "tz_m", @@ -22,7 +22,7 @@ pub const ANNOTATION_COLUMNS: [&str; 13] = [ /// Pose dataframe columns. /// Found in `city_SE3_egovehicle`. -pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; +pub const POSE_COLUMN_NAMES: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; /// Unknown map file name for use if the map doesn't exist. pub const DEFAULT_MAP_FILE_NAME: &str = "log_map_archive___DEFAULT_city_00000.json"; diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index 4adb2214..a6e4188c 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -2,7 +2,7 @@ //! //! Dataloader for loading the sensor dataset. -use constants::{ANNOTATION_COLUMNS, POSE_COLUMNS}; +use constants::{ANNOTATION_COLUMN_NAMES, POSE_COLUMN_NAMES}; use io::{read_accumulate_lidar, read_timestamped_feather}; use itertools::{multiunzip, Itertools}; use path::{extract_file_stem, walk_dir}; @@ -159,7 +159,7 @@ impl Dataloader { PyDataFrame( read_timestamped_feather( &self.city_pose_path(log_id), - &POSE_COLUMNS.to_vec(), + &POSE_COLUMN_NAMES.to_vec(), ×tamp_ns, self.memory_mapped, ) @@ -188,7 +188,7 @@ impl Dataloader { PyDataFrame( read_timestamped_feather( &self.annotations_path(log_id), - &ANNOTATION_COLUMNS.to_vec(), + &ANNOTATION_COLUMN_NAMES.to_vec(), ×tamp_ns, self.memory_mapped, ) diff --git a/rust/src/io.rs b/rust/src/io.rs index 6da0a1c1..1294574d 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -26,6 +26,7 @@ use rayon::prelude::ParallelIterator; use std::fs::File; use std::path::PathBuf; +use crate::constants::POSE_COLUMN_NAMES; use crate::se3::SE3; use crate::so3::quat_to_mat3; @@ -58,7 +59,7 @@ pub fn read_accumulate_lidar( let pose_ref = dataframe_to_nd_and_filter( &poses, - cols(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]), + cols(POSE_COLUMN_NAMES), col("timestamp_ns").eq(timestamp_ns), ); @@ -94,7 +95,7 @@ pub fn read_accumulate_lidar( if timestamp_ns_i != timestamp_ns { let pose_i = dataframe_to_nd_and_filter( &poses, - cols(["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]), + cols(POSE_COLUMN_NAMES), col("timestamp_ns").eq(timestamp_ns_i), ); diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_dataloader.py index a9bd50ed..dc0ed3a7 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -8,18 +8,33 @@ from av2.torch.dataloaders.detection import DetectionDataloader -def main() -> None: - """Iterate over the dataloader.""" - # Dataset should live at ~/data/datasets/{dataset_name}/{split_name} - root_dir = Path.home() / "data" / "datasets" - dataset_name = "av2" - split_name = "val" - num_accumulated_sweeps = 1 +def main( + root_dir: Path = Path.home() / "data" / "datasets", + dataset_name: str = "av2", + split_name: str = "val", + num_accumulated_sweeps: int = 1, +) -> None: + """Iterate over the detection dataloader. + + Dataset should live at ~/data/datasets/{dataset_name}/{split_name}. + + Args: + root_dir: Root directory to the datasets. + dataset_name: Name of the dataset (e.g., "av2"). + split_name: Name of the split (e.g., "val"). + num_accumulated_sweeps: Number of sweeps to accumulate. + """ dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) for sweep in tqdm(dataloader): + # 4x4 matrix representing the SE(3) transformation to city from ego-vehicle coordinates. city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() - lidar_xyz_city = transform_points(city_SE3_ego_4x4, sweep.lidar_xyzi[:, :3]) + + # Lidar (x,y,z) in meters and intensity (i). + lidar_xyzi_ego = sweep.lidar_xyzi[:, :3] + + # Transform the points to city coordinates. + lidar_xyz_city = transform_points(city_SE3_ego_4x4, lidar_xyzi_ego[:, :3]) if __name__ == "__main__": From cb8bcd865b9a086bea503ef4a832aa13e4e81fd6 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 09:06:05 -0700 Subject: [PATCH 082/117] Fix lint. --- src/av2/evaluation/detection/eval.py | 1 - src/av2/torch/dataloaders/utils.py | 6 ++++-- tutorials/detection_dataloader.py | 6 ++++-- 3 files changed, 8 insertions(+), 5 deletions(-) diff --git a/src/av2/evaluation/detection/eval.py b/src/av2/evaluation/detection/eval.py index 66f334a8..54c3473a 100644 --- a/src/av2/evaluation/detection/eval.py +++ b/src/av2/evaluation/detection/eval.py @@ -111,7 +111,6 @@ def evaluate( K refers to the number of evaluation metrics. Raises: - RuntimeError: If accumulation fails. ValueError: If ROI pruning is enabled but a dataset directory is not specified. """ if cfg.eval_only_roi_instances and cfg.dataset_dir is None: diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 71d48b77..2258f6da 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -75,7 +75,9 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: cuboid_mode: Cuboid parameterization mode. Defaults to (N,7) tensor. Returns: - (N,K) tensor of cuboids with the specified cuboid_mode parameterization. + (N,K) Tensor of cuboids with the specified cuboid_mode parameterization. + Raises: + NotImplementedError: Raised if the cuboid mode is not supported. """ xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMN_NAMES)) if cuboid_mode == CuboidMode.XYZLWH_YAW: @@ -86,7 +88,7 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: elif cuboid_mode == CuboidMode.XYZLWH_QWXYZ: return xyzlwh_qwxyz else: - raise NotImplementedError("{orientation_mode} orientation mode is not implemented.") + raise NotImplementedError(f"{cuboid_mode} orientation mode is not implemented.") @dataclass(frozen=True) diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_dataloader.py index dc0ed3a7..a774073a 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -1,15 +1,18 @@ """Example of rust-backed, torch dataloader.""" from pathlib import Path +from typing import Final from kornia.geometry.linalg import transform_points from tqdm import tqdm from av2.torch.dataloaders.detection import DetectionDataloader +HOME_DIR: Final = Path.home() + def main( - root_dir: Path = Path.home() / "data" / "datasets", + root_dir: Path = HOME_DIR / "data" / "datasets", dataset_name: str = "av2", split_name: str = "val", num_accumulated_sweeps: int = 1, @@ -24,7 +27,6 @@ def main( split_name: Name of the split (e.g., "val"). num_accumulated_sweeps: Number of sweeps to accumulate. """ - dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) for sweep in tqdm(dataloader): # 4x4 matrix representing the SE(3) transformation to city from ego-vehicle coordinates. From 4b836c99df65c9fb02828abc3857a7972784d038 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 09:14:19 -0700 Subject: [PATCH 083/117] Fix typing. --- src/av2/evaluation/detection/eval.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/evaluation/detection/eval.py b/src/av2/evaluation/detection/eval.py index 54c3473a..ee0391d9 100644 --- a/src/av2/evaluation/detection/eval.py +++ b/src/av2/evaluation/detection/eval.py @@ -167,7 +167,7 @@ def evaluate( logger.info("Starting evaluation ...") with mp.get_context("spawn").Pool(processes=n_jobs) as p: - outputs: Optional[List[Tuple[NDArrayFloat, NDArrayFloat]]] = p.starmap(accumulate, args_list) + outputs: List[Tuple[NDArrayFloat, NDArrayFloat]] = p.starmap(accumulate, args_list) dts_list, gts_list = zip(*outputs) From 3d0ff7c907dd0e64910bdd407773df92e0501bb0 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 09:24:35 -0700 Subject: [PATCH 084/117] Fix docstrings. --- src/av2/torch/dataloaders/utils.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index 2258f6da..ea5843e9 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -17,7 +17,6 @@ import av2._r as rust # Rust extension. -# Cuboids represented as (x,y,z) in meters, (l,w,h) in meters, and theta (in radians). XYZLWH_QWXYZ_COLUMN_NAMES: Final = ( "tx_m", "ty_m", @@ -30,9 +29,9 @@ "qy", "qz", ) -DEFAULT_LIDAR_TENSOR_FIELDS: Final = ("x", "y", "z", "intensity") -QUAT_WXYZ_FIELDS: Final = ("qw", "qx", "qy", "qz") -TRANSLATION_FIELDS: Final = ("tx_m", "ty_m", "tz_m") +LIDAR_COLUMN_NAMES: Final = ("x", "y", "z", "intensity") +QWXYZ_COLUMN_NAMES: Final = ("qw", "qx", "qy", "qz") +TRANSLATION_COLUMN_NAMES: Final = ("tx_m", "ty_m", "tz_m") class CuboidMode(str, Enum): @@ -76,6 +75,7 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: Returns: (N,K) Tensor of cuboids with the specified cuboid_mode parameterization. + Raises: NotImplementedError: Raised if the cuboid mode is not supported. """ @@ -122,7 +122,7 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: """ cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) - lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(DEFAULT_LIDAR_TENSOR_FIELDS)) + lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(LIDAR_COLUMN_NAMES)) return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) @@ -154,13 +154,13 @@ def SE3_from_frame(frame: pd.DataFrame) -> Se3: frame: (N,4) Pandas DataFrame containing quaternion coefficients. Returns: - Kornia Se3 object representing a (N,4,4) tensor of homogeneous transformations. + SE(3) object representing a (N,4,4) tensor of homogeneous transformations. """ - quaternion_npy = frame.loc[0, list(QUAT_WXYZ_FIELDS)].to_numpy().astype(float) + quaternion_npy = frame.loc[0, list(QWXYZ_COLUMN_NAMES)].to_numpy().astype(float) quat_wxyz = Quaternion(torch.as_tensor(quaternion_npy, dtype=torch.float32)) rotation = So3(quat_wxyz) - translation_npy = frame.loc[0, list(TRANSLATION_FIELDS)].to_numpy().astype(np.float32) + translation_npy = frame.loc[0, list(TRANSLATION_COLUMN_NAMES)].to_numpy().astype(np.float32) translation = torch.as_tensor(translation_npy, dtype=torch.float32) dst_SE3_src = Se3(rotation[None], translation[None]) return dst_SE3_src From 2c5bbe1e21cc8d058d481f3e6302c40bb683f00c Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 09:27:23 -0700 Subject: [PATCH 085/117] Update column naming. --- src/av2/torch/dataloaders/utils.py | 27 +++++++++++++-------------- 1 file changed, 13 insertions(+), 14 deletions(-) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py index ea5843e9..38cdec7d 100644 --- a/src/av2/torch/dataloaders/utils.py +++ b/src/av2/torch/dataloaders/utils.py @@ -13,11 +13,10 @@ from kornia.geometry.conversions import euler_from_quaternion from kornia.geometry.liegroup import Se3, So3 from kornia.geometry.quaternion import Quaternion -from torch import Tensor import av2._r as rust # Rust extension. -XYZLWH_QWXYZ_COLUMN_NAMES: Final = ( +XYZLWH_QWXYZ_COLUMNS: Final = ( "tx_m", "ty_m", "tz_m", @@ -29,9 +28,9 @@ "qy", "qz", ) -LIDAR_COLUMN_NAMES: Final = ("x", "y", "z", "intensity") -QWXYZ_COLUMN_NAMES: Final = ("qw", "qx", "qy", "qz") -TRANSLATION_COLUMN_NAMES: Final = ("tx_m", "ty_m", "tz_m") +LIDAR_COLUMNS: Final = ("x", "y", "z", "intensity") +QWXYZ_COLUMNS: Final = ("qw", "qx", "qy", "qz") +TRANSLATION_COLUMNS: Final = ("tx_m", "ty_m", "tz_m") class CuboidMode(str, Enum): @@ -63,7 +62,7 @@ def track_uuid(self) -> List[str]: category_names: List[str] = self._frame["track_uuid"].to_list() return category_names - def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: + def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> torch.Tensor: """Return object cuboids as an (N,K) tensor. Notation: @@ -74,12 +73,12 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> Tensor: cuboid_mode: Cuboid parameterization mode. Defaults to (N,7) tensor. Returns: - (N,K) Tensor of cuboids with the specified cuboid_mode parameterization. + (N,K) torch.Tensor of cuboids with the specified cuboid_mode parameterization. Raises: NotImplementedError: Raised if the cuboid mode is not supported. """ - xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMN_NAMES)) + xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMNS)) if cuboid_mode == CuboidMode.XYZLWH_YAW: quat_wxyz = xyzlwh_qwxyz[:, 6:10] w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] @@ -100,13 +99,13 @@ class Sweep: Args: city_SE3_ego: Rigid transformation describing the city pose of the ego-vehicle. - lidar_xyzi: (N,4) Tensor of lidar points containing (x,y,z) in meters and intensity (i). + lidar_xyzi: (N,4) torch.Tensor of lidar points containing (x,y,z) in meters and intensity (i). sweep_uuid: Log id and nanosecond timestamp (unique identifier). cuboids: Cuboids representing objects in the scene. """ city_SE3_ego: Se3 - lidar_xyzi: Tensor + lidar_xyzi: torch.Tensor sweep_uuid: Tuple[str, int] cuboids: Optional[Cuboids] @@ -122,11 +121,11 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: """ cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) - lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(LIDAR_COLUMN_NAMES)) + lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(LIDAR_COLUMNS)) return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) -def tensor_from_frame(frame: pd.DataFrame, columns: List[str]) -> Tensor: +def tensor_from_frame(frame: pd.DataFrame, columns: List[str]) -> torch.Tensor: """Build lidar `torch` tensor from `pandas` dataframe. Notation: @@ -156,11 +155,11 @@ def SE3_from_frame(frame: pd.DataFrame) -> Se3: Returns: SE(3) object representing a (N,4,4) tensor of homogeneous transformations. """ - quaternion_npy = frame.loc[0, list(QWXYZ_COLUMN_NAMES)].to_numpy().astype(float) + quaternion_npy = frame.loc[0, list(QWXYZ_COLUMNS)].to_numpy().astype(float) quat_wxyz = Quaternion(torch.as_tensor(quaternion_npy, dtype=torch.float32)) rotation = So3(quat_wxyz) - translation_npy = frame.loc[0, list(TRANSLATION_COLUMN_NAMES)].to_numpy().astype(np.float32) + translation_npy = frame.loc[0, list(TRANSLATION_COLUMNS)].to_numpy().astype(np.float32) translation = torch.as_tensor(translation_npy, dtype=torch.float32) dst_SE3_src = Se3(rotation[None], translation[None]) return dst_SE3_src From 3f64f01ff77e39025a3b24d967f180cda9929a6f Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 09:32:26 -0700 Subject: [PATCH 086/117] Add additional examples. --- tutorials/detection_dataloader.