Move semantic-segmentation related codes to otx adapters

docs/source/guide/reference/mpa/modules/models/heads.rst

@@ -9,19 +9,10 @@ Heads
    :members:
    :undoc-members:
 
-.. automodule:: otx.mpa.modules.models.heads.aggregator_mixin
-   :members:
-   :undoc-members:
-
-
 .. automodule:: otx.mpa.modules.models.heads.custom_cls_head
    :members:
    :undoc-members:
 
-.. automodule:: otx.mpa.modules.models.heads.custom_fcn_head
-   :members:
-   :undoc-members:
-
 .. automodule:: otx.mpa.modules.models.heads.custom_hierarchical_linear_cls_head
    :members:
    :undoc-members:
@@ -38,22 +29,10 @@ Heads
    :members:
    :undoc-members:
 
-.. automodule:: otx.mpa.modules.models.heads.mix_loss_mixin
-   :members:
-   :undoc-members:
-
 .. automodule:: otx.mpa.modules.models.heads.non_linear_cls_head
    :members:
    :undoc-members:
 
-.. automodule:: otx.mpa.modules.models.heads.pixel_weights_mixin
-   :members:
-   :undoc-members:
-
-.. automodule:: otx.mpa.modules.models.heads.segment_out_norm_mixin
-   :members:
-   :undoc-members:
-
 .. automodule:: otx.mpa.modules.models.heads.semisl_cls_head
    :members:
    :undoc-members:

docs/source/guide/reference/mpa/modules/models/index.rst

@@ -4,10 +4,7 @@ Models
 .. toctree::
    :maxdepth: 1
 
-   backbones
    classifiers
    heads
    losses
-   scalar_schedulers
-   segmentors
    utils

docs/source/guide/reference/mpa/modules/models/losses.rst

@@ -21,18 +21,6 @@ Losses
    :members:
    :undoc-members:
 
-.. automodule:: otx.mpa.modules.models.losses.base_pixel_loss
-   :members:
-   :undoc-members:
-
-.. automodule:: otx.mpa.modules.models.losses.base_weighted_loss
-   :members:
-   :undoc-members:
-
-.. automodule:: otx.mpa.modules.models.losses.cross_entropy_loss_with_ignore
-   :members:
-   :undoc-members:
-
 .. automodule:: otx.mpa.modules.models.losses.cross_entropy_loss
    :members:
    :undoc-members:
@@ -41,11 +29,6 @@ Losses
    :members:
    :undoc-members:
 
-
-.. automodule:: otx.mpa.modules.models.losses.mpa_pixel_base
-   :members:
-   :undoc-members:
-
 .. automodule:: otx.mpa.modules.models.losses.utils
    :members:
    :undoc-members:

docs/source/guide/reference/mpa/modules/ov/models.rst

@@ -24,7 +24,3 @@ Models
 .. automodule:: otx.mpa.modules.ov.models.mmcls
    :members:
    :undoc-members:
-
-.. automodule:: otx.mpa.modules.ov.models.mmseg
-   :members:
-   :undoc-members:

docs/source/guide/reference/mpa/modules/utils.rst

@@ -13,10 +13,6 @@ Utils
    :members:
    :undoc-members:
 
-.. automodule:: otx.mpa.modules.utils.seg_utils
-   :members:
-   :undoc-members:
-
 .. automodule:: otx.mpa.modules.utils.task_adapt
    :members:
    :undoc-members:

otx/algorithms/segmentation/adapters/__init__.py

@@ -1,4 +1,16 @@
 """Adapters for Segmentation."""
 
+
 # Copyright (C) 2023 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions
+# and limitations under the License.

otx/algorithms/segmentation/adapters/mmseg/__init__.py

@@ -1,10 +1,38 @@
 """OTX Adapters - mmseg."""
 
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
 
-from .data import MPASegDataset
-from .models import DetConB, DetConLoss, SelfSLMLP, SupConDetConB
+# Copyright (C) 2023 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions
+# and limitations under the License.
+
+
+from .datasets import MPASegDataset
+from .models import (
+    ClassIncrEncoderDecoder,
+    ConstantScalarScheduler,
+    CrossEntropyLossWithIgnore,
+    CustomFCNHead,
+    DetConB,
+    DetConLoss,
+    LiteHRNet,
+    MeanTeacherSegmentor,
+    MMOVBackbone,
+    MMOVDecodeHead,
+    PolyScalarScheduler,
+    SelfSLMLP,
+    StepScalarScheduler,
+    SupConDetConB,
+)
 
 # fmt: off
 # isort: off
@@ -16,4 +44,20 @@
 # fmt: off
 # isort: on
 
-__all__ = ["MPASegDataset", "DetConLoss", "SelfSLMLP", "DetConB", "SupConDetConB"]
+__all__ = [
+    "MPASegDataset",
+    "LiteHRNet",
+    "MMOVBackbone",
+    "CustomFCNHead",
+    "MMOVDecodeHead",
+    "DetConLoss",
+    "SelfSLMLP",
+    "ConstantScalarScheduler",
+    "PolyScalarScheduler",
+    "StepScalarScheduler",
+    "DetConB",
+    "CrossEntropyLossWithIgnore",
+    "SupConDetConB",
+    "ClassIncrEncoderDecoder",
+    "MeanTeacherSegmentor",
+]

otx/algorithms/segmentation/adapters/mmseg/data/__init__.py → otx/algorithms/segmentation/adapters/mmseg/datasets/__init__.py

@@ -1,6 +1,6 @@
 """OTX Algorithms - Segmentation Dataset."""
 
