Fix test utils bug when two file names have same ending.

PiperOrigin-RevId: 485780917

mediapipe/tasks/python/test/metadata/metadata_test.py

@@ -27,6 +27,8 @@ from mediapipe.tasks.metadata import schema_py_generated as _schema_fb
 from mediapipe.tasks.python.metadata import metadata as _metadata
 from mediapipe.tasks.python.test import test_utils
 
+_TEST_DATA_DIR = "mediapipe/tasks/testdata/metadata"
+
 
 class Tokenizer(enum.Enum):
   BERT_TOKENIZER = 0
@@ -810,7 +812,8 @@ class MetadataDisplayerTest(MetadataTest):
     actual_json = _metadata.convert_to_json(actual_buffer)
 
     # Verifies the generated json file.
-    golden_json_file_path = test_utils.get_test_data_path("golden_json.json")
+    golden_json_file_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, "golden_json.json"))
     with open(golden_json_file_path, "r") as f:
       expected = f.read()
     self.assertEqual(actual_json, expected)
@@ -821,7 +824,8 @@ class MetadataDisplayerTest(MetadataTest):
     actual = displayer.get_metadata_json()
 
     # Verifies the generated json file.
-    golden_json_file_path = test_utils.get_test_data_path("golden_json.json")
+    golden_json_file_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, "golden_json.json"))
     expected = _read_file(golden_json_file_path, "r")
     self.assertEqual(actual, expected)
 
@@ -848,7 +852,8 @@ class MetadataUtilTest(MetadataTest):
     metadata_json = _metadata.convert_to_json(metadata_buf)
 
     # Verifies the generated json file.
-    golden_json_file_path = test_utils.get_test_data_path("golden_json.json")
+    golden_json_file_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, "golden_json.json"))
     expected = _read_file(golden_json_file_path, "r")
     self.assertEqual(metadata_json, expected)
 

mediapipe/tasks/python/test/metadata/metadata_writers/image_classifier_test.py

@@ -14,6 +14,8 @@
 # ==============================================================================
 """Tests for metadata_writer.image_classifier."""
 
+import os
+
 from absl.testing import absltest
 from absl.testing import parameterized
 
@@ -23,18 +25,25 @@ from mediapipe.tasks.python.metadata.metadata_writers import image_classifier
 from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer
 from mediapipe.tasks.python.test import test_utils
 
+_TEST_DATA_DIR = "mediapipe/tasks/testdata/metadata"
 _FLOAT_MODEL = test_utils.get_test_data_path(
-    "mobilenet_v2_1.0_224_without_metadata.tflite")
+    os.path.join(_TEST_DATA_DIR,
+                 "mobilenet_v2_1.0_224_without_metadata.tflite"))
 _QUANT_MODEL = test_utils.get_test_data_path(
-    "mobilenet_v2_1.0_224_quant_without_metadata.tflite")
+    os.path.join(_TEST_DATA_DIR,
-_LABEL_FILE = test_utils.get_test_data_path("labels.txt")
+                 "mobilenet_v2_1.0_224_quant_without_metadata.tflite"))
-_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path("score_calibration.txt")
+_LABEL_FILE = test_utils.get_test_data_path(
+    os.path.join(_TEST_DATA_DIR, "labels.txt"))
+_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path(
+    os.path.join(_TEST_DATA_DIR, "score_calibration.txt"))
 _SCORE_CALIBRATION_FILENAME = "score_calibration.txt"
 _DEFAULT_SCORE_CALIBRATION_VALUE = 0.2
 _NORM_MEAN = 127.5
 _NORM_STD = 127.5
-_FLOAT_JSON = test_utils.get_test_data_path("mobilenet_v2_1.0_224.json")
+_FLOAT_JSON = test_utils.get_test_data_path(
-_QUANT_JSON = test_utils.get_test_data_path("mobilenet_v2_1.0_224_quant.json")
+    os.path.join(_TEST_DATA_DIR, "mobilenet_v2_1.0_224.json"))
+_QUANT_JSON = test_utils.get_test_data_path(
+    os.path.join(_TEST_DATA_DIR, "mobilenet_v2_1.0_224_quant.json"))
 
 
 class ImageClassifierTest(parameterized.TestCase):

mediapipe/tasks/python/test/metadata/metadata_writers/metadata_info_test.py

@@ -14,6 +14,7 @@
 # ==============================================================================
 """Tests for metadata info classes."""
 
