init

finetune/mmseg/structures/seg_data_sample.py

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+# Copyright (c) OpenMMLab. All rights reserved.
+from mmengine.structures import BaseDataElement, PixelData
+
+
+class SegDataSample(BaseDataElement):
+    """A data structure interface of MMSegmentation. They are used as
+    interfaces between different components.
+
+    The attributes in ``SegDataSample`` are divided into several parts:
+
+        - ``gt_sem_seg``(PixelData): Ground truth of semantic segmentation.
+        - ``pred_sem_seg``(PixelData): Prediction of semantic segmentation.
+        - ``seg_logits``(PixelData): Predicted logits of semantic segmentation.
+
+    Examples:
+         >>> import torch
+         >>> import numpy as np
+         >>> from mmengine.structures import PixelData
+         >>> from mmseg.structures import SegDataSample
+
+         >>> data_sample = SegDataSample()
+         >>> img_meta = dict(img_shape=(4, 4, 3),
+         ...                 pad_shape=(4, 4, 3))
+         >>> gt_segmentations = PixelData(metainfo=img_meta)
+         >>> gt_segmentations.data = torch.randint(0, 2, (1, 4, 4))
+         >>> data_sample.gt_sem_seg = gt_segmentations
+         >>> assert 'img_shape' in data_sample.gt_sem_seg.metainfo_keys()
+         >>> data_sample.gt_sem_seg.shape
+         (4, 4)
+         >>> print(data_sample)
+        <SegDataSample(
+
+            META INFORMATION
+
+            DATA FIELDS
+            gt_sem_seg: <PixelData(
+
+                    META INFORMATION
+                    img_shape: (4, 4, 3)
+                    pad_shape: (4, 4, 3)
+
+                    DATA FIELDS
+                    data: tensor([[[1, 1, 1, 0],
+                                 [1, 0, 1, 1],
+                                 [1, 1, 1, 1],
+                                 [0, 1, 0, 1]]])
+                ) at 0x1c2b4156460>
+        ) at 0x1c2aae44d60>
+
+        >>> data_sample = SegDataSample()
+        >>> gt_sem_seg_data = dict(sem_seg=torch.rand(1, 4, 4))
+        >>> gt_sem_seg = PixelData(**gt_sem_seg_data)
+        >>> data_sample.gt_sem_seg = gt_sem_seg
+        >>> assert 'gt_sem_seg' in data_sample
+        >>> assert 'sem_seg' in data_sample.gt_sem_seg
+    """
+
+    @property
+    def gt_sem_seg(self) -> PixelData:
+        return self._gt_sem_seg
+
+    @gt_sem_seg.setter
+    def gt_sem_seg(self, value: PixelData) -> None:
+        self.set_field(value, '_gt_sem_seg', dtype=PixelData)
+
+    @gt_sem_seg.deleter
+    def gt_sem_seg(self) -> None:
+        del self._gt_sem_seg
+
+    @property
+    def pred_sem_seg(self) -> PixelData:
+        return self._pred_sem_seg
+
+    @pred_sem_seg.setter
+    def pred_sem_seg(self, value: PixelData) -> None:
+        self.set_field(value, '_pred_sem_seg', dtype=PixelData)
+
+    @pred_sem_seg.deleter
+    def pred_sem_seg(self) -> None:
+        del self._pred_sem_seg
+
+    @property
+    def seg_logits(self) -> PixelData:
+        return self._seg_logits
+
+    @seg_logits.setter
+    def seg_logits(self, value: PixelData) -> None:
+        self.set_field(value, '_seg_logits', dtype=PixelData)
+
+    @seg_logits.deleter
+    def seg_logits(self) -> None:
+        del self._seg_logits