File size: 10,662 Bytes
08764e9 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 | """Download the dataset from HuggingFace, unzip, and build a case manifest.
Usage:
python -m toothcanal.download --config configs/default.yaml
On AutoDL (China) you may want a mirror:
export HF_ENDPOINT=https://hf-mirror.com
"""
import os, glob, zipfile, argparse, re
from .utils import load_config, ensure_dir, numeric_id, write_json
def _safe_extract(zip_path, dest):
"""Extract a zip, fixing common CJK filename mojibake (cp437 -> gbk/utf-8)."""
with zipfile.ZipFile(zip_path) as zf:
for info in zf.infolist():
name = info.filename
raw = name.encode("cp437", errors="ignore")
for enc in ("gbk", "utf-8"):
try:
name = raw.decode(enc)
break
except Exception:
continue
target = os.path.join(dest, name)
if info.is_dir() or name.endswith("/"):
ensure_dir(target)
continue
ensure_dir(os.path.dirname(target))
with zf.open(info) as src, open(target, "wb") as out:
out.write(src.read())
def download_and_extract(cfg, only_substrings=None):
from huggingface_hub import HfApi, hf_hub_download
repo = cfg["paths"]["hf_repo"]
raw_dir = ensure_dir(cfg["paths"]["raw_dir"])
api = HfApi()
files = api.list_repo_files(repo_id=repo, repo_type="dataset")
zips = [f for f in files if f.lower().endswith(".zip")]
skips = cfg["paths"].get("skip_zip_substrings", [])
zips = [f for f in zips if not any(s in f for s in skips)]
if only_substrings:
zips = [f for f in zips if any(s in f for s in only_substrings)]
print(f"[download] using {len(zips)} zip files (skipped {skips}, only={only_substrings}): {zips}")
for zf in zips:
print(f"[download] fetching {zf} ...")
local = hf_hub_download(repo_id=repo, repo_type="dataset", filename=zf,
local_dir=os.path.join(raw_dir, "_zips"))
print(f"[download] extracting {os.path.basename(local)} ...")
_safe_extract(local, raw_dir)
return raw_dir
def _build_image_from_dicom(folder):
"""Read all *.dcm in `folder`, write image_from_dicom.nii.gz, return its path."""
import SimpleITK as sitk, glob as _g
dcm_files = sorted(_g.glob(os.path.join(folder, "*.dcm")))
if len(dcm_files) < 8:
return None
reader = sitk.ImageSeriesReader()
try:
ids = reader.GetGDCMSeriesIDs(folder)
if ids:
# pick the largest series (most slices)
best_files, best_n = None, -1
for sid in ids:
fnames = reader.GetGDCMSeriesFileNames(folder, sid)
if len(fnames) > best_n:
best_n, best_files = len(fnames), fnames
reader.SetFileNames(best_files)
else:
reader.SetFileNames(dcm_files)
img = reader.Execute()
except Exception:
return None
out = os.path.join(folder, "image_from_dicom.nii.gz")
sitk.WriteImage(img, out)
return out
def _pick_label_in(folder):
"""Among nii.gz files in `folder` (excluding image_from_dicom), pick the most
likely label: prefer the canonical filename if present, else the LARGEST file
(the duplicate 01.nii.gz / 31.nii.gz pair are usually the same content, but
sometimes 01.nii.gz is a symlink/older copy)."""
canonical = os.path.join(folder, "zzz21_tooth_mask_3ik3_label_adjust.nii.gz")
if os.path.exists(canonical):
return canonical
cands = [p for p in glob.glob(os.path.join(folder, "*.nii.gz"))
if os.path.basename(p) != "image_from_dicom.nii.gz"]
if not cands:
return None
# follow symlinks; pick the one with the largest real size
return max(cands, key=lambda p: os.path.getsize(os.path.realpath(p)))
def _series_uid_dir_to_case_name(folder, raw_dir):
"""Pick the case-folder name by scanning relpath segments. The DEEPEST segment
that is purely numeric (optionally followed by trailing dashes) and in 1..40
is the case folder. Earlier batch folders like '1-20' are NOT pure-numeric
(they contain a dash between two digits) so they won't match `\\d+-*`."""
rel = os.path.relpath(folder, raw_dir).split(os.sep)
chosen = None
for seg in rel:
m = re.fullmatch(r"0*(\d+)-*", seg)
if m and 1 <= int(m.group(1)) <= 40:
chosen = seg
return chosen or os.path.basename(os.path.dirname(folder))
def _find_label_for(folder, raw_dir, case_num):
"""Look for the label .nii.gz file for this case. Strategy:
1. Same folder as the DICOMs.
2. Walk up to the CASE folder (whose name starts with case_num) and
search every .nii.gz inside it (excluding image_from_dicom).
3. If still nothing, look in sibling 'case/' summary folders one level
up from the case (e.g. data/raw/21-30/21-30/zzz027.nii.gz).
