sea_scenes/loaders.py

from pathlib import Path
from typing import Any, List, Tuple
import struct

import numpy as np
import cv2

from .types import Vector3, Quaternion, Keypoint


def load_frames(frames_path: Path) -> List[Tuple[int, np.ndarray]]:
    """Load encoded frames from a SEA stereo .dat file."""
    frames: List[Tuple[int, np.ndarray]] = []

    header_size = 8 + 8 + 4

    with open(frames_path, "rb") as f:
        while True:
            header = f.read(header_size)
            if len(header) < header_size:
                break

            frame_timestamp, frame_index, frame_size = struct.unpack(">qqi", header)
            frame_bytes = f.read(frame_size)

            if len(frame_bytes) != frame_size:
                raise EOFError("Unexpected EOF while reading frame data")

            frame_array = np.frombuffer(frame_bytes, dtype=np.uint8)
            frame = cv2.imdecode(frame_array, cv2.IMREAD_COLOR)
            if frame is not None:
                frames.append((frame_timestamp, frame))

    return frames


def load_depth(depth_dir: Path) -> list[tuple[int, np.ndarray]]:
    """Load depth from .npy files: <timestamp>_depth_meter.npy."""
    depth_frames: list[tuple[int, np.ndarray]] = []

    for path in sorted(depth_dir.glob("*_depth_meter.npy")):
        timestamp = int(path.stem.split("_")[0])

        depth = np.load(path).astype(np.float32)
        depth_frames.append((timestamp, depth))

    return depth_frames


def load_trajectory(trajectory_path: Path) -> List[Tuple[int, np.ndarray, np.ndarray]]:
    """Load camera trajectory from SEA binary trajectory file."""
    trajectory: List[Tuple[int, np.ndarray, np.ndarray]] = []

    trajectory_buffer_size = 8 + 7 * 4

    with open(trajectory_path, "rb") as f:
        while True:
            trajectory_buffer = f.read(trajectory_buffer_size)
            if len(trajectory_buffer) < trajectory_buffer_size:
                break

            timestamp = struct.unpack("<q", trajectory_buffer[:8])[0]
            pos_x, pos_y, pos_z, quat_x, quat_y, quat_z, quat_w = struct.unpack("<7f", trajectory_buffer[8:])

            pos = np.array([pos_x, pos_y, pos_z], dtype=np.float32)
            quat = np.array([quat_x, quat_y, quat_z, quat_w], dtype=np.float32)

            trajectory.append((timestamp, pos, quat))

    return trajectory


def load_body_data(body_data_path: Path) -> List[Any]:
    """Load body tracking data from SEA binary body_data file."""
    body_frames: List[Any] = []

    header_size = 8 + 4

    with open(body_data_path, "rb") as f:
        while True:
            header = f.read(header_size)
            if len(header) < header_size:
                break

            timestamp, keypoint_count = struct.unpack("<qi", header)
            keypoints = _read_keypoints(f, keypoint_count)[:70]

            body_frames.append(
                (
                    timestamp,
                    keypoints
                )
            )

    return body_frames


def load_hand_data(hand_data_path: Path) -> List[Any]:
    """Load hand tracking data from SEA binary hand_data file."""
    hand_frames: List[Any] = []

    timestamp_buffer_size = 8
    left_count_buffer_size = 4
    right_count_buffer_size = 4

    with open(hand_data_path, "rb") as f:
        while True:
            timestamp_buffer = f.read(timestamp_buffer_size)
            if len(timestamp_buffer) < timestamp_buffer_size:
                break
            timestamp = struct.unpack("<q", timestamp_buffer)[0]

            left_count_buffer = f.read(left_count_buffer_size)
            if len(left_count_buffer) < left_count_buffer_size:
                break
            left_count = struct.unpack("<i", left_count_buffer)[0]
            left_keypoints = _read_keypoints(f, left_count)

            right_count_buffer = f.read(right_count_buffer_size)
            if len(right_count_buffer) < right_count_buffer_size:
                break
            right_count = struct.unpack("<i", right_count_buffer)[0]
            right_keypoints = _read_keypoints(f, right_count)

            hand_frames.append(
                (
                    timestamp,
                    left_keypoints if left_keypoints else None,
                    right_keypoints if right_keypoints else None,
                )
            )

    return hand_frames


def _read_keypoints(f: Any, keypoint_count: int) -> List[Keypoint]:
    if keypoint_count <= 0:
        return []

    floats_per_keypoint = 7
    total_float_count = keypoint_count * floats_per_keypoint
    bytes_per_float = 4
    expected_byte_count = total_float_count * bytes_per_float

    raw_bytes = f.read(expected_byte_count)

    if len(raw_bytes) != expected_byte_count:
        raise EOFError("Unexpected EOF while reading keypoint data")

    float_values = struct.unpack("<" + "f" * total_float_count, raw_bytes)

    keypoints: List[Keypoint] = []

    for keypoint_index in range(keypoint_count):
        base_index = keypoint_index * floats_per_keypoint
        pos_x, pos_y, pos_z, quat_x, quat_y, quat_z, quat_w = float_values[
            base_index : base_index + floats_per_keypoint
        ]

        keypoints.append(
            Keypoint(
                position=Vector3(pos_x, pos_y, pos_z),
                rotation=Quaternion(quat_x, quat_y, quat_z, quat_w),
            )
        )

    return keypoints