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Commit 4430c202 authored by André Anjos's avatar André Anjos :speech_balloon:
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[configs.datasets] Removed legacy RS configurations

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1 merge request!6Making use of LightningDataModule and simplification of data loading
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# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
def _maker(protocol, resize_size=512, cc_size=512, RGB=False):
from ....data.hivtb_RS import dataset as raw
from .. import make_dataset as mk
return mk([raw.subsets(protocol)])
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 0)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_0")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 1)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_1")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 2)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_2")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 3)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_3")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 4)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_4")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 5)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_5")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 6)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_6")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 7)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_7")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 8)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_8")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""HIV-TB dataset for TB detection (cross validation fold 9)
* Split reference: none (stratified kfolding)
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.hivtb` for dataset details
"""
from . import _maker
dataset = _maker("fold_9")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
def _maker(protocol):
from ....data.indian_RS import dataset as raw
from .. import make_dataset as mk
return mk([raw.subsets(protocol)])
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (default protocol) (extended with DensenetRS
predictions)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("default")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 0)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_0")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 1)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_1")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 2)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_2")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 3)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_3")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 4)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_4")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 5)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_5")
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 6)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from . import _maker
dataset = _maker("fold_6")
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