soorena62
56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
import os
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import pysera
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from api.module import Module
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from api.io_port import InPort, OutPort, NIFTIImageType, CSVTableType
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def factory():
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m = Module("PySERAExtractor")
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in_image = InPort("image", NIFTIImageType())
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in_mask = InPort("mask", NIFTIImageType())
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out_features = OutPort("features", CSVTableType(columns=["name", "value"]))
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m.add_in_port(in_image)
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m.add_in_port(in_mask)
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m.add_out_port(out_features)
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def execute(inputs):
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image_input = inputs["image"]
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mask_input = inputs["mask"]
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output_dir = "results"
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os.makedirs(output_dir, exist_ok=True)
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result = pysera.process_batch(
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image_input=image_input,
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mask_input=mask_input,
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output_path=output_dir,
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num_workers="auto",
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enable_parallelism=True,
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apply_preprocessing=True,
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categories="all",
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dimensions="1st,2_5d,3d",
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feature_value_mode="REAL_VALUE",
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extraction_mode="handcrafted_feature",
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report="info",
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)
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df = result.get("features_extracted")
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features = []
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if df is not None:
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for idx, row in df.iterrows():
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features.append({
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"name": row[0],
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"value": row[1]
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})
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return {
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"features": features
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}
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m.execute = execute
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return m
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