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_dataloader.py index a774073a..74169a7f 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -7,6 +7,7 @@ from tqdm import tqdm from av2.torch.dataloaders.detection import DetectionDataloader +from av2.torch.dataloaders.utils import CuboidMode HOME_DIR: Final = Path.home() @@ -38,6 +39,15 @@ def main( # Transform the points to city coordinates. lidar_xyz_city = transform_points(city_SE3_ego_4x4, lidar_xyzi_ego[:, :3]) + # Cuboids might not be available (e.g., using the "test" split). + if sweep.cuboids is not None: + # Annotations in (x,y,z,l,w,h,yaw) format. + cuboids = sweep.cuboids.as_tensor() + + # Annotations in (x,y,z,l,w,h,qw,qx,qy,qz) format. + # Full 3-DOF rotation. + cuboids_qwxyz = sweep.cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ) + if __name__ == "__main__": main() From 87403743b5146f49b010e1701c7818577fb1b16e Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 09:36:16 -0700 Subject: [PATCH 087/117] Add additional examples. --- tutorials/detection_dataloader.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_dataloader.py index 74169a7f..ba9c16cd 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_dataloader.py @@ -1,5 +1,6 @@ """Example of rust-backed, torch dataloader.""" +import logging from pathlib import Path from typing import Final @@ -9,6 +10,8 @@ from av2.torch.dataloaders.detection import DetectionDataloader from av2.torch.dataloaders.utils import CuboidMode +logger = logging.getLogger(__name__) + HOME_DIR: Final = Path.home() @@ -17,6 +20,7 @@ def main( dataset_name: str = "av2", split_name: str = "val", num_accumulated_sweeps: int = 1, + max_iterations: int = 1000, ) -> None: """Iterate over the detection dataloader. @@ -27,9 +31,11 @@ def main( dataset_name: Name of the dataset (e.g., "av2"). split_name: Name of the split (e.g., "val"). num_accumulated_sweeps: Number of sweeps to accumulate. + max_iterations: Maximum number of iterations for the dataloader example. """ + logger.info("Starting detection dataloader example ...") dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) - for sweep in tqdm(dataloader): + for i, sweep in enumerate(tqdm(dataloader)): # 4x4 matrix representing the SE(3) transformation to city from ego-vehicle coordinates. city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() @@ -48,6 +54,12 @@ def main( # Full 3-DOF rotation. cuboids_qwxyz = sweep.cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ) + if i >= max_iterations: + logger.info(f"Reached max iterations of {max_iterations}!") + break + + logger.info("Example complete!") + if __name__ == "__main__": main() From ee51df8f846d6d7375417bd56100082c1ca788bf Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 10:32:30 -0700 Subject: [PATCH 088/117] Update torch structures. --- src/av2/torch/__init__.py | 9 +- src/av2/torch/dataloaders/detection.py | 2 +- src/av2/torch/dataloaders/utils.py | 165 ------------------------- src/av2/torch/structures/__init__.py | 1 + src/av2/torch/structures/cuboids.py | 71 +++++++++++ src/av2/torch/structures/sweep.py | 50 ++++++++ src/av2/torch/structures/utils.py | 53 ++++++++ 7 files changed, 184 insertions(+), 167 deletions(-) delete mode 100644 src/av2/torch/dataloaders/utils.py create mode 100644 src/av2/torch/structures/__init__.py create mode 100644 src/av2/torch/structures/cuboids.py create mode 100644 src/av2/torch/structures/sweep.py create mode 100644 src/av2/torch/structures/utils.py diff --git a/src/av2/torch/__init__.py b/src/av2/torch/__init__.py index 44b45e6b..b1745725 100644 --- a/src/av2/torch/__init__.py +++ b/src/av2/torch/__init__.py @@ -1 +1,8 @@ -"""AV2 Pytorch api.""" +"""Argoverse 2 Pytorch API.""" + +from typing import Final + +LIDAR_COLUMNS: Final = ("x", "y", "z", "intensity") +QWXYZ_COLUMNS: Final = ("qw", "qx", "qy", "qz") +TRANSLATION_COLUMNS: Final = ("tx_m", "ty_m", "tz_m") +XYZLWH_QWXYZ_COLUMNS: Final = TRANSLATION_COLUMNS + ("length_m", "width_m", "height_m") + QWXYZ_COLUMNS diff --git a/src/av2/torch/dataloaders/detection.py b/src/av2/torch/dataloaders/detection.py index a7712788..6e97cd3c 100644 --- a/src/av2/torch/dataloaders/detection.py +++ b/src/av2/torch/dataloaders/detection.py @@ -10,7 +10,7 @@ import av2._r as rust from av2.utils.typing import PathType -from .utils import Sweep +from ..structures.sweep import Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) diff --git a/src/av2/torch/dataloaders/utils.py b/src/av2/torch/dataloaders/utils.py deleted file mode 100644 index 38cdec7d..00000000 --- a/src/av2/torch/dataloaders/utils.py +++ /dev/null @@ -1,165 +0,0 @@ -"""Pytorch dataloader utilities.""" - -from __future__ import annotations - -from dataclasses import dataclass -from enum import Enum -from functools import cached_property -from typing import Final, List, Optional, Tuple - -import numpy as np -import pandas as pd -import torch -from kornia.geometry.conversions import euler_from_quaternion -from kornia.geometry.liegroup import Se3, So3 -from kornia.geometry.quaternion import Quaternion - -import av2._r as rust # Rust extension. - -XYZLWH_QWXYZ_COLUMNS: Final = ( - "tx_m", - "ty_m", - "tz_m", - "length_m", - "width_m", - "height_m", - "qw", - "qx", - "qy", - "qz", -) -LIDAR_COLUMNS: Final = ("x", "y", "z", "intensity") -QWXYZ_COLUMNS: Final = ("qw", "qx", "qy", "qz") -TRANSLATION_COLUMNS: Final = ("tx_m", "ty_m", "tz_m") - - -class CuboidMode(str, Enum): - """Cuboid parameterization modes.""" - - XYZLWH_YAW = "XYZLWH_YAW" # 1-DOF orientation. - XYZLWH_QWXYZ = "XYZLWH_QWXYZ" # 3-DOF orientation. - - -@dataclass(frozen=True) -class Cuboids: - """Cuboid representation for objects in the scene. - - Args: - _frame: Dataframe containing the annotations and their attributes. - """ - - _frame: pd.DataFrame - - @cached_property - def category(self) -> List[str]: - """Return the object category names.""" - category_names: List[str] = self._frame["category"].to_list() - return category_names - - @cached_property - def track_uuid(self) -> List[str]: - """Return the unique track identifiers.""" - category_names: List[str] = self._frame["track_uuid"].to_list() - return category_names - - def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> torch.Tensor: - """Return object cuboids as an (N,K) tensor. - - Notation: - N: Number of objects. - K: Length of the cuboid mode parameterization. - - Args: - cuboid_mode: Cuboid parameterization mode. Defaults to (N,7) tensor. - - Returns: - (N,K) torch.Tensor of cuboids with the specified cuboid_mode parameterization. - - Raises: - NotImplementedError: Raised if the cuboid mode is not supported. - """ - xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMNS)) - if cuboid_mode == CuboidMode.XYZLWH_YAW: - quat_wxyz = xyzlwh_qwxyz[:, 6:10] - w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] - _, _, yaw = euler_from_quaternion(w, x, y, z) - return torch.concat([xyzlwh_qwxyz[:, :6], yaw[:, None]], dim=-1) - elif cuboid_mode == CuboidMode.XYZLWH_QWXYZ: - return xyzlwh_qwxyz - else: - raise NotImplementedError(f"{cuboid_mode} orientation mode is not implemented.") - - -@dataclass(frozen=True) -class Sweep: - """Stores the annotations and lidar for one sweep. - - Notation: - N: Number of lidar points. - - Args: - city_SE3_ego: Rigid transformation describing the city pose of the ego-vehicle. - lidar_xyzi: (N,4) torch.Tensor of lidar points containing (x,y,z) in meters and intensity (i). - sweep_uuid: Log id and nanosecond timestamp (unique identifier). - cuboids: Cuboids representing objects in the scene. - """ - - city_SE3_ego: Se3 - lidar_xyzi: torch.Tensor - sweep_uuid: Tuple[str, int] - cuboids: Optional[Cuboids] - - @classmethod - def from_rust(cls, sweep: rust.Sweep) -> Sweep: - """Build a sweep from the Rust backend. - - Args: - sweep: Sweep object from the Rust backend dataloader. - - Returns: - Sweep object. - """ - cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) - city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) - lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(LIDAR_COLUMNS)) - return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) - - -def tensor_from_frame(frame: pd.DataFrame, columns: List[str]) -> torch.Tensor: - """Build lidar `torch` tensor from `pandas` dataframe. - - Notation: - N: Number of rows. - K: Number of columns. - - Args: - frame: (N,K) Pandas DataFrame containing N rows with K columns. - columns: List of DataFrame columns. - - Returns: - (N,K) tensor containing the frame data. - """ - frame_npy = frame.loc[:, columns].to_numpy().astype(np.float32) - return torch.as_tensor(frame_npy) - - -def SE3_from_frame(frame: pd.DataFrame) -> Se3: - """Build SE(3) object from `pandas` DataFrame. - - Notation: - N: Number of rigid transformations. - - Args: - frame: (N,4) Pandas DataFrame containing quaternion coefficients. - - Returns: - SE(3) object representing a (N,4,4) tensor of homogeneous transformations. - """ - quaternion_npy = frame.loc[0, list(QWXYZ_COLUMNS)].to_numpy().astype(float) - quat_wxyz = Quaternion(torch.as_tensor(quaternion_npy, dtype=torch.float32)) - rotation = So3(quat_wxyz) - - translation_npy = frame.loc[0, list(TRANSLATION_COLUMNS)].to_numpy().astype(np.float32) - translation = torch.as_tensor(translation_npy, dtype=torch.float32) - dst_SE3_src = Se3(rotation[None], translation[None]) - return dst_SE3_src diff --git a/src/av2/torch/structures/__init__.py b/src/av2/torch/structures/__init__.py new file mode 100644 index 00000000..30e816ab --- /dev/null +++ b/src/av2/torch/structures/__init__.py @@ -0,0 +1 @@ +"""Argoverse 2 Pytorch structures.""" diff --git a/src/av2/torch/structures/cuboids.py b/src/av2/torch/structures/cuboids.py new file mode 100644 index 00000000..355bb5d4 --- /dev/null +++ b/src/av2/torch/structures/cuboids.py @@ -0,0 +1,71 @@ +"""Pytorch dataloader utilities.""" + +from __future__ import annotations + +from dataclasses import dataclass +from enum import Enum +from functools import cached_property +from typing import List + +import pandas as pd +import torch +from kornia.geometry.conversions import euler_from_quaternion + +from .utils import tensor_from_frame + + +class CuboidMode(str, Enum): + """Cuboid parameterization modes.""" + + XYZLWH_YAW = "XYZLWH_YAW" # 1-DOF orientation. + XYZLWH_QWXYZ = "XYZLWH_QWXYZ" # 3-DOF orientation. + + +@dataclass(frozen=True) +class Cuboids: + """Cuboid representation for objects in the scene. + + Args: + _frame: Dataframe containing the annotations and their attributes. + """ + + _frame: pd.DataFrame + + @cached_property + def category(self) -> List[str]: + """Return the object category names.""" + category_names: List[str] = self._frame["category"].to_list() + return category_names + + @cached_property + def track_uuid(self) -> List[str]: + """Return the unique track identifiers.""" + category_names: List[str] = self._frame["track_uuid"].to_list() + return category_names + + def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> torch.Tensor: + """Return