73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
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# done with GWJU7LPC-20201007
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import logging
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import os
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import shutil
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from monai.apps.nnunet import nnUNetV2Runner
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import yaml
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DATASET="Dataset2602_BraTS-CK"
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YAML ="2602.yaml"
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DST_DIR="/mnt/t24/Public/kimo/raw/ensemble_predictions_postprocessed"
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def copytree(src, dst):
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os.makedirs(dst, exist_ok=True)
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for root, dirs, files in os.walk(src):
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for file in files:
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src_file = os.path.join(root, file)
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dst_file = os.path.join(dst, file)
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shutil.copyfile(src_file, dst_file)
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def main():
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FORMAT = '%(asctime)s [%(filename)s:%(lineno)d] %(message)s'
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logging.basicConfig(
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level=logging.INFO,
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format=FORMAT,
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handlers=[
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logging.StreamHandler(),
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# logging.FileHandler(__file__.replace('.py','.%s.log'%str(datetime.datetime.now()).replace(':','')), encoding='utf-8')
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logging.FileHandler(__file__.replace('.py','.log'), encoding='utf-8')
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]
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)
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with open(YAML, "r") as f:
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config = yaml.safe_load(f)
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PREPROCESSED_DIR = config["nnunet_preprocessed"]
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RESULTS_DIR = config["nnunet_results"]
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# clean up
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shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/pred_2d', ignore_errors=True)
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shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/pred_3d_fullres', ignore_errors=True)
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shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/pred_3d_lowres', ignore_errors=True)
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shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/ensemble_predictions', ignore_errors=True)
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shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/ensemble_predictions_postprocessed', ignore_errors=True)
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runner = nnUNetV2Runner(YAML)
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try:
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runner.predict_ensemble_postprocessing(
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# num_processes_preprocessing=1,
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# num_processes_segmentation_export=1
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)
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except Exception as e:
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logging.exception(e)
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exit()
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copytree(f'{RESULTS_DIR}/{DATASET}/ensemble_predictions_postprocessed', DST_DIR)
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# exit()
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# clean up
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# shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/pred_2d', ignore_errors=True)
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# shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/pred_3d_fullres', ignore_errors=True)
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# shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/pred_3d_lowres', ignore_errors=True)
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# shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/ensemble_predictions', ignore_errors=True)
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# shutil.rmtree(f'{RESULTS_DIR}/{DATASET}/ensemble_predictions_postprocessed', ignore_errors=True)
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if __name__ == "__main__":
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main()
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