Fix face landmark batch output existence check

ASL Developer Community/src/asl_data_pipeline/preprocessing/face_landmark_extractor/extractor.py

@@ -369,10 +369,15 @@ def process_batch(self) -> BatchFaceLandmarkResult:
         """Process a batch of frames from the S3 manifest."""
         start_time = datetime.now(timezone.utc)
 
-        if not self.config.force_write and self.s3_client.check_output_exists():
-            raise FaceLandmarkExtractorError(
-                f"Output directory already exists: {self.config.s3.output_uri}. " "Use force_write=True to overwrite."
+        if not self.config.force_write:
+            existing_objects = self.s3_client.list_files(
+                bucket=self.s3_client.output_bucket, prefix=self.s3_client.output_prefix
             )
+            if existing_objects:
+                raise FaceLandmarkExtractorError(
+                    f"Output folder already exists at {self.config.s3.output_uri} "
+                    f"and contains {len(existing_objects)} objects. Set force_write=True to overwrite."
+                )
 
         try:
             # Load manifest

ASL Developer Community/tests/preprocessing/face_landmark_extractor/__init__.py

@@ -0,0 +1 @@
+

ASL Developer Community/tests/preprocessing/face_landmark_extractor/test_extractor.py

@@ -0,0 +1,68 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Unit tests for the FaceLandmarkExtractor."""
+
+import sys
+import types
+from unittest.mock import MagicMock
+
+import pytest
+
+from asl_data_pipeline.models.s3 import InputType, S3Config
+
+mediapipe_stub = types.ModuleType("mediapipe")
+framework_stub = types.ModuleType("mediapipe.framework")
+formats_stub = types.ModuleType("mediapipe.framework.formats")
+landmark_pb2_stub = types.ModuleType("mediapipe.framework.formats.landmark_pb2")
+
+sys.modules.setdefault("mediapipe", mediapipe_stub)
+sys.modules.setdefault("mediapipe.framework", framework_stub)
+sys.modules.setdefault("mediapipe.framework.formats", formats_stub)
+sys.modules.setdefault("mediapipe.framework.formats.landmark_pb2", landmark_pb2_stub)
+
+from asl_data_pipeline.preprocessing.face_landmark_extractor.models import FaceLandmarkExtractorConfig  # noqa: E402
+from asl_data_pipeline.preprocessing.face_landmark_extractor.extractor import (  # noqa: E402
+    FaceLandmarkExtractor,
+    FaceLandmarkExtractorError,
+)
+
+
+def test_face_landmark_extractor_process_batch_raises_if_output_exists():
+    """Test that batch processing refuses to overwrite existing output when force_write is disabled."""
+    config = FaceLandmarkExtractorConfig(
+        s3=S3Config(
+            input_uri="s3://dummy-bucket/manifest.jsonl",
+            output_uri="s3://dummy-bucket/face-landmarks/",
+            input_type=InputType.MANIFEST,
+        ),
+        force_write=False,
+    )
+
+    extractor = FaceLandmarkExtractor.__new__(FaceLandmarkExtractor)
+    extractor.config = config
+    extractor.s3_client = MagicMock()
+    extractor.s3_client.output_bucket = "dummy-bucket"
+    extractor.s3_client.output_prefix = "face-landmarks/"
+    extractor.s3_client.list_files.return_value = ["face-landmarks/existing.json"]
+
+    with pytest.raises(FaceLandmarkExtractorError, match="Output folder already exists"):
+        extractor.process_batch()
+
+    extractor.s3_client.list_files.assert_called_once_with(
+        bucket="dummy-bucket",
+        prefix="face-landmarks/",
+    )
+    extractor.s3_client.download_file_to_bytes.assert_not_called()