Datasets:
Download scripts/to_pixcell_layout.py from srikarym/PixCell-training-data: direct link, hf CLI and curl.
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- Download file 1.82 kB
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https://huggingface.co/datasets/srikarym/PixCell-training-data/resolve/main/scripts/to_pixcell_layout.py
- Command line
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hf download hf://datasets/srikarym/PixCell-training-data/scripts/to_pixcell_layout.py
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curl -L -o to_pixcell_layout.py https://huggingface.co/datasets/srikarym/PixCell-training-data/resolve/main/scripts/to_pixcell_layout.py
1.82 kB
| """Unpack PixCell-training-data Parquet shards into the folder layout used by the PixCell training code. | |
| python to_pixcell_layout.py --hf_dir <snapshot dir> --out <root> [--sources tcga_diagnostic gtex ...] | |
| Writes <root>/patches/<src>/<subtype>/single_1024/<slide_id>/<col>_<row>.jpeg (original JPEG bytes) | |
| and <root>/patches/metadata/patch_names_all.hdf5 with one key per source (e.g. "tcga_diagnostic_1024"). | |
| Note: PTRC-HGSOC lives under "others/" (key "others_1024"), matching the original layout. | |
| """ | |
| import argparse | |
| from collections import defaultdict | |
| from pathlib import Path | |
| import h5py | |
| import pyarrow.parquet as pq | |
| from tqdm import tqdm | |
| p = argparse.ArgumentParser() | |
| p.add_argument("--hf_dir", type=Path, required=True) | |
| p.add_argument("--out", type=Path, required=True) | |
| p.add_argument("--sources", nargs="*", default=None) | |
| args = p.parse_args() | |
| patches = args.out / "patches" | |
| names = defaultdict(list) | |
| sources = args.sources or sorted(d.name for d in (args.hf_dir / "data").iterdir()) | |
| for source in sources: | |
| for f in tqdm(sorted((args.hf_dir / "data" / source).glob("*.parquet")), desc=source): | |
| for batch in pq.ParquetFile(f).iter_batches(columns=["image"], batch_size=256): | |
| for img in batch.column("image").to_pylist(): | |
| dst = patches / img["path"] | |
| dst.parent.mkdir(parents=True, exist_ok=True) | |
| dst.write_bytes(img["bytes"]) | |
| names[img["path"].split("/")[0] + "_1024"].append(img["path"]) | |
| (patches / "metadata").mkdir(parents=True, exist_ok=True) | |
| with h5py.File(patches / "metadata/patch_names_all.hdf5", "a") as h5: | |
| for key, paths in names.items(): | |
| if key in h5: | |
| del h5[key] | |
| h5.create_dataset(key, data=paths, dtype=h5py.string_dtype()) | |
| print({k: len(v) for k, v in names.items()}) | |