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Commit 00c5f0f0 authored by Daniel CARRON's avatar Daniel CARRON :b: Committed by André Anjos
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Moved tbx11k_simplified_v2 configs to data

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1 merge request!6Making use of LightningDataModule and simplification of data loading
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with 878 additions and 49 deletions
......@@ -222,28 +222,28 @@ tbx11k_simplified_rs_f7 = "ptbench.configs.datasets.tbx11k_simplified_RS.fold_7"
tbx11k_simplified_rs_f8 = "ptbench.configs.datasets.tbx11k_simplified_RS.fold_8"
tbx11k_simplified_rs_f9 = "ptbench.configs.datasets.tbx11k_simplified_RS.fold_9"
# TBX11K simplified dataset split 2 (and cross-validation folds)
tbx11k_simplified_v2 = "ptbench.configs.datasets.tbx11k_simplified_v2.default"
tbx11k_simplified_v2_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.rgb"
tbx11k_simplified_v2_f0 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_0"
tbx11k_simplified_v2_f1 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_1"
tbx11k_simplified_v2_f2 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_2"
tbx11k_simplified_v2_f3 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_3"
tbx11k_simplified_v2_f4 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_4"
tbx11k_simplified_v2_f5 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_5"
tbx11k_simplified_v2_f6 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_6"
tbx11k_simplified_v2_f7 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_7"
tbx11k_simplified_v2_f8 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_8"
tbx11k_simplified_v2_f9 = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_9"
tbx11k_simplified_v2_f0_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_0_rgb"
tbx11k_simplified_v2_f1_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_1_rgb"
tbx11k_simplified_v2_f2_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_2_rgb"
tbx11k_simplified_v2_f3_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_3_rgb"
tbx11k_simplified_v2_f4_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_4_rgb"
tbx11k_simplified_v2_f5_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_5_rgb"
tbx11k_simplified_v2_f6_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_6_rgb"
tbx11k_simplified_v2_f7_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_7_rgb"
tbx11k_simplified_v2_f8_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_8_rgb"
tbx11k_simplified_v2_f9_rgb = "ptbench.configs.datasets.tbx11k_simplified_v2.fold_9_rgb"
tbx11k_simplified_v2 = "ptbench.data.tbx11k_simplified_v2.default"
tbx11k_simplified_v2_rgb = "ptbench.data.tbx11k_simplified_v2.rgb"
tbx11k_simplified_v2_f0 = "ptbench.data.tbx11k_simplified_v2.fold_0"
tbx11k_simplified_v2_f1 = "ptbench.data.tbx11k_simplified_v2.fold_1"
tbx11k_simplified_v2_f2 = "ptbench.data.tbx11k_simplified_v2.fold_2"
tbx11k_simplified_v2_f3 = "ptbench.data.tbx11k_simplified_v2.fold_3"
tbx11k_simplified_v2_f4 = "ptbench.data.tbx11k_simplified_v2.fold_4"
tbx11k_simplified_v2_f5 = "ptbench.data.tbx11k_simplified_v2.fold_5"
tbx11k_simplified_v2_f6 = "ptbench.data.tbx11k_simplified_v2.fold_6"
tbx11k_simplified_v2_f7 = "ptbench.data.tbx11k_simplified_v2.fold_7"
tbx11k_simplified_v2_f8 = "ptbench.data.tbx11k_simplified_v2.fold_8"
tbx11k_simplified_v2_f9 = "ptbench.data.tbx11k_simplified_v2.fold_9"
tbx11k_simplified_v2_f0_rgb = "ptbench.data.tbx11k_simplified_v2.fold_0_rgb"
tbx11k_simplified_v2_f1_rgb = "ptbench.data.tbx11k_simplified_v2.fold_1_rgb"
tbx11k_simplified_v2_f2_rgb = "ptbench.data.tbx11k_simplified_v2.fold_2_rgb"
tbx11k_simplified_v2_f3_rgb = "ptbench.data.tbx11k_simplified_v2.fold_3_rgb"
tbx11k_simplified_v2_f4_rgb = "ptbench.data.tbx11k_simplified_v2.fold_4_rgb"
tbx11k_simplified_v2_f5_rgb = "ptbench.data.tbx11k_simplified_v2.fold_5_rgb"
tbx11k_simplified_v2_f6_rgb = "ptbench.data.tbx11k_simplified_v2.fold_6_rgb"
tbx11k_simplified_v2_f7_rgb = "ptbench.data.tbx11k_simplified_v2.fold_7_rgb"
tbx11k_simplified_v2_f8_rgb = "ptbench.data.tbx11k_simplified_v2.fold_8_rgb"
tbx11k_simplified_v2_f9_rgb = "ptbench.data.tbx11k_simplified_v2.fold_9_rgb"
# extended TBX11K simplified dataset split 2 (with radiological signs)
tbx11k_simplified_v2_rs = "ptbench.configs.datasets.tbx11k_simplified_v2_RS.default"
tbx11k_simplified_v2_rs_f0 = "ptbench.configs.datasets.tbx11k_simplified_v2_RS.fold_0"
......
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
def _maker(protocol, RGB=False):
from torchvision import transforms
from ....data.tbx11k_simplified_v2 import dataset as raw
from ....data.transforms import ElasticDeformation
from .. import make_dataset as mk
post_transforms = []
if RGB:
post_transforms = [
transforms.Lambda(lambda x: x.convert("RGB")),
transforms.ToTensor(),
]
return mk(
[raw.subsets(protocol)],
[],
[ElasticDeformation(p=0.8)],
post_transforms,
)
......@@ -76,15 +76,36 @@ def _loader_bbox(context, sample):
return make_delayed_bbox(sample, _raw_data_loader_bbox)
dataset = JSONDataset(
json_dataset = JSONDataset(
protocols=_protocols,
fieldnames=("data", "label"),
loader=_loader,
)
dataset_with_bboxes = JSONDataset(
json_dataset_with_bboxes = JSONDataset(
protocols=_protocols,
fieldnames=("data", "label", "bboxes"),
loader=_loader_bbox,
)
"""TBX11K simplified dataset object."""
def _maker(protocol, RGB=False):
from torchvision import transforms
from .. import make_dataset
from ..transforms import ElasticDeformation
post_transforms = []
if RGB:
post_transforms = [
transforms.Lambda(lambda x: x.convert("RGB")),
transforms.ToTensor(),
]
return make_dataset(
[json_dataset.subsets(protocol)],
[],
[ElasticDeformation(p=0.8)],
post_transforms,
)
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("default")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class DefaultModule(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("default")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = DefaultModule
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_0")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_0")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_0", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_0", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_1")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_1")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_1", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_1", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_2")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_2")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_2", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_2", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_3")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_3")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_3", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_3", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_4")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_4")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_4", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_4", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_5")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_5")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_5", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_5", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_6")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_6")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_6", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_6", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_7")
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_7")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
......@@ -12,6 +12,38 @@
* See :py:mod:`ptbench.data.tbx11k_simplified_v2` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
dataset = _maker("fold_7", RGB=True)
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_7", RGB=True)
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
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