object cuboids as an (N,K) tensor. + + Notation: + N: Number of objects. + K: Length of the cuboid mode parameterization. + + Args: + cuboid_mode: Cuboid parameterization mode. Defaults to (N,7) tensor. + + Returns: + (N,K) torch.Tensor of cuboids with the specified cuboid_mode parameterization. + + Raises: + NotImplementedError: Raised if the cuboid mode is not supported. + """ + xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMNS)) + if cuboid_mode == CuboidMode.XYZLWH_YAW: + quat_wxyz = xyzlwh_qwxyz[:, 6:10] + w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] + _, _, yaw = euler_from_quaternion(w, x, y, z) + return torch.concat([xyzlwh_qwxyz[:, :6], yaw[:, None]], dim=-1) + elif cuboid_mode == CuboidMode.XYZLWH_QWXYZ: + return xyzlwh_qwxyz + else: + raise NotImplementedError(f"{cuboid_mode} orientation mode is not implemented.") diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py new file mode 100644 index 00000000..b2558172 --- /dev/null +++ b/src/av2/torch/structures/sweep.py @@ -0,0 +1,50 @@ +"""Pytorch sweep module.""" + +from __future__ import annotations + +from dataclasses import dataclass +from typing import Optional, Tuple + +import torch +from kornia.geometry.liegroup import Se3 + +import av2._r as rust + +from .. import LIDAR_COLUMNS +from .cuboids import Cuboids +from .utils import SE3_from_frame, tensor_from_frame + + +@dataclass(frozen=True) +class Sweep: + """Stores the annotations and lidar for one sweep. + + Notation: + N: Number of lidar points. + + Args: + city_SE3_ego: Rigid transformation describing the city pose of the ego-vehicle. + lidar_xyzi: (N,4) torch.Tensor of lidar points containing (x,y,z) in meters and intensity (i). + sweep_uuid: Log id and nanosecond timestamp (unique identifier). + cuboids: Cuboids representing objects in the scene. + """ + + city_SE3_ego: Se3 + lidar_xyzi: torch.Tensor + sweep_uuid: Tuple[str, int] + cuboids: Optional[Cuboids] + + @classmethod + def from_rust(cls, sweep: rust.Sweep) -> Sweep: + """Build a sweep from the Rust backend. + + Args: + sweep: Sweep object from the Rust backend dataloader. + + Returns: + Sweep object. + """ + cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) + city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) + lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(LIDAR_COLUMNS)) + return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) diff --git a/src/av2/torch/structures/utils.py b/src/av2/torch/structures/utils.py new file mode 100644 index 00000000..2a08f93d --- /dev/null +++ b/src/av2/torch/structures/utils.py @@ -0,0 +1,53 @@ +"""Pytorch structure utilities.""" + +from __future__ import annotations + +from typing import List + +import numpy as np +import pandas as pd +import torch +from kornia.geometry.liegroup import Se3, So3 +from kornia.geometry.quaternion import Quaternion + +from .. import QWXYZ_COLUMNS, TRANSLATION_COLUMNS + + +def tensor_from_frame(frame: pd.DataFrame, columns: List[str]) -> torch.Tensor: + """Build lidar `torch` tensor from `pandas` dataframe. + + Notation: + N: Number of rows. + K: Number of columns. + + Args: + frame: (N,K) Pandas DataFrame containing N rows with K columns. + columns: List of DataFrame columns. + + Returns: + (N,K) tensor containing the frame data. + """ + frame_npy = frame.loc[:, columns].to_numpy().astype(np.float32) + return torch.as_tensor(frame_npy) + + +def SE3_from_frame(frame: pd.DataFrame) -> Se3: + """Build SE(3) object from `pandas` DataFrame. + + Notation: + N: Number of rigid transformations. + + Args: + frame: (N,4) Pandas DataFrame containing quaternion coefficients. + + Returns: + SE(3) object representing a (N,4,4) tensor of homogeneous transformations. + """ + quaternion_npy = frame.loc[0, list(QWXYZ_COLUMNS)].to_numpy().astype(float) + quat_wxyz = Quaternion(torch.as_tensor(quaternion_npy, dtype=torch.float32)) + rotation = So3(quat_wxyz) + + translation_npy = frame.loc[0, list(TRANSLATION_COLUMNS)].to_numpy().astype(np.float32) + translation = torch.as_tensor(translation_npy, dtype=torch.float32) + dst_SE3_src = Se3(rotation[None], translation[None]) + return dst_SE3_src From d2feca16b972aa579ff536ad855a5c40535a64e3 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 10:43:50 -0700 Subject: [PATCH 089/117] Update se3.rs --- rust/src/se3.rs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/rust/src/se3.rs b/rust/src/se3.rs index 0bcea089..157ed7c4 100644 --- a/rust/src/se3.rs +++ b/rust/src/se3.rs @@ -1,4 +1,4 @@ -//! # SE3 +//! # SE(3) //! //! Special Euclidean Group 3. From 688259674453d4dfd0097cef4b69ced92ba50040 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 14:38:37 -0700 Subject: [PATCH 090/117] Add unit tests. --- src/av2/torch/structures/cuboids.py | 3 +- src/av2/torch/structures/lidar.py | 34 ++++++++++++++++++++++ src/av2/torch/structures/sweep.py | 14 ++++----- tests/torch/structures/test_cuboids.py | 40 ++++++++++++++++++++++++++ tests/torch/structures/test_lidar.py | 26 +++++++++++++++++ tests/torch/structures/test_sweep.py | 34 ++++++++++++++++++++++ 6 files changed, 143 insertions(+), 8 deletions(-) create mode 100644 src/av2/torch/structures/lidar.py create mode 100644 tests/torch/structures/test_cuboids.py create mode 100644 tests/torch/structures/test_lidar.py create mode 100644 tests/torch/structures/test_sweep.py diff --git a/src/av2/torch/structures/cuboids.py b/src/av2/torch/structures/cuboids.py index 355bb5d4..e293b541 100644 --- a/src/av2/torch/structures/cuboids.py +++ b/src/av2/torch/structures/cuboids.py @@ -1,4 +1,4 @@ -"""Pytorch dataloader utilities.""" +"""Pytorch Cuboids module.""" from __future__ import annotations @@ -11,6 +11,7 @@ import torch from kornia.geometry.conversions import euler_from_quaternion +from .. import XYZLWH_QWXYZ_COLUMNS from .utils import tensor_from_frame diff --git a/src/av2/torch/structures/lidar.py b/src/av2/torch/structures/lidar.py new file mode 100644 index 00000000..26008484 --- /dev/null +++ b/src/av2/torch/structures/lidar.py @@ -0,0 +1,34 @@ +"""Pytorch Lidar Module.""" + +from __future__ import annotations + +from dataclasses import dataclass +from typing import Tuple + +import pandas as pd +import torch + +from av2.torch import LIDAR_COLUMNS +from av2.torch.structures.utils import tensor_from_frame + + +@dataclass(frozen=True) +class Lidar: + """Lidar sensor data structure. + + Args: + _frame: Dataframe containing lidar coordinates and features. + """ + + _frame: pd.DataFrame + + def as_tensor(self, columns: Tuple[str, ...] = LIDAR_COLUMNS) -> torch.Tensor: + """Return the lidar as a tensor with the specified columns. + + Args: + columns: List of ordered column names. + + Returns: + Tensor of lidar data. + """ + return tensor_from_frame(self._frame, list(columns)) diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py index b2558172..6669b468 100644 --- a/src/av2/torch/structures/sweep.py +++ b/src/av2/torch/structures/sweep.py @@ -5,14 +5,13 @@ from dataclasses import dataclass from typing import Optional, Tuple -import torch from kornia.geometry.liegroup import Se3 import av2._r as rust +from av2.torch.structures.lidar import Lidar -from .. import LIDAR_COLUMNS from .cuboids import Cuboids -from .utils import SE3_from_frame, tensor_from_frame +from .utils import SE3_from_frame @dataclass(frozen=True) @@ -21,16 +20,17 @@ class Sweep: Notation: N: Number of lidar points. + K: Number of lidar features. Args: city_SE3_ego: Rigid transformation describing the city pose of the ego-vehicle. - lidar_xyzi: (N,4) torch.Tensor of lidar points containing (x,y,z) in meters and intensity (i). + lidar: Lidar sensor data. sweep_uuid: Log id and nanosecond timestamp (unique identifier). cuboids: Cuboids representing objects in the scene. """ city_SE3_ego: Se3 - lidar_xyzi: torch.Tensor + lidar: Lidar sweep_uuid: Tuple[str, int] cuboids: Optional[Cuboids] @@ -46,5 +46,5 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: """ cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) - lidar_xyzi = tensor_from_frame(sweep.lidar.to_pandas(), list(LIDAR_COLUMNS)) - return cls(city_SE3_ego=city_SE3_ego, lidar_xyzi=lidar_xyzi, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) + lidar = Lidar(sweep.lidar.to_pandas()) + return cls(city_SE3_ego=city_SE3_ego, lidar=lidar, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py new file mode 100644 index 00000000..9f79988c --- /dev/null +++ b/tests/torch/structures/test_cuboids.py @@ -0,0 +1,40 @@ +"""Unit tests for Pytorch Cuboids module.""" + +from pathlib import Path +from typing import Final + +import numpy as np +import pandas as pd +import torch +from kornia.geometry.conversions import euler_from_quaternion + +from av2.torch import XYZLWH_QWXYZ_COLUMNS +from av2.torch.structures.cuboids import CuboidMode, Cuboids + +TEST_DATA_DIR: Final = Path(__file__).parent.parent.parent.resolve() / "test_data" +SAMPLE_LOG_DIR: Final = TEST_DATA_DIR / "sensor_dataset_logs" / "adcf7d18-0510-35b0-a2fa-b4cea13a6d76" + + +def test_build_cuboids() -> None: + """Test building the Cuboids structure.""" + annotations_path = SAMPLE_LOG_DIR / "annotations.feather" + annotations_frame = pd.read_feather(annotations_path) + cuboids_npy = annotations_frame[list(XYZLWH_QWXYZ_COLUMNS)].to_numpy().astype(np.float32) + + cuboids = Cuboids(annotations_frame) + cuboids_xyzlwht = cuboids.as_tensor() + + cuboids_xyzlwh_qwxyz = torch.as_tensor(cuboids_npy) + torch.testing.assert_close(cuboids_xyzlwht[:, :6], cuboids_xyzlwh_qwxyz[:, :6]) + + w, x, y, z = cuboids_xyzlwh_qwxyz[:, 6:10].t() + _, _, yaw = euler_from_quaternion(w, x, y, z) + torch.testing.assert_close(cuboids_xyzlwht[:, 6], yaw) + torch.testing.assert_close(cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ), cuboids_xyzlwh_qwxyz) + + +def test_build_lidar() -> None: + """Test building a lidar tensor.""" + lidar_paths = sorted((SAMPLE_LOG_DIR / "sensors" / "lidar").glob("*.feather")) + lidar_path = lidar_paths[0] + lidar_frame = pd.read_feather(lidar_path) diff --git a/tests/torch/structures/test_lidar.py b/tests/torch/structures/test_lidar.py new file mode 100644 index 00000000..967911b5 --- /dev/null +++ b/tests/torch/structures/test_lidar.py @@ -0,0 +1,26 @@ +"""Unit tests for Pytorch Lidar module.""" + +from pathlib import Path +from typing import Final + +import numpy as np +import pandas as pd +import torch + +from av2.torch import LIDAR_COLUMNS +from av2.torch.structures.lidar import Lidar + +TEST_DATA_DIR: Final = Path(__file__).parent.parent.parent.resolve() / "test_data" +SAMPLE_LOG_DIR: Final = TEST_DATA_DIR / "sensor_dataset_logs" / "adcf7d18-0510-35b0-a2fa-b4cea13a6d76" + + +def test_build_lidar() -> None: + """Test building a Lidar structure.""" + lidar_paths = sorted((SAMPLE_LOG_DIR / "sensors" / "lidar").glob("*.feather")) + lidar_path = lidar_paths[0] + frame = pd.read_feather(lidar_path) + lidar_tensor = torch.as_tensor(frame[list(LIDAR_COLUMNS)].to_numpy().astype(np.float32)) + + lidar = Lidar(frame) + torch.testing.assert_close(lidar.as_tensor(), lidar_tensor) + torch.testing.assert_close(lidar.as_tensor(columns=("y", "z",)), lidar_tensor[:, 1:3]) diff --git a/tests/torch/structures/test_sweep.py b/tests/torch/structures/test_sweep.py new file mode 100644 index 00000000..115b15ce --- /dev/null +++ b/tests/torch/structures/test_sweep.py @@ -0,0 +1,34 @@ +"""Unit tests for Pytorch Cuboids module.""" + +from pathlib import Path +from typing import Final + +import pandas as pd + +from av2.torch.structures.cuboids import Cuboids +from av2.torch.structures.lidar import Lidar +from av2.torch.structures.sweep import Sweep +from av2.torch.structures.utils import SE3_from_frame + +TEST_DATA_DIR: Final = Path(__file__).parent.parent.parent.resolve() / "test_data" +SAMPLE_LOG_DIR: Final = TEST_DATA_DIR / "sensor_dataset_logs" / "adcf7d18-0510-35b0-a2fa-b4cea13a6d76" + + +def test_build_sweep() -> None: + """Test building the Sweep structure.""" + annotations_path = SAMPLE_LOG_DIR / "annotations.feather" + annotations_frame = pd.read_feather(annotations_path) + cuboids = Cuboids(annotations_frame) + + lidar_paths = sorted((SAMPLE_LOG_DIR / "sensors" / "lidar").glob("*.feather")) + lidar_path = lidar_paths[0] + lidar_frame = pd.read_feather(lidar_path) + lidar = Lidar(lidar_frame) + + city_pose_path = SAMPLE_LOG_DIR / "city_SE3_egovehicle.feather" + city_pose_frame = pd.read_feather(city_pose_path) + city_SE3_ego = SE3_from_frame(city_pose_frame) + + sweep_uuid = annotations_path.parent.stem, int(lidar_path.stem) + sweep = Sweep(city_SE3_ego=city_SE3_ego, lidar=lidar, sweep_uuid=sweep_uuid, cuboids=cuboids) + assert sweep is not None From a6924ed70d16b823d6f291c84d446da611f45ebd Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 14:52:33 -0700 Subject: [PATCH 091/117] Add additional tests. --- rust/src/dataloader.rs | 14 +++++++------- rust/src/lib.rs | 4 ++-- src/av2/torch/dataloaders/detection.py | 12 ++++++------ .../annotations.feather | Bin 0 -> 642618 bytes .../city_SE3_egovehicle.feather | Bin 0 -> 161634 bytes ...5b0-a2fa-b4cea13a6d76___img_Sim2_city.json | 1 + ...ea13a6d76_ground_height_surface____PIT.npy | Bin 0 -> 1135548 bytes ...0-a2fa-b4cea13a6d76____PIT_city_57819.json | 1 + .../sensors/lidar/315973157959879000.feather | Bin 0 -> 1048066 bytes .../dataloaders/test_detection_dataloader.py | 18 ++++++++++++++++++ tests/torch/structures/test_lidar.py | 10 +++++++++- 11 files changed, 44 insertions(+), 16 deletions(-) create mode 100644 tests/test_data/sensor_dataset_logs/av2/sensor/val/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/annotations.feather create mode 100644 tests/test_data/sensor_dataset_logs/av2/sensor/val/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/city_SE3_egovehicle.feather create mode 100644 tests/test_data/sensor_dataset_logs/av2/sensor/val/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/adcf7d18-0510-35b0-a2fa-b4cea13a6d76___img_Sim2_city.json create mode 100644 tests/test_data/sensor_dataset_logs/av2/sensor/val/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/adcf7d18-0510-35b0-a2fa-b4cea13a6d76_ground_height_surface____PIT.npy create mode 100644 tests/test_data/sensor_dataset_logs/av2/sensor/val/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/map/log_map_archive_adcf7d18-0510-35b0-a2fa-b4cea13a6d76____PIT_city_57819.json create mode 100644 tests/test_data/sensor_dataset_logs/av2/sensor/val/adcf7d18-0510-35b0-a2fa-b4cea13a6d76/sensors/lidar/315973157959879000.feather create mode 100644 tests/torch/dataloaders/test_detection_dataloader.py diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index a6e4188c..72cecb4d 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -1,6 +1,6 @@ -//! # dataloaders +//! # data_loaders //! -//! Dataloader for loading the sensor dataset. +//! Data-loader for loading the sensor dataset. use constants::{ANNOTATION_COLUMN_NAMES, POSE_COLUMN_NAMES}; use io::{read_accumulate_lidar, read_timestamped_feather}; @@ -65,7 +65,7 @@ impl Sweep { /// Sensor dataloader for `av2`. #[derive(Serialize, Deserialize)] #[pyclass(module = "av2._r")] -pub struct Dataloader { +pub struct DataLoader { /// Root dataset directory. #[pyo3(get, set)] pub root_dir: PathBuf, @@ -93,7 +93,7 @@ pub struct Dataloader { } #[pymethods] -impl Dataloader { +impl DataLoader { /// Initialize the dataloader and build the file index. #[new] pub fn new( @@ -103,11 +103,11 @@ impl Dataloader { split_name: &str, num_accumulated_sweeps: usize, memory_mapped: bool, - ) -> Dataloader { + ) -> DataLoader { let root_dir = Path::new(root_dir); let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); let current_idx = 0; - Dataloader { + DataLoader { root_dir: root_dir.to_path_buf(), dataset_name: dataset_name.to_string(), dataset_type: dataset_type.to_string(), @@ -259,7 +259,7 @@ impl Dataloader { } } -impl Iterator for Dataloader { +impl Iterator for DataLoader { type Item = Sweep; fn next(&mut self) -> Option { diff --git a/rust/src/lib.rs b/rust/src/lib.rs index e6e6f34a..2e361fa7 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -13,7 +13,7 @@ pub mod path; pub mod se3; pub mod so3; -use dataloader::{Dataloader, Sweep}; +use dataloader::{DataLoader, Sweep}; use ndarray::Dim; use numpy::{IntoPyArray, PyArray}; use pyo3::prelude::*; @@ -54,7 +54,7 @@ fn py_voxelize<'py>( /// A Python module implemented in Rust. #[pymodule] fn _r(_py: Python, m: &PyModule) -> PyResult<()> { - m.add_class::()?; + m.add_class::()?; m.add_class::()?; m.add_function(wrap_pyfunction!(py_voxelize, m)?)?; Ok(()) diff --git a/src/av2/torch/dataloaders/detection.py b/src/av2/torch/dataloaders/detection.py index 6e97cd3c..b33d8d89 100644 --- a/src/av2/torch/dataloaders/detection.py +++ b/src/av2/torch/dataloaders/detection.py @@ -1,4 +1,4 @@ -"""Pytorch dataloader for 3D object detection task.""" +"""Pytorch data-loader for 3D object detection task.""" from __future__ import annotations @@ -17,8 +17,8 @@ @dataclass -class DetectionDataloader(Dataset[Sweep]): - """Pytorch dataloader for the sensor dataset. +class DetectionDataLoader(Dataset[Sweep]): + """Pytorch data-loader for the sensor dataset. The sensor dataset should exist somewhere such as `~/data/datasets/{dataset_name}/{dataset_type}/{split_name}`, where @@ -26,7 +26,7 @@ class DetectionDataloader(Dataset[Sweep]): dataset_type = "sensor, split_name = "train". - This dataloader backend is implemented in Rust for speed. Each iteration will yield a new sweep. + This data-loader backend is implemented in Rust for speed. Each iteration will yield a new sweep. 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zS9|!@|3@Fq_YZ5_Cr(Ej$;N`C%%1q1#MX72aC literal 0 HcmV?d00001 diff --git a/tests/torch/dataloaders/test_detection_dataloader.py b/tests/torch/dataloaders/test_detection_dataloader.py new file mode 100644 index 00000000..5ba1eb49 --- /dev/null +++ b/tests/torch/dataloaders/test_detection_dataloader.py @@ -0,0 +1,18 @@ +"""Unit tests for Pytorch Detection Dataset module.""" + +from pathlib import Path +from typing import Final + +from av2.torch.dataloaders.detection import DetectionDataloader + +TEST_DATA_DIR: Final = Path(__file__).parent.parent.parent.resolve() / "test_data" / "sensor_dataset_logs" + + +def test_build_data_loader() -> None: + """Test building the Pytorch Detection DataLoader.""" + root_dir = TEST_DATA_DIR + dataset_name = "av2" + split_name = "val" + data_loader = DetectionDataloader(root_dir=root_dir, dataset_name=dataset_name, split_name=split_name) + for datum in data_loader: + assert datum is not None diff --git a/tests/torch/structures/test_lidar.py b/tests/torch/structures/test_lidar.py index 967911b5..3064f90c 100644 --- a/tests/torch/structures/test_lidar.py +++ b/tests/torch/structures/test_lidar.py @@ -23,4 +23,12 @@ def test_build_lidar() -> None: lidar = Lidar(frame) torch.testing.assert_close(lidar.as_tensor(), lidar_tensor) - torch.testing.assert_close(lidar.as_tensor(columns=("y", "z",)), lidar_tensor[:, 1:3]) + torch.testing.assert_close( + lidar.as_tensor( + columns=( + "y", + "z", + ) + ), + lidar_tensor[:, 1:3], + ) From 47283364209a899636d163bfcf81b7df893a88b1 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 14:59:26 -0700 Subject: [PATCH 092/117] Update naming. --- src/av2/_r.pyi | 2 +- src/av2/torch/{dataloaders => data_loaders}/__init__.py | 0 src/av2/torch/{dataloaders => data_loaders}/detection.py | 4 ++-- src/av2/torch/{dataloaders => data_loaders}/scene_flow.py | 0 .../test_detection_dataloader.py | 4 ++-- .../{detection_dataloader.py => detection_data_loader.py} | 8 ++++---- 6 files changed, 9 insertions(+), 9 deletions(-) rename src/av2/torch/{dataloaders => data_loaders}/__init__.py (100%) rename src/av2/torch/{dataloaders => data_loaders}/detection.py (96%) rename src/av2/torch/{dataloaders => data_loaders}/scene_flow.py (100%) rename tests/torch/{dataloaders => data_loaders}/test_detection_dataloader.py (79%) rename tutorials/{detection_dataloader.py => detection_data_loader.py} (89%) diff --git a/src/av2/_r.pyi b/src/av2/_r.pyi index 0e9044f2..8e2e248e 100644 --- a/src/av2/_r.pyi +++ b/src/av2/_r.pyi @@ -6,7 +6,7 @@ from typing import Tuple import polars as pl @dataclass -class Dataloader: +class DataLoader: root_dir: str dataset_name: str dataset_type: str diff --git a/src/av2/torch/dataloaders/__init__.py b/src/av2/torch/data_loaders/__init__.py similarity index 100% rename from src/av2/torch/dataloaders/__init__.py rename to src/av2/torch/data_loaders/__init__.py diff --git a/src/av2/torch/dataloaders/detection.py b/src/av2/torch/data_loaders/detection.py similarity index 96% rename from src/av2/torch/dataloaders/detection.py rename to src/av2/torch/data_loaders/detection.py index b33d8d89..e65ba3e1 100644 --- a/src/av2/torch/dataloaders/detection.py +++ b/src/av2/torch/data_loaders/detection.py @@ -42,12 +42,12 @@ class DetectionDataLoader(Dataset[Sweep]): num_accumulated_sweeps: int = 1 memory_mapped: bool = False - _backend: rust.Dataloader = field(init=False) + _backend: rust.DataLoader = field(init=False) _current_idx: int = 0 def __post_init__(self) -> None: """Initialize Rust backend.""" - self._backend = rust.Dataloader( + self._backend = rust.DataLoader( str(self.root_dir), self.dataset_name, "sensor", diff --git a/src/av2/torch/dataloaders/scene_flow.py b/src/av2/torch/data_loaders/scene_flow.py similarity index 100% rename from src/av2/torch/dataloaders/scene_flow.py rename to src/av2/torch/data_loaders/scene_flow.py diff --git a/tests/torch/dataloaders/test_detection_dataloader.py b/tests/torch/data_loaders/test_detection_dataloader.py similarity index 79% rename from tests/torch/dataloaders/test_detection_dataloader.py rename to tests/torch/data_loaders/test_detection_dataloader.py index 5ba1eb49..08f2e43c 100644 --- a/tests/torch/dataloaders/test_detection_dataloader.py +++ b/tests/torch/data_loaders/test_detection_dataloader.py @@ -3,7 +3,7 @@ from pathlib import Path from typing import Final -from av2.torch.dataloaders.detection import DetectionDataloader +from av2.torch.data_loaders.detection import DetectionDataLoader TEST_DATA_DIR: Final = Path(__file__).parent.parent.parent.resolve() / "test_data" / "sensor_dataset_logs" @@ -13,6 +13,6 @@ def test_build_data_loader() -> None: root_dir = TEST_DATA_DIR dataset_name = "av2" split_name = "val" - data_loader = DetectionDataloader(root_dir=root_dir, dataset_name=dataset_name, split_name=split_name) + data_loader = DetectionDataLoader(root_dir=root_dir, dataset_name=dataset_name, split_name=split_name) for datum in data_loader: assert datum is not None diff --git a/tutorials/detection_dataloader.py b/tutorials/detection_data_loader.py similarity index 89% rename from tutorials/detection_dataloader.py rename to tutorials/detection_data_loader.py index ba9c16cd..7fa4ed41 100644 --- a/tutorials/detection_dataloader.py +++ b/tutorials/detection_data_loader.py @@ -7,8 +7,8 @@ from kornia.geometry.linalg import transform_points from tqdm import tqdm -from av2.torch.dataloaders.detection import DetectionDataloader -from av2.torch.dataloaders.utils import CuboidMode +from av2.torch.data_loaders.detection import DetectionDataLoader +from av2.torch.structures.cuboids import CuboidMode logger = logging.getLogger(__name__) @@ -34,13 +34,13 @@ def main( max_iterations: Maximum number of iterations for the dataloader example. """ logger.info("Starting detection dataloader example ...") - dataloader = DetectionDataloader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) + dataloader = DetectionDataLoader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) for i, sweep in enumerate(tqdm(dataloader)): # 4x4 matrix representing the SE(3) transformation to city from ego-vehicle coordinates. city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() # Lidar (x,y,z) in meters and intensity (i). - lidar_xyzi_ego = sweep.lidar_xyzi[:, :3] + lidar_xyzi_ego = sweep.lidar.as_tensor() # Transform the points to city coordinates. lidar_xyz_city = transform_points(city_SE3_ego_4x4, lidar_xyzi_ego[:, :3]) From 9df5c5cdc6adc21889ce2a132b5527f7a6432dba Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:00:28 -0700 Subject: [PATCH 093/117] Update rust vars. --- rust/src/constants.rs | 4 ++-- rust/src/dataloader.rs | 6 +++--- rust/src/io.rs | 6 +++--- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/rust/src/constants.rs b/rust/src/constants.rs index 3ce19eb1..98fa980f 100644 --- a/rust/src/constants.rs +++ b/rust/src/constants.rs @@ -4,7 +4,7 @@ /// Annotation dataframe columns. /// Found in `annotations.feather`. -pub const ANNOTATION_COLUMN_NAMES: [&str; 13] = [ +pub const ANNOTATION_COLUMNS: [&str; 13] = [ "tx_m", "ty_m", "tz_m", @@ -22,7 +22,7 @@ pub const ANNOTATION_COLUMN_NAMES: [&str; 13] = [ /// Pose dataframe columns. /// Found