diff --git a/AeroPath.py b/AeroPath.py index 2987ccb5a4e482f7400b8ce5164654e81491be4f..2f5a9509ffbeb1d0e5cfca79d94de08b44e66334 100644 --- a/AeroPath.py +++ b/AeroPath.py @@ -1,29 +1,16 @@ -# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -# TODO: Address all TODOs and remove all explanatory comments -"""TODO: Add a description here.""" +"""AeroPath: An airway segmentation benchmark dataset with challenging pathology.""" -import csv -import json -import os - import datasets +_DESCRIPTION = """\ +AeroPath: An airway segmentation benchmark dataset with challenging pathology. +""" + +_HOMEPAGE = "https://github.com/raidionics/AeroPath" + +_LICENSE = "MIT" -# TODO: Add BibTeX citation -# Find for instance the citation on arxiv or on the dataset repo/website _CITATION = """\ @misc{støverud2023aeropath, title={AeroPath: An airway segmentation benchmark dataset with challenging pathology}, @@ -35,130 +22,49 @@ primaryClass={cs.CV} } """ -# TODO: Add description of the dataset here -# You can copy an official description -_DESCRIPTION = """\ -AeroPath: An airway segmentation benchmark dataset with challenging pathology. -""" - -# TODO: Add a link to an official homepage for the dataset here -_HOMEPAGE = "https://github.com/raidionics/AeroPath" - -# TODO: Add the licence for the dataset here if you can find it -_LICENSE = "MIT" - -# TODO: Add link to the official dataset URLs here -# The HuggingFace Datasets library doesn't host the datasets but only points to the original files. -# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) -_URLS = { - #"first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip", - #"second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip", - "zenodo": "https://zenodo.org/records/10069289/files/AeroPath.zip?download=1" -} +_URLS = [ + { + "ct": f"data/{i}/{i}_CT_HR.nii.gz", + "airways": f"data/{i}/{i}_CT_HR_label_airways.nii.gz", + "lungs": f"data/{i}/{i}_CT_HR_label_lungs.nii.gz", + } + for i in range(1, 28) +] -# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case class AeroPath(datasets.GeneratorBasedBuilder): """An airway segmentation benchmark dataset with challenging pathology.""" VERSION = datasets.Version("1.0.0") - # This is an example of a dataset with multiple configurations. - # If you don't want/need to define several sub-sets in your dataset, - # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. - - # If you need to make complex sub-parts in the datasets with configurable options - # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig - # BUILDER_CONFIG_CLASS = MyBuilderConfig - - # You will be able to load one or the other configurations in the following list with - # data = datasets.load_dataset('my_dataset', 'first_domain') - # data = datasets.load_dataset('my_dataset', 'second_domain') - BUILDER_CONFIGS = [ - #datasets.BuilderConfig(name="first_domain", version=VERSION, description="This part of my dataset covers a first domain"), - #datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"), - datasets.BuilderConfig(name="zenodo", version=VERSION, description="This includes all 27 CTs stored as a single zip on Zenodo"), - ] - - DEFAULT_CONFIG_NAME = "zenodo" # It's not mandatory to have a default configuration. Just use one if it make sense. - - def __init__(self, **kwargs): - super().__init__(**kwargs) - self.DATA_DIR = None - - def get_patient(self, patient_id): - if (patient_id < 1) or (patiend_id > 27): - raise ValueError("patient_id should be an integer in range [1, 27].") - def _info(self): - # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset - if self.config.name == "zenodo": # This is the name of the configuration selected in BUILDER_CONFIGS above - features = datasets.Features( - { - "ct": datasets.Value("string"), - "airways": datasets.Value("string"), - "lungs": datasets.Value("string") - # These are the features of your dataset like images, labels ... - } - ) - else: - raise ValueError("Only 'zenodo' is supported.")# This is an example to show how to have different features for "first_domain" and "second_domain" - + features = datasets.Features( + { + "ct": datasets.Value("string"), + "airways": datasets.Value("string"), + "lungs": datasets.Value("string"), + } + ) return datasets.DatasetInfo( - # This is the description that will appear on the datasets page. description=_DESCRIPTION, - # This defines the different columns of the dataset and their types - features=features, # Here we define them above because they are different between the two configurations - # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and - # specify them. They'll be used if as_supervised=True in builder.as_dataset. - # supervised_keys=("sentence", "label"), - # Homepage of the dataset for documentation + features=features, homepage=_HOMEPAGE, - # License for the dataset if available license=_LICENSE, - # Citation for the dataset citation=_CITATION, ) - def get_data_dir(self): - return self.DATA_DIR - def _split_generators(self, dl_manager): - # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration - # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name - - # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS - # 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. - # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive - urls = _URLS[self.config.name] - self.DATA_DIR = dl_manager.download_and_extract(urls) - - # append AeroPath - self.DATA_DIR = os.path.join(self.DATA_DIR, "AeroPath") - - print("data is downloaded to:", self.DATA_DIR) - + data_dirs = dl_manager.download(_URLS) return [ datasets.SplitGenerator( name=datasets.Split.TEST, # These kwargs will be passed to _generate_examples gen_kwargs={ - "split": "test", + "data_dirs": data_dirs, }, ), ] - # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` - def _generate_examples(self, split): - # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. - # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example. - for patient_id in os.listdir(self.DATA_DIR): - curr_path = os.path.join(self.DATA_DIR, patient_id) - if patient_id in ["README.md", "license.md"]: - continue - yield patient_id, { - "ct": os.path.join(curr_path, patient_id + "_CT_HR.nii.gz"), - "airways": os.path.join(curr_path, patient_id + "_CT_HR_label_airways.nii.gz"), - "lungs": os.path.join(curr_path, patient_id + "_CT_HR_label_lungs.nii.gz"), - } - + def _generate_examples(self, data_dirs): + for key, patient in enumerate(data_dirs): + yield key, patient diff --git a/1/1_CT_HR.nii.gz b/data/1/1_CT_HR.nii.gz similarity index 100% rename from 1/1_CT_HR.nii.gz rename to data/1/1_CT_HR.nii.gz diff --git a/1/1_CT_HR_label_airways.nii.gz b/data/1/1_CT_HR_label_airways.nii.gz similarity index 100% rename from 1/1_CT_HR_label_airways.nii.gz rename to data/1/1_CT_HR_label_airways.nii.gz diff --git a/1/1_CT_HR_label_lungs.nii.gz b/data/1/1_CT_HR_label_lungs.nii.gz similarity index 100% rename from 1/1_CT_HR_label_lungs.nii.gz rename to data/1/1_CT_HR_label_lungs.nii.gz diff --git a/10/10_CT_HR.nii.gz b/data/10/10_CT_HR.nii.gz similarity index 100% rename from 10/10_CT_HR.nii.gz rename to data/10/10_CT_HR.nii.gz diff 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