+import os
 import tempfile
 
 from absl.testing import absltest
@@ -26,13 +27,15 @@ from mediapipe.tasks.python.metadata import metadata as _metadata
 from mediapipe.tasks.python.metadata.metadata_writers import metadata_info
 from mediapipe.tasks.python.test import test_utils
 
-_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path("score_calibration.txt")
+_TEST_DATA_DIR = "mediapipe/tasks/testdata/metadata"
+_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path(
+    os.path.join(_TEST_DATA_DIR, "score_calibration.txt"))
 
 
 class GeneralMdTest(absltest.TestCase):
 
   _EXPECTED_GENERAL_META_JSON = test_utils.get_test_data_path(
-      "general_meta.json")
+      os.path.join(_TEST_DATA_DIR, "general_meta.json"))
 
   def test_create_metadata_should_succeed(self):
     general_md = metadata_info.GeneralMd(
@@ -59,7 +62,7 @@ class GeneralMdTest(absltest.TestCase):
 class AssociatedFileMdTest(absltest.TestCase):
 
   _EXPECTED_META_JSON = test_utils.get_test_data_path(
-      "associated_file_meta.json")
+      os.path.join(_TEST_DATA_DIR, "associated_file_meta.json"))
 
   def test_create_metadata_should_succeed(self):
     file_md = metadata_info.AssociatedFileMd(
@@ -92,11 +95,11 @@ class TensorMdTest(parameterized.TestCase):
   _LABEL_FILE_EN = "labels.txt"
   _LABEL_FILE_CN = "labels_cn.txt"  # Locale label file in Chinese.
   _EXPECTED_FEATURE_TENSOR_JSON = test_utils.get_test_data_path(
-      "feature_tensor_meta.json")
+      os.path.join(_TEST_DATA_DIR, "feature_tensor_meta.json"))
   _EXPECTED_IMAGE_TENSOR_JSON = test_utils.get_test_data_path(
-      "image_tensor_meta.json")
+      os.path.join(_TEST_DATA_DIR, "image_tensor_meta.json"))
   _EXPECTED_BOUNDING_BOX_TENSOR_JSON = test_utils.get_test_data_path(
-      "bounding_box_tensor_meta.json")
+      os.path.join(_TEST_DATA_DIR, "bounding_box_tensor_meta.json"))
 
   @parameterized.named_parameters(
       {
@@ -142,11 +145,11 @@ class InputImageTensorMdTest(parameterized.TestCase):
   _NORM_STD = (127.5, 127.5, 127.5)
   _COLOR_SPACE_TYPE = _metadata_fb.ColorSpaceType.RGB
   _EXPECTED_FLOAT_TENSOR_JSON = test_utils.get_test_data_path(
-      "input_image_tensor_float_meta.json")
+      os.path.join(_TEST_DATA_DIR, "input_image_tensor_float_meta.json"))
   _EXPECTED_UINT8_TENSOR_JSON = test_utils.get_test_data_path(
-      "input_image_tensor_uint8_meta.json")
+      os.path.join(_TEST_DATA_DIR, "input_image_tensor_uint8_meta.json"))
   _EXPECTED_UNSUPPORTED_TENSOR_JSON = test_utils.get_test_data_path(
-      "input_image_tensor_unsupported_meta.json")
+      os.path.join(_TEST_DATA_DIR, "input_image_tensor_unsupported_meta.json"))
 
   @parameterized.named_parameters(
       {
@@ -196,11 +199,12 @@ class ClassificationTensorMdTest(parameterized.TestCase):
   _LABEL_FILE_CN = "labels_cn.txt"  # Locale label file in Chinese.
   _CALIBRATION_DEFAULT_SCORE = 0.2
   _EXPECTED_FLOAT_TENSOR_JSON = test_utils.get_test_data_path(
-      "classification_tensor_float_meta.json")
+      os.path.join(_TEST_DATA_DIR, "classification_tensor_float_meta.json"))
   _EXPECTED_UINT8_TENSOR_JSON = test_utils.get_test_data_path(
-      "classification_tensor_uint8_meta.json")
+      os.path.join(_TEST_DATA_DIR, "classification_tensor_uint8_meta.json"))
   _EXPECTED_UNSUPPORTED_TENSOR_JSON = test_utils.get_test_data_path(
-      "classification_tensor_unsupported_meta.json")
+      os.path.join(_TEST_DATA_DIR,
+                   "classification_tensor_unsupported_meta.json"))
 
