Added __init__ to store self.DATA_DIR
Browse files- AeroPath.py +8 -9
AeroPath.py
CHANGED
@@ -82,10 +82,9 @@ class AeroPath(datasets.GeneratorBasedBuilder):
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DEFAULT_CONFIG_NAME = "zenodo" # It's not mandatory to have a default configuration. Just use one if it make sense.
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return DATA_DIR
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def get_patient(self, patient_id):
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if (patient_id < 1) or (patiend_id > 27):
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@@ -122,7 +121,7 @@ class AeroPath(datasets.GeneratorBasedBuilder):
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)
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def get_data_dir(self):
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return DATA_DIR
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def _split_generators(self, dl_manager):
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# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
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@@ -132,9 +131,9 @@ class AeroPath(datasets.GeneratorBasedBuilder):
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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urls = _URLS[self.config.name]
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DATA_DIR = dl_manager.download_and_extract(urls)
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print("data is downloaded to:", DATA_DIR)
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return [
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datasets.SplitGenerator(
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@@ -150,8 +149,8 @@ class AeroPath(datasets.GeneratorBasedBuilder):
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def _generate_examples(self, split):
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# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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for patient_id in os.listdir(DATA_DIR):
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curr_path = os.path.join(DATA_DIR, patient_id)
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yield patient_id, {
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"ct": os.path.join(curr_path, patient_id, "_CT_HR.nii.gz"),
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"airways": os.path.join(curr_path, patient_id, "_CT_HR_label_airways.nii.gz"),
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DEFAULT_CONFIG_NAME = "zenodo" # It's not mandatory to have a default configuration. Just use one if it make sense.
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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self.DATA_DIR = None
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def get_patient(self, patient_id):
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if (patient_id < 1) or (patiend_id > 27):
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)
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def get_data_dir(self):
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return self.DATA_DIR
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def _split_generators(self, dl_manager):
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# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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urls = _URLS[self.config.name]
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self.DATA_DIR = dl_manager.download_and_extract(urls)
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print("data is downloaded to:", self.DATA_DIR)
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return [
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datasets.SplitGenerator(
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def _generate_examples(self, split):
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# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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for patient_id in os.listdir(self.DATA_DIR):
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curr_path = os.path.join(self.DATA_DIR, patient_id)
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yield patient_id, {
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"ct": os.path.join(curr_path, patient_id, "_CT_HR.nii.gz"),
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"airways": os.path.join(curr_path, patient_id, "_CT_HR_label_airways.nii.gz"),
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