Datasets:
Tasks:
Robotics
Formats:
json
Languages:
English
Size:
< 1K
Tags:
tactile-sensing
electronic-skin
deformation-response
tactile-time-series
time-series-classification
inary-classification
License:
File size: 3,759 Bytes
cc858da | 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 | #!/usr/bin/env python3
import json
import math
from pathlib import Path
import numpy as np
ROOT = Path(".")
DATA_DIR = ROOT / "data"
META_DIR = ROOT / "metadata"
SPLITS = {
"train": "train",
"val": "validation",
"validation": "validation",
"test": "test",
}
EXPECTED_SHAPE = (64, 32, 32)
EXPECTED_DTYPE = np.float32
def read_json(path: Path) -> dict:
with path.open("r", encoding="utf-8") as f:
return json.load(f)
def parse_stiffness(value):
if value is None:
return None
if isinstance(value, (int, float)) and math.isfinite(float(value)):
return float(value)
raise ValueError(f"invalid stiffness: {value!r}")
def get_label(targets: dict):
# 兼容旧字段 rigidity，新字段 deformation_response 优先。
if "deformation_response" in targets:
label = targets["deformation_response"]
elif "rigidity" in targets:
label = targets["rigidity"]
else:
raise ValueError("missing targets.deformation_response or targets.rigidity")
if label not in ("rigid", "deformable"):
raise ValueError(f"invalid deformation label: {label!r}")
return label
def inspect_npz(npz_path: Path):
with np.load(npz_path, allow_pickle=False) as z:
if "frames" not in z.files:
raise ValueError(f"missing key 'frames', keys={z.files}")
frames = z["frames"]
shape = tuple(frames.shape)
dtype = frames.dtype
if shape != EXPECTED_SHAPE:
raise ValueError(f"bad shape {shape}, expected {EXPECTED_SHAPE}")
if dtype != EXPECTED_DTYPE:
raise ValueError(f"bad dtype {dtype}, expected float32")
return shape, str(dtype)
def main():
META_DIR.mkdir(parents=True, exist_ok=True)
summary = {}
for folder_name, split_name in SPLITS.items():
split_dir = DATA_DIR / folder_name
if not split_dir.exists():
continue
rows = []
errors = []
for npz_path in sorted(split_dir.glob("*.npz")):
json_path = npz_path.with_suffix(".json")
if not json_path.exists():
errors.append(f"{npz_path.name}: missing json")
continue
try:
meta = read_json(json_path)
targets = meta.get("targets", {})
shape, dtype = inspect_npz(npz_path)
row = {
"file_name": npz_path.name,
"npz_path": str(npz_path.as_posix()),
"json_path": str(json_path.as_posix()),
"sample_id": meta.get("sample_id"),
"specimen_id": meta.get("specimen_id"),
"deformation_response": get_label(targets),
"stiffness": parse_stiffness(targets.get("stiffness")),
"num_frames": shape[0],
"height": shape[1],
"width": shape[2],
"dtype": dtype,
"split": split_name,
}
rows.append(row)
except Exception as exc:
errors.append(f"{npz_path.name}: {exc}")
out_path = META_DIR / f"{split_name}.jsonl"
with out_path.open("w", encoding="utf-8") as f:
for row in rows:
f.write(json.dumps(row, ensure_ascii=False, allow_nan=False) + "\n")
summary[split_name] = {
"samples": len(rows),
"errors": errors,
}
with (META_DIR / "summary.json").open("w", encoding="utf-8") as f:
json.dump(summary, f, indent=2, ensure_ascii=False, allow_nan=False)
print(json.dumps(summary, indent=2, ensure_ascii=False))
if __name__ == "__main__":
main() |