   @parameterized.named_parameters(
       {
@@ -243,9 +247,9 @@ class ClassificationTensorMdTest(parameterized.TestCase):
 class ScoreCalibrationMdTest(absltest.TestCase):
   _DEFAULT_VALUE = 0.2
   _EXPECTED_TENSOR_JSON = test_utils.get_test_data_path(
-      "score_calibration_tensor_meta.json")
+      os.path.join(_TEST_DATA_DIR, "score_calibration_tensor_meta.json"))
   _EXPECTED_MODEL_META_JSON = test_utils.get_test_data_path(
-      "score_calibration_file_meta.json")
+      os.path.join(_TEST_DATA_DIR, "score_calibration_file_meta.json"))
 
   def test_create_metadata_should_succeed(self):
     score_calibration_md = metadata_info.ScoreCalibrationMd(
@@ -310,7 +314,7 @@ class ScoreCalibrationMdTest(absltest.TestCase):
 class ScoreThresholdingMdTest(absltest.TestCase):
   _DEFAULT_GLOBAL_THRESHOLD = 0.5
   _EXPECTED_TENSOR_JSON = test_utils.get_test_data_path(
-      "score_thresholding_meta.json")
+      os.path.join(_TEST_DATA_DIR, "score_thresholding_meta.json"))
 
   def test_create_metadata_should_succeed(self):
     score_thresholding_md = metadata_info.ScoreThresholdingMd(

mediapipe/tasks/python/test/metadata/metadata_writers/metadata_writer_test.py

@@ -21,9 +21,12 @@ from absl.testing import absltest
 from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer
 from mediapipe.tasks.python.test import test_utils
 
+_TEST_DATA_DIR = 'mediapipe/tasks/testdata/metadata'
+
 _IMAGE_CLASSIFIER_MODEL = test_utils.get_test_data_path(
-    'mobilenet_v1_0.25_224_1_default_1.tflite')
+    os.path.join(_TEST_DATA_DIR, 'mobilenet_v1_0.25_224_1_default_1.tflite'))
-_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path('score_calibration.txt')
+_SCORE_CALIBRATION_FILE = test_utils.get_test_data_path(
+    os.path.join(_TEST_DATA_DIR, 'score_calibration.txt'))
 
 
 class LabelsTest(absltest.TestCase):
@@ -85,8 +88,7 @@ class ScoreCalibrationTest(absltest.TestCase):
       with self.assertRaisesRegex(
           ValueError,
           'Expected empty lines or 3 or 4 parameters per line in score '
-          'calibration file, but got 2.'
+          'calibration file, but got 2.'):
-      ):
         metadata_writer.ScoreCalibration.create_from_file(
             metadata_writer.ScoreCalibration.transformation_types.LOG,
             test_file)

mediapipe/tasks/python/test/test_utils.py

@@ -42,13 +42,15 @@ def test_srcdir():
     raise RuntimeError("Missing TEST_SRCDIR environment.")
 
 
-def get_test_data_path(file_or_dirname: str) -> str:
+def get_test_data_path(file_or_dirname_path: str) -> str:
   """Returns full test data path."""
   for (directory, subdirs, files) in os.walk(test_srcdir()):
     for f in subdirs + files:
-      if f.endswith(file_or_dirname):
+      path = os.path.join(directory, f)
-        return os.path.join(directory, f)
+      if path.endswith(file_or_dirname_path):
-  raise ValueError("No %s in test directory" % file_or_dirname)
+        return path
+  raise ValueError("No %s in test directory: %s." %
+                   (file_or_dirname_path, test_srcdir()))
 
 
 def create_calibration_file(file_dir: str,

mediapipe/tasks/python/test/vision/image_classifier_test.py

@@ -14,10 +14,12 @@
 """Tests for image classifier."""
 
 import enum
+import os
 from unittest import mock
 
 from absl.testing import absltest
 from absl.testing import parameterized
+
 import numpy as np
 
 from mediapipe.python._framework_bindings import image
@@ -48,6 +50,7 @@ _ALLOW_LIST = ['cheeseburger', 'guacamole']
 _DENY_LIST = ['cheeseburger']
 _SCORE_THRESHOLD = 0.5
 _MAX_RESULTS = 3
+_TEST_DATA_DIR = 'mediapipe/tasks/testdata/vision'
 
 
 def _generate_empty_results(timestamp_ms: int) -> _ClassificationResult:
@@ -124,8 +127,10 @@ class ImageClassifierTest(parameterized.TestCase):
   def setUp(self):
     super().setUp()
     self.test_image = _Image.create_from_file(
-        test_utils.get_test_data_path(_IMAGE_FILE))
+        test_utils.get_test_data_path(
-    self.model_path = test_utils.get_test_data_path(_MODEL_FILE)
+            os.path.join(_TEST_DATA_DIR, _IMAGE_FILE)))
+    self.model_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, _MODEL_FILE))
 
