File size: 5,793 Bytes
e37c13d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 | """Episode build: source H5 -> published videos + per-frame parquet.
from react_preprocess import pipeline
pipeline.build_episode(Path(".../episode_000.h5"), task="pushT")
Output layout (mirrors the HF dataset):
<stage>/<task>/videos/<date>/<episode>/{view_*,tactile_*}.mp4
<stage>/<task>/depth/<date>/<episode>/depth_*.mkv (--with-depth)
<stage>/<task>/meta/<date>/<episode>.parquet
<stage>/<task>/meta/<date>/<episode>._detect.pt (quality sidecar)
"""
from __future__ import annotations
import time
from dataclasses import dataclass
from pathlib import Path
import h5py
import hdf5plugin # noqa: F401 (registers BLOSC for the recorded files)
import numpy as np
from . import meta as meta_mod
from .config import CAM_STREAM, CHUNK, GEL_STREAM, SIDES, stage_dirs
from .encode import depth_writer, rgb_writer
from .h5io import open_episode
from .tactile import process_side
@dataclass
class BuildReport:
episode: str
status: str
timestamped: bool = False
duration_s: float = 0.0
detail: str = ""
def __str__(self):
return f"{self.episode}: {self.status}" + (f" — {self.detail}" if self.detail else "")
def _encode_cameras(f, source, video_dir: Path) -> None:
for cam_idx, name in CAM_STREAM.items():
key = f"realsense/cam{cam_idx}/color"
if key not in f:
continue
ds = f[key] # (N, H, W, 3) BGR
with rgb_writer(video_dir / f"{name}.mp4") as w:
for s in range(0, source.T, CHUNK):
e = min(s + CHUNK, source.T)
w.write(ds[source.trim + s:source.trim + e])
def _encode_depth(f, source, depth_dir: Path) -> int:
written = 0
for cam_idx, name in CAM_STREAM.items():
key = f"realsense/cam{cam_idx}/depth"
if key not in f:
continue
ds = f[key] # (N, H, W) uint16 mm
out = depth_dir / f"{name.replace('view_', 'depth_')}.mkv"
with depth_writer(out) as w:
for s in range(0, source.T, CHUNK):
e = min(s + CHUNK, source.T)
w.write(np.asarray(ds[source.trim + s:source.trim + e], np.uint16))
written += 1
return written
def _object_pose(f, source) -> np.ndarray | None:
"""Nearest-timestamp pose of the manipulated object, if it was tracked."""
from .h5io import cam_align_poses
for body in (source.task, "object", "motherboard"):
grp = f"optitrack/{body}"
if grp in f and len(f[f"{grp}/timestamps"]) > 0:
pose = cam_align_poses(source.trimmed_cam_ts,
f[f"{grp}/timestamps"][:], f[f"{grp}/pose"][:]).copy()
off = source.world_offset
pose[:, 0] += off[0]; pose[:, 1] += off[1]; pose[:, 2] += off[2]
return pose
return np.full((source.T, 7), np.nan, np.float32)
def _write_detect_sidecar(path: Path, source, tactile) -> None:
"""Small torch sidecar consumed by the quality detector."""
import torch
torch.save({
"timestamps": torch.from_numpy(source.trimmed_cam_ts.astype(np.float64)),
"sensor_left_pose": torch.from_numpy(source.pose_left),
"sensor_right_pose": torch.from_numpy(source.pose_right),
"tactile_left_intensity": torch.from_numpy(tactile["left"].intensity),
"tactile_right_intensity": torch.from_numpy(tactile["right"].intensity),
"_contact_meta": {
"trim_offset": int(source.trim),
"active_sensors": source.active,
"ref_p01_idx_left": int(tactile["left"].ref_index),
"ref_p01_idx_right": int(tactile["right"].ref_index),
"world_frame_offset_applied": list(source.world_offset),
"tactile_timestamped": bool(source.timestamped),
"tactile_stats": {s: tactile[s].stats for s in SIDES},
},
}, str(path))
def build_episode(h5_path: Path, task: str, force: bool = False,
with_depth: bool = False, encode_video: bool = True) -> BuildReport:
"""Build every published artefact for one source recording."""
h5_path = Path(h5_path)
t0 = time.time()
try:
source = open_episode(h5_path, task)
except Exception as exc: # noqa: BLE001
return BuildReport(h5_path.stem, "FAIL", detail=f"unreadable ({exc})")
video_dir, meta_dir = stage_dirs(task, source.date, source.episode)
pq_path = meta_dir / f"{source.episode}.parquet"
if pq_path.exists() and not force:
return BuildReport(source.episode, "skipped", detail="already built")
with h5py.File(str(h5_path), "r") as f:
if encode_video:
_encode_cameras(f, source, video_dir)
tactile = {
side: process_side(f, side, source.align[side],
video_dir / f"{GEL_STREAM[side]}.mp4",
encode=encode_video)
for side in SIDES
}
obj_pose = _object_pose(f, source)
if with_depth:
depth_dir = video_dir.parent.parent.parent / "depth" / source.date / source.episode
_encode_depth(f, source, depth_dir)
table = meta_mod.build_table(source, tactile, obj_pose)
meta_mod.write_table(table, pq_path)
_write_detect_sidecar(meta_dir / f"{source.episode}._detect.pt", source, tactile)
lstat = tactile["left"].stats
detail = (f"T={source.T} "
f"{'timestamped' if source.timestamped else 'legacy'} "
f"tactile {lstat['effective_fps']:.1f}fps "
f"({lstat['duplicate_ratio']*100:.0f}% dup)")
return BuildReport(source.episode, "OK", source.timestamped,
time.time() - t0, detail)
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