test: test path exists

Signed-off-by: Inhyuk Andy Cho <andy.inhyuk.jo@intel.com>

tests/unit/core/data/manager/test_dataset_manager.py

@@ -4,6 +4,7 @@
 #
 import shutil
 from typing import List
+from tempfile import TemporaryDirectory
 
 import datumaro as dm
 import pytest
@@ -76,6 +77,12 @@ def test_get_image_path(self, task, subset):
         )
         assert random_data is None
 
+        with TemporaryDirectory() as temp_dir:
+            random_data = DatasetManager.get_image_path(
+                generate_datumaro_dataset_item(item_id="0", subset=subset, task=task, temp_dir=temp_dir)
+            )
+            assert random_data is not None
+
     @e2e_pytest_unit
     @pytest.mark.parametrize("task", AVAILABLE_TASKS)
     @pytest.mark.parametrize("subset", AVAILABLE_SUBSETS)

tests/unit/core/data/test_helpers.py

@@ -2,8 +2,10 @@
 # Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 #
-from typing import List
+from typing import List, Optional
+import os
 
+import cv2
 import datumaro as dm
 import numpy as np
 
@@ -86,6 +88,7 @@ def generate_datumaro_dataset_item(
     task: str,
     image_shape: np.array = np.array((5, 5, 3)),
     mask_shape: np.array = np.array((5, 5)),
+    temp_dir: Optional[str] = None,
 ) -> dm.DatasetItem:
     """Generate Datumaro DatasetItem.
 
@@ -95,6 +98,7 @@ def generate_datumaro_dataset_item(
         task (str): task type, e.g. "classification"
         image_shape (np.array): the shape of image.
         image_shape (np.array): the shape of mask.
+        temp_dir (str): directory to save image data
 
     Returns:
         dm.DatasetItem: Datumaro DatasetItem
@@ -105,6 +109,11 @@ def generate_datumaro_dataset_item(
         "segmentation": dm.Mask(np.zeros(mask_shape)),
     }
 
+    if temp_dir:
+        path = os.path.join(temp_dir, "image.png")
+        cv2.imwrite(path, np.ones(image_shape))
+        return dm.DatasetItem(id=item_id, subset=subset, image=path, annotations=[ann_task_dict[task]])
+
     return dm.DatasetItem(id=item_id, subset=subset, image=np.ones(image_shape), annotations=[ann_task_dict[task]])