Source code for domainlab.tasks.task_mini_vlcs

"""
test task for image size 224
"""
import os

from torchvision import transforms

from domainlab.tasks.task_folder_mk import mk_task_folder
from domainlab.tasks.utils_task import ImSize

path_this_file = os.path.dirname(os.path.realpath(__file__))




def addtask2chain(chain):
    """
    given a chain of responsibility for task selection, add another task into the chain
    """
    new_chain = mk_task_folder(
        extensions={"caltech": "jpg", "sun": "jpg", "labelme": "jpg"},
        list_str_y=["chair", "car"],
        dict_domain_folder_name2class={
            "caltech": {"auto": "car", "stuhl": "chair"},
            "sun": {"vehicle": "car", "sofa": "chair"},
            "labelme": {"drive": "car", "sit": "chair"},
        },
        dict_domain_img_trans={
            "caltech": transforms.Compose(
                [transforms.Resize((224, 224)), transforms.ToTensor()]
            ),
            "sun": transforms.Compose(
                [transforms.Resize((224, 224)), transforms.ToTensor()]
            ),
            "labelme": transforms.Compose(
                [transforms.Resize((224, 224)), transforms.ToTensor()]
            ),
        },
        img_trans_te=transforms.Compose(
            [transforms.Resize((224, 224)), transforms.ToTensor()]
        ),
        isize=ImSize(3, 224, 224),
        dict_domain2imgroot={
            "caltech": os.path.join(
                path_this_file,
                os.path.normpath("../"),
                os.path.normpath("zdata/vlcs_mini/caltech/"),
            ),
            "sun": os.path.join(
                path_this_file,
                os.path.normpath("../"),
                os.path.normpath("zdata/vlcs_mini/sun/"),
            ),
            "labelme": os.path.join(
                path_this_file,
                os.path.normpath("../"),
                os.path.normpath("zdata/vlcs_mini/labelme/"),
            ),
        },
        taskna="mini_vlcs",
        succ=chain,
    )
    return new_chain