   def test_create_from_file_succeeds_with_valid_model_path(self):
     # Creates with default option and valid model file successfully.
@@ -220,7 +225,8 @@ class ImageClassifierTest(parameterized.TestCase):
     with _ImageClassifier.create_from_options(options) as classifier:
       # Load the test image.
       test_image = _Image.create_from_file(
-          test_utils.get_test_data_path('multi_objects.jpg'))
+          test_utils.get_test_data_path(
+              os.path.join(_TEST_DATA_DIR, 'multi_objects.jpg')))
       # NormalizedRect around the soccer ball.
       roi = _NormalizedRect(
           x_center=0.532, y_center=0.521, width=0.164, height=0.427)
@@ -409,7 +415,8 @@ class ImageClassifierTest(parameterized.TestCase):
     with _ImageClassifier.create_from_options(options) as classifier:
       # Load the test image.
       test_image = _Image.create_from_file(
-          test_utils.get_test_data_path('multi_objects.jpg'))
+          test_utils.get_test_data_path(
+              os.path.join(_TEST_DATA_DIR, 'multi_objects.jpg')))
       # NormalizedRect around the soccer ball.
       roi = _NormalizedRect(
           x_center=0.532, y_center=0.521, width=0.164, height=0.427)
@@ -482,7 +489,8 @@ class ImageClassifierTest(parameterized.TestCase):
   def test_classify_async_succeeds_with_region_of_interest(self):
     # Load the test image.
     test_image = _Image.create_from_file(
-        test_utils.get_test_data_path('multi_objects.jpg'))
+        test_utils.get_test_data_path(
+            os.path.join(_TEST_DATA_DIR, 'multi_objects.jpg')))
     # NormalizedRect around the soccer ball.
     roi = _NormalizedRect(
         x_center=0.532, y_center=0.521, width=0.164, height=0.427)

mediapipe/tasks/python/test/vision/image_segmenter_test.py

@@ -14,6 +14,7 @@
 """Tests for image segmenter."""
 
 import enum
+import os
 from typing import List
 from unittest import mock
 
@@ -43,6 +44,7 @@ _IMAGE_FILE = 'segmentation_input_rotation0.jpg'
 _SEGMENTATION_FILE = 'segmentation_golden_rotation0.png'
 _MASK_MAGNIFICATION_FACTOR = 10
 _MASK_SIMILARITY_THRESHOLD = 0.98
+_TEST_DATA_DIR = 'mediapipe/tasks/testdata/vision'
 
 
 def _similar_to_uint8_mask(actual_mask, expected_mask):
@@ -71,12 +73,16 @@ class ImageSegmenterTest(parameterized.TestCase):
     super().setUp()
     # Load the test input image.
     self.test_image = _Image.create_from_file(
-        test_utils.get_test_data_path(_IMAGE_FILE))
+        test_utils.get_test_data_path(
+            os.path.join(_TEST_DATA_DIR, _IMAGE_FILE)))
     # Loads ground truth segmentation file.
     gt_segmentation_data = cv2.imread(
-        test_utils.get_test_data_path(_SEGMENTATION_FILE), cv2.IMREAD_GRAYSCALE)
+        test_utils.get_test_data_path(
+            os.path.join(_TEST_DATA_DIR, _SEGMENTATION_FILE)),
+        cv2.IMREAD_GRAYSCALE)
     self.test_seg_image = _Image(_ImageFormat.GRAY8, gt_segmentation_data)
-    self.model_path = test_utils.get_test_data_path(_MODEL_FILE)
+    self.model_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, _MODEL_FILE))
 
   def test_create_from_file_succeeds_with_valid_model_path(self):
     # Creates with default option and valid model file successfully.

mediapipe/tasks/python/test/vision/object_detector_test.py

@@ -14,6 +14,7 @@
 """Tests for object detector."""
 
 import enum
+import os
 from unittest import mock
 
 from absl.testing import absltest
@@ -87,6 +88,7 @@ _ALLOW_LIST = ['cat', 'dog']
 _DENY_LIST = ['cat']
 _SCORE_THRESHOLD = 0.3
 _MAX_RESULTS = 3
+_TEST_DATA_DIR = 'mediapipe/tasks/testdata/vision'
 
 
 class ModelFileType(enum.Enum):
@@ -99,8 +101,10 @@ class ObjectDetectorTest(parameterized.TestCase):
   def setUp(self):
     super().setUp()
     self.test_image = _Image.create_from_file(
-        test_utils.get_test_data_path(_IMAGE_FILE))
+        test_utils.get_test_data_path(
-    self.model_path = test_utils.get_test_data_path(_MODEL_FILE)
+            os.path.join(_TEST_DATA_DIR, _IMAGE_FILE)))
+    self.model_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, _MODEL_FILE))
 
   def test_create_from_file_succeeds_with_valid_model_path(self):
     # Creates with default option and valid model file successfully.
@@ -395,5 +399,6 @@ class ObjectDetectorTest(parameterized.TestCase):
       detector.detect_async(self.test_image, timestamp)
     detector.close()
 
+
 if __name__ == '__main__':
   absltest.main()