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# -*- coding: utf-8 -*-
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2023 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# Contact: mica@tue.mpg.de
import numpy as np
from torch.utils.data import ConcatDataset
from datasets.base import BaseDataset
def build_train(config, device):
data_list = []
total_images = 0
for dataset in config.training_data:
dataset_name = dataset.upper()
config.n_train = np.Inf
if type(dataset) is list:
dataset_name, n_train = dataset
config.n_train = n_train
dataset = BaseDataset(name=dataset_name, config=config, device=device, isEval=False)
data_list.append(dataset)
total_images += dataset.total_images
return ConcatDataset(data_list), total_images
def build_val(config, device):
data_list = []
total_images = 0
for dataset in config.eval_data:
dataset_name = dataset.upper()
config.n_train = np.Inf
if type(dataset) is list:
dataset_name, n_train = dataset
config.n_train = n_train
dataset = BaseDataset(name=dataset_name, config=config, device=device, isEval=True)
data_list.append(dataset)
total_images += dataset.total_images
return ConcatDataset(data_list), total_images
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