"""
canonical = "zzz21_tooth_mask_3ik3_label_adjust.nii.gz"
def _ok(p):
return os.path.basename(p) != "image_from_dicom.nii.gz"
# 1. same folder
here = [p for p in glob.glob(os.path.join(folder, "*.nii.gz")) if _ok(p)]
if here:
return max(here, key=lambda p: os.path.getsize(os.path.realpath(p)))
# 2. walk up to the case folder
cur = folder
while True:
parent = os.path.dirname(cur)
if parent == raw_dir or parent == cur:
break
cur = parent
m = re.match(r"0*(\d+)", os.path.basename(cur))
if m and int(m.group(1)) == case_num:
cands = [p for p in glob.glob(os.path.join(cur, "**", "*.nii.gz"),
recursive=True) if _ok(p)]
if cands:
# prefer one whose filename contains the case number
preferred = [p for p in cands if str(case_num) in os.path.basename(p)
or canonical in os.path.basename(p)]
pool = preferred or cands
return max(pool, key=lambda p: os.path.getsize(os.path.realpath(p)))
break
return None
def discover_cases(raw_dir):
"""Find all CBCT cases under raw_dir. A case = the directory directly
containing the DICOM slices (>=8 .dcm files), OR a directory with an
explicit image_from_dicom.nii.gz. Labels are searched in the same folder,
then up the directory tree to the case-numbered ancestor."""
cases = {}
explicit_imgs = glob.glob(os.path.join(raw_dir, "**", "image_from_dicom.nii.gz"),
recursive=True)
candidate_dirs = set()
for p in explicit_imgs:
candidate_dirs.add(os.path.dirname(p))
# any directory with >=8 .dcm files is a DICOM series
for folder, dirs, files in os.walk(raw_dir):
# skip hidden and the HF cache
parts = folder.split(os.sep)
if any(seg.startswith(".") or seg == "_zips" for seg in parts):
dirs[:] = []
continue
n_dcm = sum(1 for f in files if f.lower().endswith(".dcm"))
if n_dcm >= 8:
candidate_dirs.add(folder)
for folder in sorted(candidate_dirs):
# derive a stable case id and a numeric case number from the path.
# The path may look like raw/1-20/01-/20230519/<series_uid>/ so the FIRST
# segment with a number (`1-20`) is the batch folder, not the case. We want
# the DEEPEST segment whose name parses as a single number in 1..40 — that's
# the actual case folder.
rel = os.path.relpath(folder, raw_dir).split(os.sep)
case_num = -1
case_name = None
for seg in rel:
m = re.fullmatch(r"0*(\d+)-*", seg) # purely numeric + trailing dashes
if m and 1 <= int(m.group(1)) <= 40:
case_num = int(m.group(1))
case_name = seg # keep updating -> deepest wins
if case_num < 0:
print(f"[discover] cannot infer case number from {folder}; skipping")
continue
# if multiple series exist under the same case (rare here), keep only the
# largest one (most DICOM slices)
prev = cases.get(case_name)
n_dcm = sum(1 for f in os.listdir(folder) if f.lower().endswith(".dcm"))
if prev is not None and prev.get("n_dcm", 0) >= n_dcm and prev.get("has_real_dcm", True):
continue
# build image_from_dicom if not already present
img_path = os.path.join(folder, "image_from_dicom.nii.gz")
if not os.path.exists(img_path):
if n_dcm >= 8:
print(f"[discover] {case_name}: building image_from_dicom.nii.gz "
f"from {n_dcm} DICOM slices in {folder} ...")
built = _build_image_from_dicom(folder)
if built is None:
print(f"[discover] {folder}: DICOM read failed, skipping.")
continue
img_path = built
else:
continue
label = _find_label_for(folder, raw_dir, case_num)
if label is None:
print(f"[discover] {case_name}: no label .nii.gz found anywhere in "
f"its subtree, skipping.")
continue
cases[case_name] = dict(image=img_path, label=label, num=case_num,
n_dcm=n_dcm, has_real_dcm=True)
cases = {k: {kk: vv for kk, vv in v.items() if kk not in ("n_dcm", "has_real_dcm")}
for k, v in sorted(cases.items(), key=lambda kv: kv[1]["num"])}
print(f"[discover] found {len(cases)} cases: {[c for c in cases]}")
return cases
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--config", default="configs/default.yaml")
ap.add_argument("--skip_download", action="store_true",
help="only (re)build manifest from already-extracted raw_dir")
ap.add_argument("--only_zips", nargs="*", default=None,
help="only fetch zips whose name contains any of these substrings "
"(e.g. --only_zips 31-35 for the smoke test)")
args = ap.parse_args()
cfg = load_config(args.config)
if not args.skip_download:
download_and_extract(cfg, only_substrings=args.only_zips)
cases = discover_cases(cfg["paths"]["raw_dir"])
if not cases:
raise SystemExit("No cases found. Check raw_dir / extraction.")
write_json(cases, os.path.join(cfg["paths"]["raw_dir"], "manifest.json"))
print(f"[download] manifest written with {len(cases)} cases.")
if __name__ == "__main__":
main()
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