Source code for

@author: Junguang Jiang
import os
from .imagelist import ImageList

[docs]class Retinopathy(ImageList): """`Retinopathy <>`_ dataset \ consists of image-label pairs with high-resolution retina images, and labels that indicate \ the presence of Diabetic Retinopahy (DR) in a 0-4 scale (No DR, Mild, Moderate, Severe, \ or Proliferative DR). .. note:: You need to download the source data manually into `root` directory. Args: root (str): Root directory of dataset split (str, optional): The dataset split, supports ``train``, or ``test``. transform (callable, optional): A function/transform that takes in an PIL image and returns a \ transformed version. E.g, :class:`torchvision.transforms.RandomCrop`. target_transform (callable, optional): A function/transform that takes in the target and transforms it. """ CLASSES = ['No DR', 'Mild', 'Moderate', 'Severe', 'Proliferative DR'] def __init__(self, root, split, download=False, **kwargs): super(Retinopathy, self).__init__(os.path.join(root, split), Retinopathy.CLASSES, os.path.join(root, "image_list", "{}.txt".format(split)), **kwargs)


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