in `city_SE3_egovehicle`. -pub const POSE_COLUMN_NAMES: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; +pub const POSE_COLUMNS: [&str; 7] = ["tx_m", "ty_m", "tz_m", "qw", "qx", "qy", "qz"]; /// Unknown map file name for use if the map doesn't exist. pub const DEFAULT_MAP_FILE_NAME: &str = "log_map_archive___DEFAULT_city_00000.json"; diff --git a/rust/src/dataloader.rs b/rust/src/dataloader.rs index 72cecb4d..30010bc9 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/dataloader.rs @@ -2,7 +2,7 @@ //! //! Data-loader for loading the sensor dataset. -use constants::{ANNOTATION_COLUMN_NAMES, POSE_COLUMN_NAMES}; +use constants::{ANNOTATION_COLUMNS, POSE_COLUMNS}; use io::{read_accumulate_lidar, read_timestamped_feather}; use itertools::{multiunzip, Itertools}; use path::{extract_file_stem, walk_dir}; @@ -159,7 +159,7 @@ impl DataLoader { PyDataFrame( read_timestamped_feather( &self.city_pose_path(log_id), - &POSE_COLUMN_NAMES.to_vec(), + &POSE_COLUMNS.to_vec(), ×tamp_ns, self.memory_mapped, ) @@ -188,7 +188,7 @@ impl DataLoader { PyDataFrame( read_timestamped_feather( &self.annotations_path(log_id), - &ANNOTATION_COLUMN_NAMES.to_vec(), + &ANNOTATION_COLUMNS.to_vec(), ×tamp_ns, self.memory_mapped, ) diff --git a/rust/src/io.rs b/rust/src/io.rs index 1294574d..98313eca 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -26,7 +26,7 @@ use rayon::prelude::ParallelIterator; use std::fs::File; use std::path::PathBuf; -use crate::constants::POSE_COLUMN_NAMES; +use crate::constants::POSE_COLUMNS; use crate::se3::SE3; use crate::so3::quat_to_mat3; @@ -59,7 +59,7 @@ pub fn read_accumulate_lidar( let pose_ref = dataframe_to_nd_and_filter( &poses, - cols(POSE_COLUMN_NAMES), + cols(POSE_COLUMNS), col("timestamp_ns").eq(timestamp_ns), ); @@ -95,7 +95,7 @@ pub fn read_accumulate_lidar( if timestamp_ns_i != timestamp_ns { let pose_i = dataframe_to_nd_and_filter( &poses, - cols(POSE_COLUMN_NAMES), + cols(POSE_COLUMNS), col("timestamp_ns").eq(timestamp_ns_i), ); From e3bb48a7a8ae9917045a45a5ab75758c423b5e7c Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:06:43 -0700 Subject: [PATCH 094/117] Update naming. --- rust/src/{dataloader.rs => data_loader.rs} | 6 +++--- rust/src/lib.rs | 4 ++-- src/av2/torch/data_loaders/__init__.py | 2 +- src/av2/torch/data_loaders/scene_flow.py | 8 ++++---- src/av2/torch/structures/cuboids.py | 6 +++--- src/av2/torch/structures/sweep.py | 2 +- tutorials/detection_data_loader.py | 10 +++++----- 7 files changed, 19 insertions(+), 19 deletions(-) rename rust/src/{dataloader.rs => data_loader.rs} (98%) diff --git a/rust/src/dataloader.rs b/rust/src/data_loader.rs similarity index 98% rename from rust/src/dataloader.rs rename to rust/src/data_loader.rs index 30010bc9..581b4755 100644 --- a/rust/src/dataloader.rs +++ b/rust/src/data_loader.rs @@ -62,7 +62,7 @@ impl Sweep { } } -/// Sensor dataloader for `av2`. +/// Sensor data-loader for `av2`. #[derive(Serialize, Deserialize)] #[pyclass(module = "av2._r")] pub struct DataLoader { @@ -87,14 +87,14 @@ pub struct DataLoader { /// Dataframe consisting of `log_id`, `timestamp_ns`, and `city_name`. #[pyo3(get, set)] pub file_index: PyDataFrame, - /// Current index of the dataloader. + /// Current index of the data-loader. #[pyo3(get, set)] pub current_index: usize, } #[pymethods] impl DataLoader { - /// Initialize the dataloader and build the file index. + /// Initialize the data-loader and build the file index. #[new] pub fn new( root_dir: &str, diff --git a/rust/src/lib.rs b/rust/src/lib.rs index 2e361fa7..49426e9b 100644 --- a/rust/src/lib.rs +++ b/rust/src/lib.rs @@ -6,14 +6,14 @@ #![warn(missing_doc_code_examples)] pub mod constants; -pub mod dataloader; +pub mod data_loader; pub mod io; pub mod ops; pub mod path; pub mod se3; pub mod so3; -use dataloader::{DataLoader, Sweep}; +use data_loader::{DataLoader, Sweep}; use ndarray::Dim; use numpy::{IntoPyArray, PyArray}; use pyo3::prelude::*; diff --git a/src/av2/torch/data_loaders/__init__.py b/src/av2/torch/data_loaders/__init__.py index 8c794a20..abd1512d 100644 --- a/src/av2/torch/data_loaders/__init__.py +++ b/src/av2/torch/data_loaders/__init__.py @@ -1 +1 @@ -"""Pytorch sensor dataloader module.""" +"""Pytorch sensor data-loader module.""" diff --git a/src/av2/torch/data_loaders/scene_flow.py b/src/av2/torch/data_loaders/scene_flow.py index d1301334..aadc5842 100644 --- a/src/av2/torch/data_loaders/scene_flow.py +++ b/src/av2/torch/data_loaders/scene_flow.py @@ -1,4 +1,4 @@ -"""Pytorch dataloader for the scene flow task.""" +"""Pytorch data-loader for the scene flow task.""" from __future__ import annotations @@ -21,7 +21,7 @@ @dataclass class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): - """Pytorch dataloader for the sensor dataset. + """Pytorch data-loader for the sensor dataset. Args: root_dir: Path to the dataset directory. @@ -77,11 +77,11 @@ def __getitem__(self, index: int) -> Tuple[Sweep, Optional[Sweep]]: return Sweep.from_rust(sweep), next_sweep def __len__(self) -> int: - """Length of the dataloader.""" + """Length of the data-loader.""" return self._backend.__len__() def __iter__(self) -> SceneFlowDataloader: - """Iterate method for the dataloader.""" + """Iterate method for the data-loader.""" return self def __next__(self) -> Tuple[Sweep, Optional[Sweep]]: diff --git a/src/av2/torch/structures/cuboids.py b/src/av2/torch/structures/cuboids.py index e293b541..0694d016 100644 --- a/src/av2/torch/structures/cuboids.py +++ b/src/av2/torch/structures/cuboids.py @@ -18,7 +18,7 @@ class CuboidMode(str, Enum): """Cuboid parameterization modes.""" - XYZLWH_YAW = "XYZLWH_YAW" # 1-DOF orientation. + XYZLWH_T = "XYZLWHT" # 1-DOF orientation. XYZLWH_QWXYZ = "XYZLWH_QWXYZ" # 3-DOF orientation. @@ -44,7 +44,7 @@ def track_uuid(self) -> List[str]: category_names: List[str] = self._frame["track_uuid"].to_list() return category_names - def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> torch.Tensor: + def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_T) -> torch.Tensor: """Return object cuboids as an (N,K) tensor. Notation: @@ -61,7 +61,7 @@ def as_tensor(self, cuboid_mode: CuboidMode = CuboidMode.XYZLWH_YAW) -> torch.Te NotImplementedError: Raised if the cuboid mode is not supported. """ xyzlwh_qwxyz = tensor_from_frame(self._frame, list(XYZLWH_QWXYZ_COLUMNS)) - if cuboid_mode == CuboidMode.XYZLWH_YAW: + if cuboid_mode == CuboidMode.XYZLWH_T: quat_wxyz = xyzlwh_qwxyz[:, 6:10] w, x, y, z = quat_wxyz[:, 0], quat_wxyz[:, 1], quat_wxyz[:, 2], quat_wxyz[:, 3] _, _, yaw = euler_from_quaternion(w, x, y, z) diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py index 6669b468..9cd82622 100644 --- a/src/av2/torch/structures/sweep.py +++ b/src/av2/torch/structures/sweep.py @@ -39,7 +39,7 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: """Build a sweep from the Rust backend. Args: - sweep: Sweep object from the Rust backend dataloader. + sweep: Sweep object from the Rust backend data-loader. Returns: Sweep object. diff --git a/tutorials/detection_data_loader.py b/tutorials/detection_data_loader.py index 7fa4ed41..5bf00f6d 100644 --- a/tutorials/detection_data_loader.py +++ b/tutorials/detection_data_loader.py @@ -22,7 +22,7 @@ def main( num_accumulated_sweeps: int = 1, max_iterations: int = 1000, ) -> None: - """Iterate over the detection dataloader. + """Iterate over the detection data-loader. Dataset should live at ~/data/datasets/{dataset_name}/{split_name}. @@ -31,11 +31,11 @@ def main( dataset_name: Name of the dataset (e.g., "av2"). split_name: Name of the split (e.g., "val"). num_accumulated_sweeps: Number of sweeps to accumulate. - max_iterations: Maximum number of iterations for the dataloader example. + max_iterations: Maximum number of iterations for the data-loader example. """ - logger.info("Starting detection dataloader example ...") - dataloader = DetectionDataLoader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) - for i, sweep in enumerate(tqdm(dataloader)): + logger.info("Starting detection data-loader example ...") + data_loader = DetectionDataLoader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) + for i, sweep in enumerate(tqdm(data_loader)): # 4x4 matrix representing the SE(3) transformation to city from ego-vehicle coordinates. city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() From 2a91e435995ca7151fbc7abfc6f6cf59749836ad Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:08:14 -0700 Subject: [PATCH 095/117] Fix nit --- tutorials/detection_data_loader.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tutorials/detection_data_loader.py b/tutorials/detection_data_loader.py index 5bf00f6d..372f0406 100644 --- a/tutorials/detection_data_loader.py +++ b/tutorials/detection_data_loader.py @@ -40,10 +40,10 @@ def main( city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() # Lidar (x,y,z) in meters and intensity (i). - lidar_xyzi_ego = sweep.lidar.as_tensor() + lidar_tensor = sweep.lidar.as_tensor() # Transform the points to city coordinates. - lidar_xyz_city = transform_points(city_SE3_ego_4x4, lidar_xyzi_ego[:, :3]) + lidar_xyz_city = transform_points(city_SE3_ego_4x4, lidar_tensor[:, :3]) # Cuboids might not be available (e.g., using the "test" split). if sweep.cuboids is not None: From f9b020f99901e29cdc9b38d629b804e19dbf6772 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:12:40 -0700 Subject: [PATCH 096/117] Fix docstring. --- src/av2/torch/data_loaders/detection.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/data_loaders/detection.py b/src/av2/torch/data_loaders/detection.py index e65ba3e1..6d9b2aa6 100644 --- a/src/av2/torch/data_loaders/detection.py +++ b/src/av2/torch/data_loaders/detection.py @@ -32,7 +32,7 @@ class DetectionDataLoader(Dataset[Sweep]): root_dir: Path to the dataset directory. dataset_name: Dataset name (e.g., "av2"). split_name: Name of the dataset split (e.g., "train"). - num_accum_sweeps: Number of temporally accumulated sweeps (accounting for ego-vehicle motion). + num_accumulated_sweeps: Number of temporally accumulated sweeps (accounting for ego-vehicle motion). memory_mapped: Boolean flag indicating whether to memory map the dataframes. """ From 55915ae8f339c761b3c0d614f693c29cc5e84d9d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:13:12 -0700 Subject: [PATCH 097/117] Fix docstring. --- src/av2/torch/data_loaders/scene_flow.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/data_loaders/scene_flow.py b/src/av2/torch/data_loaders/scene_flow.py index aadc5842..f00c586e 100644 --- a/src/av2/torch/data_loaders/scene_flow.py +++ b/src/av2/torch/data_loaders/scene_flow.py @@ -27,7 +27,7 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): root_dir: Path to the dataset directory. dataset_name: Dataset name (e.g., "av2"). split_name: Name of the dataset split (e.g., "train"). - num_accum_sweeps: Number of temporally accumulated sweeps (accounting for ego-vehicle motion). + num_accumulated_sweeps: Number of temporally accumulated sweeps (accounting for ego-vehicle motion). memory_mapped: Boolean flag indicating whether to memory map the dataframes. """ From 5a8d02474214eedc7c7b309a44a221bae1b0ce59 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:13:43 -0700 Subject: [PATCH 098/117] Fix enum. --- src/av2/torch/structures/cuboids.