#!/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()