File size: 2,753 Bytes
0ea5581 | 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 | #!/usr/bin/env python3
"""Count images/metadata and write data/manifests/inventory.json."""
from __future__ import annotations
import json
from collections import Counter
from pathlib import Path
ROOT = Path("/opt/dlami/nvme/workspace/skin_disease_classification")
RAW = ROOT / "data/raw"
OUT = ROOT / "data/manifests/inventory.json"
IMG_EXT = {".jpg", ".jpeg", ".png", ".bmp", ".tif", ".tiff", ".webp"}
def count_images(path: Path) -> int:
if not path.exists():
return 0
n = 0
for p in path.rglob("*"):
if p.is_file() and p.suffix.lower() in IMG_EXT:
n += 1
return n
def folder_classes(path: Path) -> dict[str, int]:
if not path.exists():
return {}
counts: Counter[str] = Counter()
for p in path.rglob("*"):
if p.is_file() and p.suffix.lower() in IMG_EXT:
rel = p.relative_to(path)
if len(rel.parts) > 1:
counts[rel.parts[0]] += 1
return dict(sorted(counts.items()))
def main() -> None:
inv = {
"skindisnet": {
"images": count_images(RAW / "skindisnet"),
"classes": folder_classes(RAW / "skindisnet"),
},
"pad_ufes_20": {
"images": count_images(RAW / "pad_ufes_20"),
"metadata": str(RAW / "pad_ufes_20/metadata.csv"),
},
"scin": {
"images": count_images(RAW / "scin"),
"cases_csv": str(RAW / "scin/dataset/scin_cases.csv"),
"labels_csv": str(RAW / "scin/dataset/scin_labels.csv"),
},
"fitzpatrick17k": {
"images": count_images(RAW / "fitzpatrick17k"),
"csv": str(RAW / "fitzpatrick17k/fitzpatrick17k.csv"),
},
"ddi": {
"images": count_images(RAW / "ddi"),
},
"ham10000_isic2018_task3": {
"images": count_images(RAW / "ham10000"),
"metadata": str(RAW / "ham10000/HAM10000_metadata.tab"),
},
"isic2016_task3": {"images": count_images(RAW / "isic2016")},
"isic2017_task3_labels_only": {"csvs": [p.name for p in (RAW / "isic2017").glob("*.csv")]},
"isic2019": {"images": count_images(RAW / "isic2019")},
"isic2020": {
"images": count_images(RAW / "isic2020"),
"csvs": [p.name for p in (RAW / "isic2020").glob("*.csv")],
},
"isic2024": {"images": count_images(RAW / "isic2024")},
"milk10k": {"images": count_images(RAW / "milk10k")},
}
OUT.parent.mkdir(parents=True, exist_ok=True)
OUT.write_text(json.dumps(inv, indent=2))
print(json.dumps(inv, indent=2))
print("total_images", sum(v.get("images", 0) for v in inv.values() if isinstance(v, dict)))
if __name__ == "__main__":
main()
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