Support cloud-storage paths for Pascal VOC semantic segmentation imports#872
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LeonardoRosaa merged 12 commits intomainfrom Apr 4, 2026
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📝 WalkthroughWalkthroughAdds cloud-storage (remote URI) support for Pascal VOC semantic segmentation imports by preserving remote paths, introduces a path-normalization helper, pins Changes
Sequence Diagram(s)sequenceDiagram
participant ExampleScript as Example Script
participant FSSpec as fsspec (S3 / memory)
participant ImageDataset as ImageDataset.add_samples_from_pascal_voc_segmentations
participant DB as DB / Storage
ExampleScript->>FSSpec: resolve images_path, masks_path, class mapping
ExampleScript->>ImageDataset: call add_samples_from_pascal_voc_segmentations(...)
ImageDataset->>FSSpec: list/read image & mask files (preserve remote URIs)
ImageDataset->>DB: create samples with file_path_abs and semantic annotations
ImageDataset->>DB: generate and store embeddings
ExampleScript->>DB: start GUI (reads samples/annotations)
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Possibly related PRs
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🚥 Pre-merge checks | ✅ 2 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (2 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
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Verify each finding against the current code and only fix it if needed.
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In `@lightly_studio/pyproject.toml`:
- Line 36: The labelformat dependency in pyproject.toml is pinned to a short
commit hash ("labelformat @
git+https://github.com/lightly-ai/labelformat.git@f9cf7d5"); replace the short
SHA with the full 40-character commit SHA
(f9cf7d51dd2b058d27d91d733a87475a404c1f18) so the dependency line uses the
complete hash to ensure deterministic installs and avoid collisions.
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CHANGELOG.mdlightly_studio/pyproject.tomllightly_studio/src/lightly_studio/core/image/image_dataset.pylightly_studio/src/lightly_studio/examples/example_semantic_segmentation_s3.pylightly_studio/tests/core/image/test_image_dataset__pascal_voc.py
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🧹 Nitpick comments (1)
lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py (1)
200-237: Consider extracting shared annotation assertions into a helper.The annotation checks are duplicated across tests; a small helper would reduce maintenance overhead and make future schema changes easier to update.
♻️ Optional refactor sketch
+def _assert_sample_annotations(sample, expected_file_path: str | None = None) -> None: + if expected_file_path is not None: + assert sample.file_path_abs == expected_file_path + annotations = sorted(sample.annotations, key=lambda ann: ann.label) + # shared assertions for bg/cat/dog ... + # in both tests: -annotations = sorted(samples[0].annotations, key=lambda ann: ann.label) -... many repeated asserts ... +_assert_sample_annotations(samples[0], expected_file_path=f"{images_path}/image1.jpg")🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py` around lines 200 - 237, Extract the repeated assertion blocks into a small helper function (e.g., assert_segmentation_annotation) that accepts the annotation object (or its fields: label, x, y, width, height, segmentation_mask) and performs the isinstance check and all equality assertions; then replace the duplicated blocks in this test with calls like assert_segmentation_annotation(annotations[0], label="bg", x=0, y=0, width=4, height=3, segmentation_mask=[...]) and similarly for other annotations and samples[1].annotations[0]; ensure the helper references SemanticSegmentationAnnotation and uses the same assertion semantics so behavior is unchanged.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Nitpick comments:
In `@lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py`:
- Around line 200-237: Extract the repeated assertion blocks into a small helper
function (e.g., assert_segmentation_annotation) that accepts the annotation
object (or its fields: label, x, y, width, height, segmentation_mask) and
performs the isinstance check and all equality assertions; then replace the
duplicated blocks in this test with calls like
assert_segmentation_annotation(annotations[0], label="bg", x=0, y=0, width=4,
height=3, segmentation_mask=[...]) and similarly for other annotations and
samples[1].annotations[0]; ensure the helper references
SemanticSegmentationAnnotation and uses the same assertion semantics so behavior
is unchanged.
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lightly_studio/pyproject.tomllightly_studio/tests/core/image/test_image_dataset__pascal_voc.py
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🧹 Nitpick comments (1)
lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py (1)
200-237: Consider extracting shared annotation assertions into a helper.The annotation assertions (lines 200-237) duplicate those in the first test (lines 67-108). While test duplication is acceptable for readability, extracting a helper could reduce maintenance burden if assertion logic changes.
def _assert_expected_annotations(samples: list) -> None: """Verify semantic segmentation annotations for standard test masks.""" annotations = sorted(samples[0].annotations, key=lambda ann: ann.label) # ... shared assertion logicThis is optional since test independence is also valuable.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py` around lines 200 - 237, Extract the repeated annotation assertion logic into a single helper function (e.g., _assert_expected_annotations) that takes the samples list and performs the shared checks currently duplicated in the block that inspects samples[0].annotations and samples[1].annotations; move the sorted(samples[0].annotations, key=lambda ann: ann.label) logic and all assertions about SemanticSegmentationAnnotation, .label, .x, .y, .width, .height, and .segmentation_mask into that helper and call it from both test locations to eliminate duplication while keeping test behavior identical.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Nitpick comments:
In `@lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py`:
- Around line 200-237: Extract the repeated annotation assertion logic into a
single helper function (e.g., _assert_expected_annotations) that takes the
samples list and performs the shared checks currently duplicated in the block
that inspects samples[0].annotations and samples[1].annotations; move the
sorted(samples[0].annotations, key=lambda ann: ann.label) logic and all
assertions about SemanticSegmentationAnnotation, .label, .x, .y, .width,
.height, and .segmentation_mask into that helper and call it from both test
locations to eliminate duplication while keeping test behavior identical.
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lightly_studio/tests/core/image/test_image_dataset__pascal_voc.py
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MalteEbner
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Apr 2, 2026
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Code mostly looks good to me, but some details should be improved.
Will you update the docs in a follow-up PR?
Co-authored-by: MalteEbner <malte.ebner@gmail.com>
…gmentation' of https://github.com/lightly-ai/lightly-studio into leonardo-lig-8784-support-cloud-storage-for-semantic-segmentation
MalteEbner
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Apr 4, 2026
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What has changed and why?
This PR enables Pascal VOC semantic segmentation imports from cloud/object storage URIs.
How has it been tested?
Unit tests
Did you update CHANGELOG.md?
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New Features
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