biodatasets
Module¶
biodatasets
module provides classes to load public biomedical datasets
in a PyTorch friendly manner.
ChestXrayDataset
class¶
-
class
farabio.data.biodatasets.
ChestXrayDataset
(root: str, mode: str = 'train', shape: int = 256, transform=None, target_transform=None, download: bool = True)[source]¶ Chest X-ray dataset class
Kaggle Chest X-Ray Images competition dataset to detect pneumonia from [1].
References
Examples
>>> train_dataset = ChestXrayDataset(root=".", transform=None, download=True) >>> train_dataset.visualize_dataset()
DSB18Dataset
class¶
-
class
farabio.data.biodatasets.
DSB18Dataset
(root: str, train: bool = True, shape: int = 512, transform=None, download: bool = True)[source]¶ Nuclei segmentation dataset class
Kaggle 2018 Data Science Bowl competition dataset for segmented nuclei images from [1].
References
Examples
>>> train_dataset = DSB18Dataset(root=".", transform=None, download=False) >>> train_dataset.visualize_dataset(5)
HistocancerDataset
class¶
-
class
farabio.data.biodatasets.
HistocancerDataset
(root: str, train: bool = True, transform=None, download: bool = True)[source]¶ Histopathologic Cancer Dataset class
Kaggle Histopathologic Cancer Detection dataset from [1]
References
Examples
>>> train_dataset = HistocancerDataset(root=".", download=True, train=True) >>> train_dataset.visualize_dataset()
RANZCRDataset
class¶
-
class
farabio.data.biodatasets.
RANZCRDataset
(root: str, train: bool = True, transform=None, download: bool = False)[source]¶ RANZCR 2021 dataset class
Catheters presence and position detection from RANZCR CLiP - Catheter and Line Position Challenge from [1]
References
Examples
>>> train_dataset = RANZCRDataset(".", train=True, transform=None, download=True) >>> train_dataset.visualize_dataset()
RetinopathyDataset
class¶
-
class
farabio.data.biodatasets.
RetinopathyDataset
(root: str, train: bool = True, download: bool = True, transform=None)[source]¶ Retinopathy Dataset class
Retina images taken using fundus photography from Kaggle APTOS 2019 Blindness Detection competition, [1].
References
Examples
>>> train_dataset = RetinopathyDataset(root=".", transform=None, download=True) >>> train_dataset.visualize_dataset(9)