updated TB-POC dataset and corresponding tests

Updated TB-POC dataset and corresponding tests

src/ptbench/data/tbpoc/__init__.py

-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-"""TB-POC dataset for computer-aided diagnosis.
-
-* Reference: [TB-POC-2018]_
-* Original resolution (height x width or width x height): 2048 x 2500
-* Split reference: none
-* Stratified kfold protocol:
-
-  * Training samples: 72% of TB and healthy CXR (including labels)
-  * Validation samples: 18% of TB and healthy CXR (including labels)
-  * Test samples: 10% of TB and healthy CXR (including labels)
-"""
-
-import importlib.resources
-import os
-
-from ...utils.rc import load_rc
-from .. import make_dataset
-from ..dataset import JSONDataset
-from ..loader import load_pil_grayscale, make_delayed
-
-_protocols = [
-    importlib.resources.files(__name__).joinpath("fold_0.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_1.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_2.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_3.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_4.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_5.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_6.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_7.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_8.json.bz2"),
-    importlib.resources.files(__name__).joinpath("fold_9.json.bz2"),
-]
-
-_datadir = load_rc().get("datadir.tbpoc", os.path.realpath(os.curdir))
-
-
-def _raw_data_loader(sample):
-    return dict(
-        data=load_pil_grayscale(os.path.join(_datadir, sample["data"])),
-        label=sample["label"],
-    )
-
-
-def _loader(context, sample):
-    # "context" is ignored in this case - database is homogeneous
-    # we returned delayed samples to avoid loading all images at once
-    return make_delayed(sample, _raw_data_loader)
-
-
-json_dataset = JSONDataset(
-    protocols=_protocols,
-    fieldnames=("data", "label"),
-    loader=_loader,
-)
-"""TB-POC dataset object."""
-
-
-def _maker(protocol, resize_size=512, cc_size=512, RGB=False):
-    from torchvision import transforms
-
-    from ..augmentations import ElasticDeformation
-    from ..image_utils import RemoveBlackBorders
-
-    post_transforms = []
-    if RGB:
-        post_transforms = [
-            transforms.Lambda(lambda x: x.convert("RGB")),
-            transforms.ToTensor(),
-        ]
-
-    return make_dataset(
-        [json_dataset.subsets(protocol)],
-        [
-            RemoveBlackBorders(),
-            transforms.Resize(resize_size),
-            transforms.CenterCrop(cc_size),
-        ],
-        [ElasticDeformation(p=0.8)],
-        post_transforms,
-    )