Source code for

@author: Junguang Jiang
import os
from typing import Optional
from .imagelist import ImageList
from ._util import download as download_data, check_exits

[docs]class VisDA2017(ImageList): """`VisDA-2017 <>`_ Dataset Args: root (str): Root directory of dataset task (str): The task (domain) to create dataset. Choices include ``'Synthetic'``: synthetic images and \ ``'Real'``: real-world images. download (bool, optional): If true, downloads the dataset from the internet and puts it \ in root directory. If dataset is already downloaded, it is not downloaded again. transform (callable, optional): A function/transform that takes in an PIL image and returns a \ transformed version. E.g, ``transforms.RandomCrop``. target_transform (callable, optional): A function/transform that takes in the target and transforms it. .. note:: In `root`, there will exist following files after downloading. :: train/ aeroplance/ *.png ... validation/ image_list/ train.txt validation.txt """ download_list = [ ("image_list", "", ""), ("train", "train.tar", ""), ("validation", "validation.tar", "") ] image_list = { "Synthetic": "image_list/train.txt", "Real": "image_list/validation.txt" } CLASSES = ['aeroplane', 'bicycle', 'bus', 'car', 'horse', 'knife', 'motorcycle', 'person', 'plant', 'skateboard', 'train', 'truck'] def __init__(self, root: str, task: str, download: Optional[bool] = False, **kwargs): assert task in self.image_list data_list_file = os.path.join(root, self.image_list[task]) if download: list(map(lambda args: download_data(root, *args), self.download_list)) else: list(map(lambda file_name, _: check_exits(root, file_name), self.download_list)) super(VisDA2017, self).__init__(root, VisDA2017.CLASSES, data_list_file=data_list_file, **kwargs)
[docs] @classmethod def domains(cls): return list(cls.image_list.keys())


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