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config.py
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# <config.py>
#
# Definition of parameters for each dataset.
#
# @Authors and Contributors:
# Lucas Pascotti Valem <[email protected]>
# João Gabriel Camacho Presotto <[email protected]>
# Nikolas Gomes de Sá <[email protected]>
# Daniel Carlos Guimarães Pedronette <[email protected]>
#
# ------------------------------------------------------------------------------
#
# This file is part of Weakly Supervised Experiments Framework (WSEF).
# Official Repository: https://github.com/UDLF/WSEF
#
# WSEF is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# WSEF is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with WSEF. If not, see <http://www.gnu.org/licenses/>.
#
# ------------------------------------------------------------------------------
# list of datasets to run execution
datasets = ["flowers"]
# init dictionary of parameters
dataset_settings = dict()
# flowers dataset parameters
dataset_settings["flowers"] = {"descriptors": ["resnet"],
"classifiers": ["opf"],
"correlation_measures": ["rbo"],
"thresholds": {"intersection": 0.15,
"jaccard": 0.45,
"jaccard_k": 0.30,
"kendalltau": 0.55,
"rbo": 0.20,
"spearman": 0.55},
"top_k": 80,
"dataset_size": 1360,
"L": 400,
"n_executions": 1,
"n_folds": 10,
}
# corel5k dataset parameters
dataset_settings["corel5k"] = {"descriptors": ["acc", "resnet"],
"classifiers": ["opf", "svm", "knn", "gcn"],
"correlation_measures": ["intersection", "jaccard", "jaccard_k", "kendalltau", "rbo", "spearman"],
"thresholds": {"intersection": 0.45,
"jaccard": 0.40,
"jaccard_k": 0.25,
"kendalltau": 0.50,
"rbo": 0.15,
"spearman": 0.45},
"top_k": 100,
"dataset_size": 5000,
"L": 1000,
"n_executions": 1,
"n_folds": 10,
}
# cub200 dataset parameters
dataset_settings["cub200"] = {"descriptors": ["resnet152"],
"classifiers": ["opf", "svm", "knn", "gcn"],
"correlation_measures": ["intersection", "jaccard", "jaccard_k", "kendalltau", "rbo", "spearman"],
"thresholds": {"intersection": 0.45,
"jaccard": 0.40,
"jaccard_k": 0.25,
"kendalltau": 0.50,
"rbo": 0.15,
"spearman": 0.45},
"top_k": 50,
"dataset_size": 11788,
"L": 1000,
"n_executions": 1,
"n_folds": 10,
}