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/structures/cuboids.py b/src/av2/torch/structures/cuboids.py index 0694d016..65f5a325 100644 --- a/src/av2/torch/structures/cuboids.py +++ b/src/av2/torch/structures/cuboids.py @@ -18,7 +18,7 @@ class CuboidMode(str, Enum): """Cuboid parameterization modes.""" - XYZLWH_T = "XYZLWHT" # 1-DOF orientation. + XYZLWH_T = "XYZLWH_T" # 1-DOF orientation. XYZLWH_QWXYZ = "XYZLWH_QWXYZ" # 3-DOF orientation. From 502842fff3c1cbb100590cf41f13fbfe2cfaebae Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:32:23 -0700 Subject: [PATCH 099/117] Add utils tests. --- tests/torch/structures/test_utils.py | 52 ++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) create mode 100644 tests/torch/structures/test_utils.py diff --git a/tests/torch/structures/test_utils.py b/tests/torch/structures/test_utils.py new file mode 100644 index 00000000..090770ef --- /dev/null +++ b/tests/torch/structures/test_utils.py @@ -0,0 +1,52 @@ +"""Unit test for Pytorch structure utilities.""" + +import numpy as np +import pandas as pd +import torch +from kornia.geometry.liegroup import Se3, So3 +from kornia.geometry.quaternion import Quaternion + +from av2.torch import QWXYZ_COLUMNS, TRANSLATION_COLUMNS +from av2.torch.structures.utils import SE3_from_frame, tensor_from_frame + + +def _build_dummy_frame() -> pd.DataFrame: + """Build a dummy data-frame.""" + return pd.DataFrame( + { + "tx_m": [0.0], + "ty_m": [1.0], + "tz_m": [0.0], + "qw": [1.0], + "qx": [0.0], + "qy": [0.0], + "qz": [0.0], + }, + dtype=np.float32, + ) + + +def test_tensor_from_frame() -> None: + """Test converting a data-frame into a tensor.""" + frame = _build_dummy_frame() + tensor = tensor_from_frame(frame, columns=["qw", "qx", "qy", "qz"]) + + tensor_expected = torch.as_tensor( + [[frame.loc[0, "qw"], frame.loc[0, "qx"], frame.loc[0, "qy"], frame.loc[0, "qz"]]] + ) + torch.testing.assert_close(tensor, tensor_expected) + + +def test_SE3_from_frame() -> None: + """Test converting a data-frame into an SE(3) object.""" + frame = _build_dummy_frame() + + quat_wxyz_tensor = torch.as_tensor(frame[list(QWXYZ_COLUMNS)].to_numpy().astype(np.float32)) + translation = torch.as_tensor(frame[list(TRANSLATION_COLUMNS)].to_numpy().astype(np.float32)) + quat_wxyz = Quaternion(quat_wxyz_tensor) + rotation = So3(quat_wxyz) + city_SE3_ego_expected = Se3(rotation, translation) + city_SE3_ego = SE3_from_frame(frame) + + torch.testing.assert_close(city_SE3_ego.translation, city_SE3_ego_expected.translation) + torch.testing.assert_close(city_SE3_ego.rotation.matrix(), city_SE3_ego_expected.rotation.matrix()) From 3fd3a3113a2ff833e4d246d1974a9c6a968de75b Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:34:57 -0700 Subject: [PATCH 100/117] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 0647c871..e4c0cfc1 100644 --- a/README.md +++ b/README.md @@ -45,7 +45,7 @@ The easiest way to install the API is via [conda](https://docs.conda.io/en/lates bash conda/install.sh ``` -Additional information can be found in: [INSTALL](conda/INSTALL.md). +Additional information can be found in the: [INSTALL README](conda/INSTALL.md). ### Datasets From 28fa6f17b190b44a117af682a59f7af3ab8604c5 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:39:37 -0700 Subject: [PATCH 101/117] Add additional tests. --- tests/torch/structures/test_cuboids.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py index 9f79988c..8f37605a 100644 --- a/tests/torch/structures/test_cuboids.py +++ b/tests/torch/structures/test_cuboids.py @@ -1,7 +1,7 @@ """Unit tests for Pytorch Cuboids module.""" from pathlib import Path -from typing import Final +from typing import Final, List import numpy as np import pandas as pd @@ -32,6 +32,12 @@ def test_build_cuboids() -> None: torch.testing.assert_close(cuboids_xyzlwht[:, 6], yaw) torch.testing.assert_close(cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ), cuboids_xyzlwh_qwxyz) + track_uuid_expected: List[str] = annotations_frame["track_uuid"].to_list() + assert cuboids.track_uuid == track_uuid_expected + + category_expected: List[str] = annotations_frame["category"].to_list() + assert cuboids.category == category_expected + def test_build_lidar() -> None: """Test building a lidar tensor.""" From aaffaae30a55931c989b1332d1f1d6a40b154fb1 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:39:55 -0700 Subject: [PATCH 102/117] Remove dead code. --- tests/torch/structures/test_cuboids.py | 7 ------- 1 file changed, 7 deletions(-) diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py index 8f37605a..00ee3a1b 100644 --- a/tests/torch/structures/test_cuboids.py +++ b/tests/torch/structures/test_cuboids.py @@ -37,10 +37,3 @@ def test_build_cuboids() -> None: category_expected: List[str] = annotations_frame["category"].to_list() assert cuboids.category == category_expected - - -def test_build_lidar() -> None: - """Test building a lidar tensor.""" - lidar_paths = sorted((SAMPLE_LOG_DIR / "sensors" / "lidar").glob("*.feather")) - lidar_path = lidar_paths[0] - lidar_frame = pd.read_feather(lidar_path) From b1eb02bad29c37a7f3484d73da711a94fb121e2a Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:41:34 -0700 Subject: [PATCH 103/117] Update spelling. --- src/av2/torch/__init__.py | 2 +- src/av2/torch/data_loaders/__init__.py | 2 +- src/av2/torch/data_loaders/detection.py | 4 ++-- src/av2/torch/data_loaders/scene_flow.py | 4 ++-- src/av2/torch/structures/__init__.py | 2 +- src/av2/torch/structures/cuboids.py | 2 +- src/av2/torch/structures/lidar.py | 2 +- src/av2/torch/structures/sweep.py | 2 +- src/av2/torch/structures/utils.py | 2 +- tests/torch/data_loaders/test_detection_dataloader.py | 4 ++-- tests/torch/structures/test_cuboids.py | 2 +- tests/torch/structures/test_lidar.py | 2 +- tests/torch/structures/test_sweep.py | 2 +- tests/torch/structures/test_utils.py | 2 +- 14 files changed, 17 insertions(+), 17 deletions(-) diff --git a/src/av2/torch/__init__.py b/src/av2/torch/__init__.py index b1745725..96826ea0 100644 --- a/src/av2/torch/__init__.py +++ b/src/av2/torch/__init__.py @@ -1,4 +1,4 @@ -"""Argoverse 2 Pytorch API.""" +"""Argoverse 2 PyTorch API.""" from typing import Final diff --git a/src/av2/torch/data_loaders/__init__.py b/src/av2/torch/data_loaders/__init__.py index abd1512d..58adbd69 100644 --- a/src/av2/torch/data_loaders/__init__.py +++ b/src/av2/torch/data_loaders/__init__.py @@ -1 +1 @@ -"""Pytorch sensor data-loader module.""" +"""PyTorch sensor data-loader module.""" diff --git a/src/av2/torch/data_loaders/detection.py b/src/av2/torch/data_loaders/detection.py index 6d9b2aa6..1a07191d 100644 --- a/src/av2/torch/data_loaders/detection.py +++ b/src/av2/torch/data_loaders/detection.py @@ -1,4 +1,4 @@ -"""Pytorch data-loader for 3D object detection task.""" +"""PyTorch data-loader for 3D object detection task.""" from __future__ import annotations @@ -18,7 +18,7 @@ @dataclass class DetectionDataLoader(Dataset[Sweep]): - """Pytorch data-loader for the sensor dataset. + """PyTorch data-loader for the sensor dataset. The sensor dataset should exist somewhere such as `~/data/datasets/{dataset_name}/{dataset_type}/{split_name}`, where diff --git a/src/av2/torch/data_loaders/scene_flow.py b/src/av2/torch/data_loaders/scene_flow.py index f00c586e..7a69da0b 100644 --- a/src/av2/torch/data_loaders/scene_flow.py +++ b/src/av2/torch/data_loaders/scene_flow.py @@ -1,4 +1,4 @@ -"""Pytorch data-loader for the scene flow task.""" +"""PyTorch data-loader for the scene flow task.""" from __future__ import annotations @@ -21,7 +21,7 @@ @dataclass class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): - """Pytorch data-loader for the sensor dataset. + """PyTorch data-loader for the sensor dataset. Args: root_dir: Path to the dataset directory. diff --git a/src/av2/torch/structures/__init__.py b/src/av2/torch/structures/__init__.py index 30e816ab..91d4a29c 100644 --- a/src/av2/torch/structures/__init__.py +++ b/src/av2/torch/structures/__init__.py @@ -1 +1 @@ -"""Argoverse 2 Pytorch structures.""" +"""Argoverse 2 PyTorch structures.""" diff --git a/src/av2/torch/structures/cuboids.py b/src/av2/torch/structures/cuboids.py index 65f5a325..7f12e38c 100644 --- a/src/av2/torch/structures/cuboids.py +++ b/src/av2/torch/structures/cuboids.py @@ -1,4 +1,4 @@ -"""Pytorch Cuboids module.""" +"""PyTorch Cuboids module.""" from __future__ import annotations diff --git a/src/av2/torch/structures/lidar.py b/src/av2/torch/structures/lidar.py index 26008484..40d5a8d1 100644 --- a/src/av2/torch/structures/lidar.py +++ b/src/av2/torch/structures/lidar.py @@ -1,4 +1,4 @@ -"""Pytorch Lidar Module.""" +"""PyTorch Lidar Module.""" from __future__ import annotations diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py index 9cd82622..4af26947 100644 --- a/src/av2/torch/structures/sweep.py +++ b/src/av2/torch/structures/sweep.py @@ -1,4 +1,4 @@ -"""Pytorch sweep module.""" +"""PyTorch sweep module.""" from __future__ import annotations diff --git a/src/av2/torch/structures/utils.py b/src/av2/torch/structures/utils.py index 2a08f93d..dd589443 100644 --- a/src/av2/torch/structures/utils.py +++ b/src/av2/torch/structures/utils.py @@ -1,4 +1,4 @@ -"""Pytorch structure utilities.""" +"""PyTorch structure utilities.""" from __future__ import annotations diff --git a/tests/torch/data_loaders/test_detection_dataloader.py b/tests/torch/data_loaders/test_detection_dataloader.py index 08f2e43c..f5d60e00 100644 --- a/tests/torch/data_loaders/test_detection_dataloader.py +++ b/tests/torch/data_loaders/test_detection_dataloader.py @@ -1,4 +1,4 @@ -"""Unit tests for Pytorch Detection Dataset module.""" +"""Unit tests for PyTorch Detection Dataset module.""" from pathlib import Path from typing import Final @@ -9,7 +9,7 @@ def test_build_data_loader() -> None: - """Test building the Pytorch Detection DataLoader.""" + """Test building the PyTorch Detection DataLoader.""" root_dir = TEST_DATA_DIR dataset_name = "av2" split_name = "val" diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py index 00ee3a1b..c9e092b0 100644 --- a/tests/torch/structures/test_cuboids.py +++ b/tests/torch/structures/test_cuboids.py @@ -1,4 +1,4 @@ -"""Unit tests for Pytorch Cuboids module.""" +"""Unit tests for PyTorch Cuboids module.""" from pathlib import Path from typing import Final, List diff --git a/tests/torch/structures/test_lidar.py b/tests/torch/structures/test_lidar.py index 3064f90c..2a8b942d 100644 --- a/tests/torch/structures/test_lidar.py +++ b/tests/torch/structures/test_lidar.py @@ -1,4 +1,4 @@ -"""Unit tests for Pytorch Lidar module.""" +"""Unit tests for PyTorch Lidar module.""" from pathlib import Path from typing import Final diff --git a/tests/torch/structures/test_sweep.py b/tests/torch/structures/test_sweep.py index 115b15ce..a8dc684e 100644 --- a/tests/torch/structures/test_sweep.py +++ b/tests/torch/structures/test_sweep.py @@ -1,4 +1,4 @@ -"""Unit tests for Pytorch Cuboids module.""" +"""Unit tests for PyTorch Cuboids module.""" from pathlib import Path from typing import Final diff --git a/tests/torch/structures/test_utils.py b/tests/torch/structures/test_utils.py index 090770ef..ae913ee7 100644 --- a/tests/torch/structures/test_utils.py +++ b/tests/torch/structures/test_utils.py @@ -1,4 +1,4 @@ -"""Unit test for Pytorch structure utilities.""" +"""Unit test for PyTorch structure utilities.""" import numpy as np import pandas as pd From 7d08883d702e05547fd16e739900fc33f58600d6 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 15:56:15 -0700 Subject: [PATCH 104/117] Update docstrings. --- tutorials/detection_data_loader.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/tutorials/detection_data_loader.py b/tutorials/detection_data_loader.py index 372f0406..dffff7da 100644 --- a/tutorials/detection_data_loader.py +++ b/tutorials/detection_data_loader.py @@ -1,4 +1,4 @@ -"""Example of rust-backed, torch dataloader.""" +"""Example of Rust-backed, PyTorch data-loader.""" import logging from pathlib import Path @@ -10,6 +10,7 @@ from av2.torch.data_loaders.detection import DetectionDataLoader from av2.torch.structures.cuboids import CuboidMode +logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) HOME_DIR: Final = Path.home() @@ -37,13 +38,13 @@ def main( data_loader = DetectionDataLoader(root_dir, dataset_name, split_name, num_accumulated_sweeps=num_accumulated_sweeps) for i, sweep in enumerate(tqdm(data_loader)): # 4x4 matrix representing the SE(3) transformation to city from ego-vehicle coordinates. - city_SE3_ego_4x4 = sweep.city_SE3_ego.matrix() + city_SE3_ego_mat4 = sweep.city_SE3_ego.matrix() # Lidar (x,y,z) in meters and intensity (i). lidar_tensor = sweep.lidar.as_tensor() # Transform the points to city coordinates. - lidar_xyz_city = transform_points(city_SE3_ego_4x4, lidar_tensor[:, :3]) + lidar_xyz_city = transform_points(city_SE3_ego_mat4, lidar_tensor[:, :3]) # Cuboids might not be available (e.g., using the "test" split). if sweep.cuboids is not None: From 96aae61722c654415965b6097214e9c6fa130a1f Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:00:02 -0700 Subject: [PATCH 105/117] Add additional examples. --- tutorials/detection_data_loader.