-# Copyright (C) 2022 Intel Corporation
+# Copyright (C) 2023 Intel Corporation
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -18,13 +18,17 @@
 from .pipelines import (
     LoadAnnotationFromOTXDataset,
     LoadImageFromOTXDataset,
+    MaskCompose,
+    ProbCompose,
     TwoCropTransform,
 )
 
 __all__ = [
-    "get_annotation_mmseg_format",
-    "LoadImageFromOTXDataset",
     "LoadAnnotationFromOTXDataset",
-    "MPASegDataset",
+    "LoadImageFromOTXDataset",
+    "MaskCompose",
+    "ProbCompose",
     "TwoCropTransform",
+    "get_annotation_mmseg_format",
+    "MPASegDataset",
 ]

otx/algorithms/segmentation/adapters/mmseg/data/dataset.py → otx/algorithms/segmentation/adapters/mmseg/datasets/dataset.py

@@ -1,6 +1,6 @@
 """Base MMDataset for Segmentation Task."""
 
-# Copyright (C) 2022 Intel Corporation
+# Copyright (C) 2023 Intel Corporation
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

otx/algorithms/segmentation/adapters/mmseg/datasets/pipelines/__init__.py

@@ -0,0 +1,21 @@
+"""OTX Algorithms - Segmentation pipelines."""
+
+# Copyright (C) 2023 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions
+# and limitations under the License.
+
+from .compose import MaskCompose, ProbCompose
+from .loads import LoadAnnotationFromOTXDataset, LoadImageFromOTXDataset
+from .transforms import TwoCropTransform
+
+__all__ = ["MaskCompose", "ProbCompose", "LoadImageFromOTXDataset", "LoadAnnotationFromOTXDataset", "TwoCropTransform"]

otx/mpa/modules/datasets/pipelines/compose.py → otx/algorithms/segmentation/adapters/mmseg/datasets/pipelines/compose.py

@@ -1,4 +1,6 @@
-# Copyright (C) 2022 Intel Corporation
+"""Collection of compose pipelines for segmentation task."""
+
+# Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 #
 
@@ -11,8 +13,11 @@
 from scipy.ndimage import gaussian_filter
 
 
+# pylint: disable=consider-using-f-string
 @PIPELINES.register_module()
-class ProbCompose(object):
+class ProbCompose:
+    """Compose pipelines in a list and enable or disable them with the probability."""
+
     def __init__(self, transforms, probs):
         assert isinstance(transforms, Sequence)
         assert isinstance(probs, Sequence)
@@ -35,6 +40,7 @@ def __init__(self, transforms, probs):
                 raise TypeError(f"transform must be callable or a dict, but got {type(transform)}")
 
     def __call__(self, data):
+        """Callback function of ProbCompose."""
         rand_value = np.random.rand()
         transform_id = np.max(np.where(rand_value > self.limits)[0])
 
@@ -44,17 +50,20 @@ def __call__(self, data):
         return data
 
     def __repr__(self):
+        """Repr."""
         format_string = self.__class__.__name__ + "("
         for t in self.transforms:
             format_string += "\n"
-            format_string += "    {0}".format(t)
+            format_string += f"    {t}"
         format_string += "\n)"
 
         return format_string
 
 
 @PIPELINES.register_module()
-class MaskCompose(object):
+class MaskCompose:
+    """Compose mask-related pipelines in a list and enable or disable them with the probability."""
+
     def __init__(self, transforms, prob, lambda_limits=(4, 16), keep_original=False):
         self.keep_original = keep_original
         self.prob = prob
@@ -102,6 +111,7 @@ def _mix_img(main_img, aux_img, mask):
         return np.where(np.expand_dims(mask, axis=2), main_img, aux_img)
 
     def __call__(self, data):
+        """Callback function of MaskCompose."""
         main_data = self._apply_transforms(deepcopy(data), self.transforms)
         assert main_data is not None
         if not self.keep_original and np.random.rand() > self.prob:
@@ -123,10 +133,11 @@ def __call__(self, data):
         return main_data
 
     def __repr__(self):
+        """Repr."""
         format_string = self.__class__.__name__ + "("
         for t in self.transforms:
             format_string += "\n"
-            format_string += "    {0}".format(t)
+            format_string += f"    {t}"
         format_string += "\n)"
 
         return format_string