Update rsna-atd.py
Browse files- rsna-atd.py +31 -31
rsna-atd.py
CHANGED
@@ -33,27 +33,27 @@ class RSNAATD(datasets.GeneratorBasedBuilder):
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"patient_id": datasets.Value("int64"),
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"series_id": datasets.Value("int64"),
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"image": datasets.Array3D(shape=(None, 512, 512), dtype="uint8"),
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"mask": datasets.Array3D(shape=(None, 512, 512), dtype="uint8"),
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"aortic_hu": datasets.Value("float64"),
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"incomplete_organ": datasets.Value("int64"),
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"bowel_healthy": datasets.Value("int64"),
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"bowel_injury": datasets.Value("int64"),
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"extravasation_healthy": datasets.Value("int64"),
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"extravasation_injury": datasets.Value("int64"),
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"kidney_healthy": datasets.Value("int64"),
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"kidney_low": datasets.Value("int64"),
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"kidney_high": datasets.Value("int64"),
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"liver_healthy": datasets.Value("int64"),
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"liver_low": datasets.Value("int64"),
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"liver_high": datasets.Value("int64"),
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"spleen_healthy": datasets.Value("int64"),
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"spleen_low": datasets.Value("int64"),
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"spleen_high": datasets.Value("int64"),
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"any_injury": datasets.Value("int64"),
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}
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),
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supervised_keys=None,
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@@ -86,16 +86,16 @@ class RSNAATD(datasets.GeneratorBasedBuilder):
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# "test": images
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# }
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# return
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for idx, (data) in enumerate(df.to_numpy()):
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image_path = Path(
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mask_path = Path(
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image, mask = [hkl.load(image_path)], [hkl.load(mask_path)]
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(
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patient_id,
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"test": datasets.Value("string"),
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# "patient_id": datasets.Value("int64"),
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# "series_id": datasets.Value("int64"),
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# "image": datasets.Array3D(shape=(None, 512, 512), dtype="uint8"),
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# "mask": datasets.Array3D(shape=(None, 512, 512), dtype="uint8"),
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# "aortic_hu": datasets.Value("float64"),
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# "incomplete_organ": datasets.Value("int64"),
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# "bowel_healthy": datasets.Value("int64"),
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# "bowel_injury": datasets.Value("int64"),
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# "extravasation_healthy": datasets.Value("int64"),
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# "extravasation_injury": datasets.Value("int64"),
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# "kidney_healthy": datasets.Value("int64"),
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# "kidney_low": datasets.Value("int64"),
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# "kidney_high": datasets.Value("int64"),
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# "liver_healthy": datasets.Value("int64"),
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# "liver_low": datasets.Value("int64"),
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# "liver_high": datasets.Value("int64"),
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# "spleen_healthy": datasets.Value("int64"),
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# "spleen_low": datasets.Value("int64"),
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# "spleen_high": datasets.Value("int64"),
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# "any_injury": datasets.Value("int64"),
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}
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),
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supervised_keys=None,
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# "test": images
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# }
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# return
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for i, image in enumerate(images):
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# image_path = Path(image).name
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# test = hkl.load(image_path)
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yield i, {
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"test": image
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}
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return
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for idx, (data, image_path, mask_path) in enumerate(zip(df.to_numpy(), images, masks)):
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image_path = Path(image_path) / data[0]
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mask_path = Path(mask_path) / data[0]
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image, mask = [hkl.load(image_path)], [hkl.load(mask_path)]
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(
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patient_id,
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