31 lines
No EOL
1.2 KiB
Python
31 lines
No EOL
1.2 KiB
Python
"""Build/rebuild the nnU-Net raw dataset (Dataset210_NTUH_T1C_PL) from rows jsonl.
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rows: {key, img, label} where img is the NATIVE (unprocessed) T1c nifti and
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label a nifti mask on (or warpable to) that grid. No resampling/cropping/
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normalization is applied here — nnUNetv2_plan_and_preprocess (02) does the
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preprocessing; imagesTr entries are symlinks to the native volumes, labelsTr
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entries are symlinks when already 0/1 on the image grid, else nearest-warped
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+ binarized copies (label fix-up only).
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Usage: python scripts_nnu/01_prepare_dataset.py --rows <rows.jsonl>
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"""
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import argparse
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import os
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import sys
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from src.common import load_jsonl
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from nnu_common import make_raw_dataset, raw_ds
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--rows", required=True, help="jsonl with {key, img, label} (native paths)")
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args = ap.parse_args()
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rows = load_jsonl(args.rows)
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n = make_raw_dataset(rows)
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print(f"[nnu:prepare] {raw_ds()}: {n} cases", flush=True)
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if __name__ == "__main__":
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main() |