init

finetune/mmseg/datasets/atlantic.py

@@ -0,0 +1,48 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import json
+import os.path as osp
+from typing import List
+
+from mmseg.registry import DATASETS
+from .basesegdataset import BaseSegDataset
+
+@DATASETS.register_module()
+class AtlanticDataset(BaseSegDataset):
+    METAINFO = dict(
+        classes=('Background', 'Deforestation area'),
+        palette=[[0,0,0], [255,255,255]]
+    )
+    def __init__(self,
+                 img_suffix='.tif',
+                 seg_map_suffix='.tif',
+                 reduce_zero_label=False,
+                 **kwargs) -> None:
+        super().__init__(
+            img_suffix=img_suffix,
+            seg_map_suffix=seg_map_suffix,
+            reduce_zero_label=reduce_zero_label,
+            **kwargs)
+    
+    def load_data_list(self) -> List[dict]:
+        """Load annotation from directory or annotation file.
+
+        Returns:
+            list[dict]: All data info of dataset.
+        """
+        data_list = []
+        if not osp.isdir(self.ann_file) and self.ann_file:
+            assert osp.isfile(self.ann_file), \
+                f'Failed to load `ann_file` {self.ann_file}'
+            lines = json.load(open(self.ann_file))
+            for line in lines:
+                # img_name = line.strip()
+                data_info = dict(
+                    img_path=osp.join(self.data_root, line['s2_path']))
+                if 'target_path' in line.keys():
+                    data_info['seg_map_path'] = osp.join(self.data_root, line['target_path'])
+                data_info['label_map'] = self.label_map
+                data_info['reduce_zero_label'] = self.reduce_zero_label
+                data_info['seg_fields'] = []
+                data_list.append(data_info)
+            data_list = sorted(data_list, key=lambda x: x['img_path'])
+        return data_list