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/tutorials/detection_data_loader.py b/tutorials/detection_data_loader.py index dffff7da..270696b7 100644 --- a/tutorials/detection_data_loader.py +++ b/tutorials/detection_data_loader.py @@ -51,9 +51,15 @@ def main( # Annotations in (x,y,z,l,w,h,yaw) format. cuboids = sweep.cuboids.as_tensor() - # Annotations in (x,y,z,l,w,h,qw,qx,qy,qz) format. - # Full 3-DOF rotation. - cuboids_qwxyz = sweep.cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ) + # Annotations in (x,y,z,l,theta) format. + # 1-DOF rotation. + xyzlwh_t = sweep.cuboids.as_tensor() + + # Access cuboid category. + category = sweep.cuboids.category + + # Access track uuid. + track_uuid = sweep.cuboids.track_uuid if i >= max_iterations: logger.info(f"Reached max iterations of {max_iterations}!") From 663e80c30bcbd44c176bd4a563e52f6a1c4384e0 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:00:17 -0700 Subject: [PATCH 106/117] Remove unused import. --- tutorials/detection_data_loader.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tutorials/detection_data_loader.py b/tutorials/detection_data_loader.py index 270696b7..8cbabee5 100644 --- a/tutorials/detection_data_loader.py +++ b/tutorials/detection_data_loader.py @@ -8,7 +8,6 @@ from tqdm import tqdm from av2.torch.data_loaders.detection import DetectionDataLoader -from av2.torch.structures.cuboids import CuboidMode logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) From b2d9a4721d52ab5af365408ba92ba6d06f261fde Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:02:54 -0700 Subject: [PATCH 107/117] Update versioning. --- Cargo.lock | 2 +- rust/Cargo.toml | 2 +- src/av2/__init__.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index 6c937196..4e54fc66 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -174,7 +174,7 @@ checksum = "d468802bab17cbc0cc575e9b053f41e72aa36bfa6b7f55e3529ffa43161b97fa" [[package]] name = "av2" -version = "0.1.0" +version = "0.3.0" dependencies = [ "anyhow", "bincode", diff --git a/rust/Cargo.toml b/rust/Cargo.toml index aef4a0ec..3ba3c962 100644 --- a/rust/Cargo.toml +++ b/rust/Cargo.toml @@ -1,6 +1,6 @@ [package] name = "av2" -version = "0.1.0" +version = "0.3.0" edition = "2021" [package.metadata.maturin] diff --git a/src/av2/__init__.py b/src/av2/__init__.py index a7c96927..c0993eaa 100644 --- a/src/av2/__init__.py +++ b/src/av2/__init__.py @@ -2,4 +2,4 @@ """Argoverse 2 API.""" -__version__ = "0.2.1" +__version__ = "0.3.0" From a5b9bac6001e94b8193851f8318a82339dfddce2 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:04:39 -0700 Subject: [PATCH 108/117] Rename rust methods. --- rust/src/io.rs | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/rust/src/io.rs b/rust/src/io.rs index 98313eca..6985fd0a 100644 --- a/rust/src/io.rs +++ b/rust/src/io.rs @@ -57,7 +57,7 @@ pub fn read_accumulate_lidar( let poses_path = log_dir.join("city_SE3_egovehicle.feather"); let poses = read_feather(&poses_path, memory_mapped); - let pose_ref = dataframe_to_nd_and_filter( + let pose_ref = ndarray_filtered_from_frame( &poses, cols(POSE_COLUMNS), col("timestamp_ns").eq(timestamp_ns), @@ -87,13 +87,13 @@ pub fn read_accumulate_lidar( let mut lidar = read_feather(&lidar_path, memory_mapped).lazy(); let xyz = - convert_dataframe_to_nd(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); + ndarray_from_frame(&lidar.clone().collect().unwrap(), cols(["x", "y", "z"])); let timedeltas = Series::new( "timedelta_ns", vec![(timestamp_ns - timestamp_ns_i) as f32 * 1e-9; xyz.shape()[0]], ); if timestamp_ns_i != timestamp_ns { - let pose_i = dataframe_to_nd_and_filter( + let pose_i = ndarray_filtered_from_frame( &poses, cols(POSE_COLUMNS), col("timestamp_ns").eq(timestamp_ns_i), @@ -172,7 +172,7 @@ pub fn build_lidar_file_path(log_dir: PathBuf, timestamp_ns: u64) -> PathBuf { } /// Convert a dataframe to `ndarray`. -pub fn convert_dataframe_to_nd(frame: &DataFrame, exprs: Expr) -> Array2 { +pub fn ndarray_from_frame(frame: &DataFrame, exprs: Expr) -> Array2 { frame .clone() .lazy() @@ -186,7 +186,7 @@ pub fn convert_dataframe_to_nd(frame: &DataFrame, exprs: Expr) -> Array2 { } /// Convert a dataframe to `ndarray` and filter. -pub fn dataframe_to_nd_and_filter( +pub fn ndarray_filtered_from_frame( frame: &DataFrame, select_exprs: Expr, filter_exprs: Expr, From 50d395f509859d20a87a088c99ab82c52c4bcd4d Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:07:44 -0700 Subject: [PATCH 109/117] Update docstrings. --- src/av2/datasets/sensor/__init__.py | 2 +- src/av2/torch/data_loaders/__init__.py | 2 +- src/av2/torch/structures/cuboids.py | 2 +- src/av2/torch/structures/sweep.py | 2 +- tests/rendering/test_rasterize.py | 2 +- tests/torch/data_loaders/test_detection_dataloader.py | 2 +- tests/torch/structures/test_cuboids.py | 2 +- tests/torch/structures/test_lidar.py | 2 +- tests/torch/structures/test_sweep.py | 2 +- 9 files changed, 9 insertions(+), 9 deletions(-) diff --git a/src/av2/datasets/sensor/__init__.py b/src/av2/datasets/sensor/__init__.py index 8986d95b..4ab690f9 100644 --- a/src/av2/datasets/sensor/__init__.py +++ b/src/av2/datasets/sensor/__init__.py @@ -1,3 +1,3 @@ # -"""Sensor dataset submodule.""" +"""Sensor dataset sub-package.""" diff --git a/src/av2/torch/data_loaders/__init__.py b/src/av2/torch/data_loaders/__init__.py index 58adbd69..dd1a2b8d 100644 --- a/src/av2/torch/data_loaders/__init__.py +++ b/src/av2/torch/data_loaders/__init__.py @@ -1 +1 @@ -"""PyTorch sensor data-loader module.""" +"""PyTorch sensor data-loader sub-package.""" diff --git a/src/av2/torch/structures/cuboids.py b/src/av2/torch/structures/cuboids.py index 7f12e38c..e9ca1b66 100644 --- a/src/av2/torch/structures/cuboids.py +++ b/src/av2/torch/structures/cuboids.py @@ -1,4 +1,4 @@ -"""PyTorch Cuboids module.""" +"""PyTorch Cuboids sub-module.""" from __future__ import annotations diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py index 4af26947..dd2c1238 100644 --- a/src/av2/torch/structures/sweep.py +++ b/src/av2/torch/structures/sweep.py @@ -1,4 +1,4 @@ -"""PyTorch sweep module.""" +"""PyTorch sweep sub-module.""" from __future__ import annotations diff --git a/tests/rendering/test_rasterize.py b/tests/rendering/test_rasterize.py index fd206681..dda574b3 100644 --- a/tests/rendering/test_rasterize.py +++ b/tests/rendering/test_rasterize.py @@ -1,4 +1,4 @@ -"""Tests for the rasterize module.""" +"""Tests for the rasterize sub-module.""" from typing import Tuple diff --git a/tests/torch/data_loaders/test_detection_dataloader.py b/tests/torch/data_loaders/test_detection_dataloader.py index f5d60e00..8ca831d9 100644 --- a/tests/torch/data_loaders/test_detection_dataloader.py +++ b/tests/torch/data_loaders/test_detection_dataloader.py @@ -1,4 +1,4 @@ -"""Unit tests for PyTorch Detection Dataset module.""" +"""Unit tests for PyTorch Detection Dataset sub-module.""" from pathlib import Path from typing import Final diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py index c9e092b0..dd24550e 100644 --- a/tests/torch/structures/test_cuboids.py +++ b/tests/torch/structures/test_cuboids.py @@ -1,4 +1,4 @@ -"""Unit tests for PyTorch Cuboids module.""" +"""Unit tests for PyTorch Cuboids sub-module.""" from pathlib import Path from typing import Final, List diff --git a/tests/torch/structures/test_lidar.py b/tests/torch/structures/test_lidar.py index 2a8b942d..f498a221 100644 --- a/tests/torch/structures/test_lidar.py +++ b/tests/torch/structures/test_lidar.py @@ -1,4 +1,4 @@ -"""Unit tests for PyTorch Lidar module.""" +"""Unit tests for PyTorch Lidar sub-module.""" from pathlib import Path from typing import Final diff --git a/tests/torch/structures/test_sweep.py b/tests/torch/structures/test_sweep.py index a8dc684e..e44fe304 100644 --- a/tests/torch/structures/test_sweep.py +++ b/tests/torch/structures/test_sweep.py @@ -1,4 +1,4 @@ -"""Unit tests for PyTorch Cuboids module.""" +"""Unit tests for PyTorch Cuboids sub-module.""" from pathlib import Path from typing import Final From 82687cfca8e38bfea95355641701ffa136c5f978 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:23:36 -0700 Subject: [PATCH 110/117] Update sweep variables. --- rust/src/data_loader.rs | 44 ++++++++++++++++++++----------- src/av2/_r.pyi | 6 ++--- src/av2/torch/structures/sweep.py | 2 +- 3 files changed, 32 insertions(+), 20 deletions(-) diff --git a/rust/src/data_loader.rs b/rust/src/data_loader.rs index 581b4755..5932dec5 100644 --- a/rust/src/data_loader.rs +++ b/rust/src/data_loader.rs @@ -10,7 +10,10 @@ use pyo3::prelude::*; use pyo3_polars::PyDataFrame; use rayon::slice::ParallelSliceMut; use serde::{Deserialize, Serialize}; -use std::path::{Path, PathBuf}; +use std::{ + path::{Path, PathBuf}, + str::FromStr, +}; use anyhow::Result; use bincode::{deserialize, serialize}; @@ -28,9 +31,6 @@ const MIN_NUM_LIDAR_PTS: u64 = 1; /// Data associated with a single lidar sweep. #[pyclass] pub struct Sweep { - /// Ground truth annotations. - #[pyo3(get, set)] - pub annotations: Option, /// Ego-vehicle city pose. #[pyo3(get, set)] pub city_pose: PyDataFrame, @@ -40,6 +40,9 @@ pub struct Sweep { /// Log id and nanosecond timestamp (unique identifier). #[pyo3(get, set)] pub sweep_uuid: (String, u64), + /// Ground truth annotations. + #[pyo3(get, set)] + pub cuboids: Option, } /// Encapsulates sensor data associated with a single sweep. @@ -54,10 +57,10 @@ impl Sweep { sweep_uuid: (String, u64), ) -> Sweep { Sweep { - annotations: Some(annotations), city_pose, lidar, sweep_uuid, + cuboids: Some(annotations), } } } @@ -104,18 +107,27 @@ impl DataLoader { num_accumulated_sweeps: usize, memory_mapped: bool, ) -> DataLoader { - let root_dir = Path::new(root_dir); - let file_index = build_file_index(root_dir, dataset_name, dataset_type, split_name); - let current_idx = 0; + let root_dir = PathBuf::from_str(root_dir).unwrap(); + let file_index = PyDataFrame(build_file_index( + root_dir.as_path(), + dataset_name, + dataset_type, + split_name, + )); + + let dataset_name = dataset_name.to_string(); + let dataset_type = dataset_type.to_string(); + let split_name = split_name.to_string(); + let current_index = 0; DataLoader { - root_dir: root_dir.to_path_buf(), - dataset_name: dataset_name.to_string(), - dataset_type: dataset_type.to_string(), - split_name: split_name.to_string(), + root_dir, + dataset_name, + dataset_type, + split_name, num_accumulated_sweeps, memory_mapped, - file_index: PyDataFrame(file_index), - current_index: current_idx, + file_index, + current_index, } } @@ -207,7 +219,7 @@ impl DataLoader { ); // Annotations aren't available for the test set. - let annotations = match self.split_name.as_str() { + let cuboids = match self.split_name.as_str() { "test" => None, _ => Some(self.read_annotations(log_id, timestamp_ns)), }; @@ -217,10 +229,10 @@ impl DataLoader { let sweep_uuid = (log_id.to_string(), timestamp_ns); Sweep { - annotations, city_pose, lidar, sweep_uuid, + cuboids, } } diff --git a/src/av2/_r.pyi b/src/av2/_r.pyi index 8e2e248e..1e61a549 100644 --- a/src/av2/_r.pyi +++ b/src/av2/_r.pyi @@ -1,7 +1,7 @@ """Rust backend typing stubs.""" from dataclasses import dataclass, field -from typing import Tuple +from typing import Optional, Tuple import polars as pl @@ -11,7 +11,7 @@ class DataLoader: dataset_name: str dataset_type: str split_name: str - num_accum_sweeps: int + num_accumulated_sweeps: int memory_map: bool file_index: pl.DataFrame = field(init=False) @@ -21,7 +21,7 @@ class DataLoader: @dataclass class Sweep: - annotations: pl.DataFrame city_pose: pl.DataFrame lidar: pl.DataFrame sweep_uuid: Tuple[str, int] + cuboids: Optional[pl.DataFrame] diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py index dd2c1238..6837c87f 100644 --- a/src/av2/torch/structures/sweep.py +++ b/src/av2/torch/structures/sweep.py @@ -44,7 +44,7 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: Returns: Sweep object. """ - cuboids = Cuboids(_frame=sweep.annotations.to_pandas()) + cuboids = Cuboids(_frame=sweep.cuboids.to_pandas()) city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) lidar = Lidar(sweep.lidar.to_pandas()) return cls(city_SE3_ego=city_SE3_ego, lidar=lidar, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) From 1b76576fa2c5fb1b51eb242f623462516adfe1a0 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:27:33 -0700 Subject: [PATCH 111/117] Minor docstring updates. --- rust/src/data_loader.rs | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/rust/src/data_loader.rs b/rust/src/data_loader.rs index 5932dec5..7e50ad1f 100644 --- a/rust/src/data_loader.rs +++ b/rust/src/data_loader.rs @@ -40,7 +40,7 @@ pub struct Sweep { /// Log id and nanosecond timestamp (unique identifier). #[pyo3(get, set)] pub sweep_uuid: (String, u64), - /// Ground truth annotations. + /// Cuboids associated with the sweep. #[pyo3(get, set)] pub cuboids: Option, } @@ -84,10 +84,10 @@ pub struct DataLoader { /// Number of accumulated lidar sweeps. #[pyo3(get, set)] pub num_accumulated_sweeps: usize, - /// Boolean flag to enable memory-mapped dataframe loading. + /// Boolean flag to enable memory-mapped data-frame loading. #[pyo3(get, set)] pub memory_mapped: bool, - /// Dataframe consisting of `log_id`, `timestamp_ns`, and `city_name`. + /// Data-frame consisting of `log_id`, `timestamp_ns`, and `city_name`. #[pyo3(get, set)] pub file_index: PyDataFrame, /// Current index of the data-loader. From 02ee74b24f10db26e3fc6f1907dd366f28241fee Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:29:57 -0700 Subject: [PATCH 112/117] Add rust warning. --- rust/README.md | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 rust/README.md diff --git a/rust/README.md b/rust/README.md new file mode 100644 index 00000000..6ddaabdf --- /dev/null +++ b/rust/README.md @@ -0,0 +1,3 @@ +# Rust API + +This API is **experimental** and is not intended to be used directly at this time. From 19b5854081a078aca6b65ab83db7d4394716e914 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 16:33:36 -0700 Subject: [PATCH 113/117] Minor docstring updates. --- src/av2/torch/structures/lidar.