README.md

metadata

license: cc-by-nc-sa-4.0
pretty_name: Pathomics

Step 3 — Install Dependencies

pip install huggingface-hub pandas

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Step 4 — Login

from huggingface_hub import login

login(token="YOUR_HF_TOKEN")

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Download Script

from huggingface_hub import snapshot_download
import pandas as pd
import os


def download_pathomics(
    ids=None,
    pathomics_dir="pathomics_data",
    hest_dir="pathomics_data",
):

    # -----------------------------
    # load metadata index
    # -----------------------------
    meta = None
    
    csv_files = [f for f in os.listdir(pathomics_dir)
                 if f.startswith("PATHOMICS_v")]

    # print(csv_files)

    if len(csv_files) > 0:
        csv_path = os.path.join(pathomics_dir, sorted(csv_files)[-1])
        meta = pd.read_csv(csv_path)

    if ids is None:
        snapshot_download(
            repo_id="Boyoungc/pathomics",
            allow_patterns="*",
            repo_type="dataset",
            local_dir=pathomics_dir,
        )
        return

    # -----------------------------
    # split ids
    # -----------------------------
    hest_ids = []
    local_ids = []

    if meta is not None and "source" in meta.columns:
        sub = meta[meta["id"].isin(ids)]
        hest_ids = sub[sub["source"] == "hest"]["id"].tolist()
        local_ids = sub[sub["source"] != "hest"]["id"].tolist()
    else:
        local_ids = ids

    # =========================================================
    # 1. HEST DOWNLOAD (STRICT MODALITY FILTER)
    # =========================================================
    if len(hest_ids) > 0:

        hest_patterns = []
    
        for hid in hest_ids:
            hest_patterns.extend([
                f"metadata/{hid}.json",
                f"st/{hid}.h5ad",
                f"wsis/{hid}.tif",
                f"thumbnails/{hid}_*",
                f"spatial_plots/{hid}_*",
            ])
    
        snapshot_download(
            repo_id="MahmoodLab/hest",
            allow_patterns=hest_patterns,
            repo_type="dataset",
            local_dir=hest_dir,
        )
    
        print(f"[HEST] downloaded {len(hest_ids)} samples")

    # =========================================================
    # 2. PATHOMICS SEG ONLY for HEST
    # =========================================================
    if len(hest_ids) > 0:

        seg_patterns = [
            f"cellvit_seg_for_superfocus/{hid}/**"
            for hid in hest_ids
        ]

        snapshot_download(
            repo_id="Boyoungc/pathomics",
            allow_patterns=seg_patterns,
            repo_type="dataset",
            local_dir=pathomics_dir,
        )

        print(f"[SEG] downloaded HEST segmentations")

    # =========================================================
    # 3. PATHOMICS FULL for literature
    # =========================================================
    if len(local_ids) > 0:

        patterns = []

        for sid in local_ids:
            patterns.extend([
                f"metadata/{sid}.json",
                f"st/{sid}.h5ad",
                f"wsis/{sid}.tif",
                f"thumbnails/{sid}_*",
                f"spatial_plots/{sid}_*",
                f"cellvit_seg_for_superfocus/{sid}/**",
            ])

        snapshot_download(
            repo_id="Boyoungc/pathomics",
            allow_patterns=patterns,
            repo_type="dataset",
            local_dir=pathomics_dir,
        )

        print(f"[PATHOMICS] downloaded literature samples")

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Usage Examples

Download One Sample

download_pathomics(
    ids=["NCBI689"]
)

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Download Multiple Samples

download_pathomics(
    ids=["NCBI689", "MEND62"]
)

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Download Entire Dataset

download_pathomics()

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Download Only ST Data

download_pathomics(
    ids=["NCBI689"],
    modalities=["st"]
)

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