[Fix] Fix bug when loading class name form file in custom dataset (op…

…en-mmlab#923)

* [Fix] open-mmlab#916 expection string type classes

* add unittests for string path classes

* fix double quote string in test_dataset.py

* move the import to the top of the file

* fix isort lint error

fix isort lint error when move the import to the top of the file

mmseg/datasets/custom.py

@@ -319,7 +319,7 @@ def get_classes_and_palette(self, classes=None, palette=None):
             raise ValueError(f'Unsupported type {type(classes)} of classes.')
 
         if self.CLASSES:
-            if not set(classes).issubset(self.CLASSES):
+            if not set(class_names).issubset(self.CLASSES):
                 raise ValueError('classes is not a subset of CLASSES.')
 
             # dictionary, its keys are the old label ids and its values
@@ -330,7 +330,7 @@ def get_classes_and_palette(self, classes=None, palette=None):
                 if c not in class_names:
                     self.label_map[i] = -1
                 else:
-                    self.label_map[i] = classes.index(c)
+                    self.label_map[i] = class_names.index(c)
 
         palette = self.get_palette_for_custom_classes(class_names, palette)
 

tests/test_data/test_dataset.py

@@ -1,6 +1,8 @@
 # Copyright (c) OpenMMLab. All rights reserved.
+import os
 import os.path as osp
 import shutil
+import tempfile
 from typing import Generator
 from unittest.mock import MagicMock, patch
 
@@ -26,6 +28,37 @@ def test_classes():
         get_classes('unsupported')
 
 
+def test_classes_file_path():
+    tmp_file = tempfile.NamedTemporaryFile()
+    classes_path = f'{tmp_file.name}.txt'
+    train_pipeline = [dict(type='LoadImageFromFile')]
+    kwargs = dict(pipeline=train_pipeline, img_dir='./', classes=classes_path)
+
+    # classes.txt with full categories
+    categories = get_classes('cityscapes')
+    with open(classes_path, 'w') as f:
+        f.write('\n'.join(categories))
+    assert list(CityscapesDataset(**kwargs).CLASSES) == categories
+
+    # classes.txt with sub categories
+    categories = ['road', 'sidewalk', 'building']
+    with open(classes_path, 'w') as f:
+        f.write('\n'.join(categories))
+    assert list(CityscapesDataset(**kwargs).CLASSES) == categories
+
+    # classes.txt with unknown categories
+    categories = ['road', 'sidewalk', 'unknown']
+    with open(classes_path, 'w') as f:
+        f.write('\n'.join(categories))
+
+    with pytest.raises(ValueError):
+        CityscapesDataset(**kwargs)
+
+    tmp_file.close()
+    os.remove(classes_path)
+    assert not osp.exists(classes_path)
+
+
 def test_palette():
     assert CityscapesDataset.PALETTE == get_palette('cityscapes')
     assert PascalVOCDataset.PALETTE == get_palette('voc') == get_palette(