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/av2/torch/structures/lidar.py b/src/av2/torch/structures/lidar.py index 40d5a8d1..2ca63ecd 100644 --- a/src/av2/torch/structures/lidar.py +++ b/src/av2/torch/structures/lidar.py @@ -1,4 +1,4 @@ -"""PyTorch Lidar Module.""" +"""PyTorch Lidar sub-module.""" from __future__ import annotations From ca24f4fefa1460ad5eb12fb6f973edaed4cf50e1 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 17:12:06 -0700 Subject: [PATCH 114/117] Add init files to test. --- tests/__init__.py | 0 tests/torch/__init__.py | 0 tests/torch/data_loaders/__init__.py | 0 tests/torch/structures/__init__.py | 0 4 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 tests/__init__.py create mode 100644 tests/torch/__init__.py create mode 100644 tests/torch/data_loaders/__init__.py create mode 100644 tests/torch/structures/__init__.py diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/torch/__init__.py b/tests/torch/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/torch/data_loaders/__init__.py b/tests/torch/data_loaders/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/torch/structures/__init__.py b/tests/torch/structures/__init__.py new file mode 100644 index 00000000..e69de29b From 65c9176300c50190cb946aca9f840d90609f686a Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 17:44:53 -0700 Subject: [PATCH 115/117] Update scene flow. --- src/av2/torch/data_loaders/scene_flow.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/av2/torch/data_loaders/scene_flow.py b/src/av2/torch/data_loaders/scene_flow.py index 7a69da0b..54827206 100644 --- a/src/av2/torch/data_loaders/scene_flow.py +++ b/src/av2/torch/data_loaders/scene_flow.py @@ -13,7 +13,7 @@ import av2._r as rust from av2.utils.typing import PathType -from .utils import Sweep +from ..structures.sweep import Sweep logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) @@ -37,12 +37,12 @@ class SceneFlowDataloader(Dataset[Tuple[Sweep, Optional[Sweep]]]): num_accumulated_sweeps: int = 1 memory_mapped: bool = False - _backend: rust.Dataloader = field(init=False) + _backend: rust.DataLoader = field(init=False) _current_idx: int = 0 def __post_init__(self) -> None: """Initialize Rust backend.""" - self._backend = rust.Dataloader( + self._backend = rust.DataLoader( str(self.root_dir), self.dataset_name, "sensor", From c3f66f2fc4ca365485226bc8fb52d7b73883d345 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 18:01:09 -0700 Subject: [PATCH 116/117] Add docstrings + change assert_allclose. --- tests/__init__.py | 1 + tests/torch/__init__.py | 1 + tests/torch/data_loaders/__init__.py | 1 + tests/torch/structures/__init__.py | 1 + tests/torch/structures/test_cuboids.py | 6 +++--- tests/torch/structures/test_lidar.py | 4 ++-- tests/torch/structures/test_utils.py | 6 +++--- 7 files changed, 12 insertions(+), 8 deletions(-) diff --git a/tests/__init__.py b/tests/__init__.py index e69de29b..46816ddf 100644 --- a/tests/__init__.py +++ b/tests/__init__.py @@ -0,0 +1 @@ +"""Tests package.""" diff --git a/tests/torch/__init__.py b/tests/torch/__init__.py index e69de29b..e3de7e3e 100644 --- a/tests/torch/__init__.py +++ b/tests/torch/__init__.py @@ -0,0 +1 @@ +"""Torch tests sub-package.""" diff --git a/tests/torch/data_loaders/__init__.py b/tests/torch/data_loaders/__init__.py index e69de29b..dc883d64 100644 --- a/tests/torch/data_loaders/__init__.py +++ b/tests/torch/data_loaders/__init__.py @@ -0,0 +1 @@ +"""PyTorch Data-loaders tests sub-package.""" diff --git a/tests/torch/structures/__init__.py b/tests/torch/structures/__init__.py index e69de29b..80a1e8ca 100644 --- a/tests/torch/structures/__init__.py +++ b/tests/torch/structures/__init__.py @@ -0,0 +1 @@ +"""PyTorch structures tests.""" diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py index dd24550e..7ad036e1 100644 --- a/tests/torch/structures/test_cuboids.py +++ b/tests/torch/structures/test_cuboids.py @@ -25,12 +25,12 @@ def test_build_cuboids() -> None: cuboids_xyzlwht = cuboids.as_tensor() cuboids_xyzlwh_qwxyz = torch.as_tensor(cuboids_npy) - torch.testing.assert_close(cuboids_xyzlwht[:, :6], cuboids_xyzlwh_qwxyz[:, :6]) + torch.testing.assert_allclose(cuboids_xyzlwht[:, :6], cuboids_xyzlwh_qwxyz[:, :6]) w, x, y, z = cuboids_xyzlwh_qwxyz[:, 6:10].t() _, _, yaw = euler_from_quaternion(w, x, y, z) - torch.testing.assert_close(cuboids_xyzlwht[:, 6], yaw) - torch.testing.assert_close(cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ), cuboids_xyzlwh_qwxyz) + torch.testing.assert_allclose(cuboids_xyzlwht[:, 6], yaw) + torch.testing.assert_allclose(cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ), cuboids_xyzlwh_qwxyz) track_uuid_expected: List[str] = annotations_frame["track_uuid"].to_list() assert cuboids.track_uuid == track_uuid_expected diff --git a/tests/torch/structures/test_lidar.py b/tests/torch/structures/test_lidar.py index f498a221..9993edf6 100644 --- a/tests/torch/structures/test_lidar.py +++ b/tests/torch/structures/test_lidar.py @@ -22,8 +22,8 @@ def test_build_lidar() -> None: lidar_tensor = torch.as_tensor(frame[list(LIDAR_COLUMNS)].to_numpy().astype(np.float32)) lidar = Lidar(frame) - torch.testing.assert_close(lidar.as_tensor(), lidar_tensor) - torch.testing.assert_close( + torch.testing.assert_allclose(lidar.as_tensor(), lidar_tensor) + torch.testing.assert_allclose( lidar.as_tensor( columns=( "y", diff --git a/tests/torch/structures/test_utils.py b/tests/torch/structures/test_utils.py index ae913ee7..189cf180 100644 --- a/tests/torch/structures/test_utils.py +++ b/tests/torch/structures/test_utils.py @@ -34,7 +34,7 @@ def test_tensor_from_frame() -> None: tensor_expected = torch.as_tensor( [[frame.loc[0, "qw"], frame.loc[0, "qx"], frame.loc[0, "qy"], frame.loc[0, "qz"]]] ) - torch.testing.assert_close(tensor, tensor_expected) + torch.testing.assert_allclose(tensor, tensor_expected) def test_SE3_from_frame() -> None: @@ -48,5 +48,5 @@ def test_SE3_from_frame() -> None: city_SE3_ego_expected = Se3(rotation, translation) city_SE3_ego = SE3_from_frame(frame) - torch.testing.assert_close(city_SE3_ego.translation, city_SE3_ego_expected.translation) - torch.testing.assert_close(city_SE3_ego.rotation.matrix(), city_SE3_ego_expected.rotation.matrix()) + torch.testing.assert_allclose(city_SE3_ego.translation, city_SE3_ego_expected.translation) + torch.testing.assert_allclose(city_SE3_ego.rotation.matrix(), city_SE3_ego_expected.rotation.matrix()) From 093faa3b4a89a7f9489d8ed1ec1d651658264d33 Mon Sep 17 00:00:00 2001 From: Benjamin Wilson Date: Sun, 19 Mar 2023 18:43:48 -0700 Subject: [PATCH 117/117] Testing fixes. --- src/av2/torch/structures/sweep.py | 4 +++- tests/torch/structures/test_cuboids.py | 7 ++++--- tests/torch/structures/test_lidar.py | 5 +++-- tests/torch/structures/test_utils.py | 7 ++++--- 4 files changed, 14 insertions(+), 9 deletions(-) diff --git a/src/av2/torch/structures/sweep.py b/src/av2/torch/structures/sweep.py index 6837c87f..1e09af2f 100644 --- a/src/av2/torch/structures/sweep.py +++ b/src/av2/torch/structures/sweep.py @@ -44,7 +44,9 @@ def from_rust(cls, sweep: rust.Sweep) -> Sweep: Returns: Sweep object. """ - cuboids = Cuboids(_frame=sweep.cuboids.to_pandas()) + cuboids: Optional[Cuboids] = None + if sweep.cuboids is not None: + cuboids = Cuboids(_frame=sweep.cuboids.to_pandas()) city_SE3_ego = SE3_from_frame(frame=sweep.city_pose.to_pandas()) lidar = Lidar(sweep.lidar.to_pandas()) return cls(city_SE3_ego=city_SE3_ego, lidar=lidar, sweep_uuid=sweep.sweep_uuid, cuboids=cuboids) diff --git a/tests/torch/structures/test_cuboids.py b/tests/torch/structures/test_cuboids.py index 7ad036e1..1d2dae05 100644 --- a/tests/torch/structures/test_cuboids.py +++ b/tests/torch/structures/test_cuboids.py @@ -7,6 +7,7 @@ import pandas as pd import torch from kornia.geometry.conversions import euler_from_quaternion +from torch.testing._comparison import assert_close from av2.torch import XYZLWH_QWXYZ_COLUMNS from av2.torch.structures.cuboids import CuboidMode, Cuboids @@ -25,12 +26,12 @@ def test_build_cuboids() -> None: cuboids_xyzlwht = cuboids.as_tensor() cuboids_xyzlwh_qwxyz = torch.as_tensor(cuboids_npy) - torch.testing.assert_allclose(cuboids_xyzlwht[:, :6], cuboids_xyzlwh_qwxyz[:, :6]) + assert_close(cuboids_xyzlwht[:, :6], cuboids_xyzlwh_qwxyz[:, :6]) w, x, y, z = cuboids_xyzlwh_qwxyz[:, 6:10].t() _, _, yaw = euler_from_quaternion(w, x, y, z) - torch.testing.assert_allclose(cuboids_xyzlwht[:, 6], yaw) - torch.testing.assert_allclose(cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ), cuboids_xyzlwh_qwxyz) + assert_close(cuboids_xyzlwht[:, 6], yaw) + assert_close(cuboids.as_tensor(cuboid_mode=CuboidMode.XYZLWH_QWXYZ), cuboids_xyzlwh_qwxyz) track_uuid_expected: List[str] = annotations_frame["track_uuid"].to_list() assert cuboids.track_uuid == track_uuid_expected diff --git a/tests/torch/structures/test_lidar.py b/tests/torch/structures/test_lidar.py index 9993edf6..96be6e92 100644 --- a/tests/torch/structures/test_lidar.py +++ b/tests/torch/structures/test_lidar.py @@ -6,6 +6,7 @@ import numpy as np import pandas as pd import torch +from torch.testing._comparison import assert_close from av2.torch import LIDAR_COLUMNS from av2.torch.structures.lidar import Lidar @@ -22,8 +23,8 @@ def test_build_lidar() -> None: lidar_tensor = torch.as_tensor(frame[list(LIDAR_COLUMNS)].to_numpy().astype(np.float32)) lidar = Lidar(frame) - torch.testing.assert_allclose(lidar.as_tensor(), lidar_tensor) - torch.testing.assert_allclose( + assert_close(lidar.as_tensor(), lidar_tensor) + assert_close( lidar.as_tensor( columns=( "y", diff --git a/tests/torch/structures/test_utils.py b/tests/torch/structures/test_utils.py index 189cf180..baaa6a2d 100644 --- a/tests/torch/structures/test_utils.py +++ b/tests/torch/structures/test_utils.py @@ -5,6 +5,7 @@ import torch from kornia.geometry.liegroup import Se3, So3 from kornia.geometry.quaternion import Quaternion +from torch.testing._comparison import assert_close from av2.torch import QWXYZ_COLUMNS, TRANSLATION_COLUMNS from av2.torch.structures.utils import SE3_from_frame, tensor_from_frame @@ -34,7 +35,7 @@ def test_tensor_from_frame() -> None: tensor_expected = torch.as_tensor( [[frame.loc[0, "qw"], frame.loc[0, "qx"], frame.loc[0, "qy"], frame.loc[0, "qz"]]] ) - torch.testing.assert_allclose(tensor, tensor_expected) + assert_close(tensor, tensor_expected) def test_SE3_from_frame() -> None: @@ -48,5 +49,5 @@ def test_SE3_from_frame() -> None: city_SE3_ego_expected = Se3(rotation, translation) city_SE3_ego = SE3_from_frame(frame) - torch.testing.assert_allclose(city_SE3_ego.translation, city_SE3_ego_expected.translation) - torch.testing.assert_allclose(city_SE3_ego.rotation.matrix(), city_SE3_ego_expected.rotation.matrix()) + assert_close(city_SE3_ego.translation, city_SE3_ego_expected.translation) + assert_close(city_SE3_ego.rotation.matrix(), city_SE3_ego_expected.rotation.matrix())

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