- Fixed detection medium findings across adapters, mask non-max merge, sinks, segmentation parsing, LineZone history, and mask ROI handling
- Fixed mask non-max merge deprecation warnings to honor the standard warning opt-out and include version context
- Fixed mask non-max merge validation for invalid IoU thresholds
- Fixed CompactMask non-max merge grouping to update merged mask candidates correctly
- Fixed selected and compacted detections to copy arrays and metadata, preventing mutations from leaking back to source detections
- Fixed LineZone crossing history eviction to tolerate short tracking gaps and evict stale state per tracker/class key
- Fixed semantic segmentation handling to preserve class ID 0
- Improved mask ROI conversion performance by avoiding unnecessary full-frame copies and repeated scans
- Updated JSONSink changelog/docs to document native bool/int/float output while leaving CSVSink unchanged
- Updated detection docstrings for mask parsing, selection copy semantics, validation errors, and argument readability guidance
---------
Co-authored-by: Codex <codex@openai.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
- `from_tensorflow` scaled boxes in place on the array returned by `.numpy()`, which can share memory with the source tensor — corrupting caller data and double-scaling on a repeat call; copy before scaling
- `from_lmm` raised a bare `KeyError` for `MOONDREAM` and `QWEN_3_VL`, which the enum and docstring advertise; map both to their `VLM` members
- `from_deepseek_vl_2` returned a `(0,)`-shaped `xyxy` on empty output, so a zero-detection response crashed the `Detections` constructor; return `(0, 4)` like the other parsers
- `extract_ultralytics_masks` binarized bilinear-resized masks with `> 0`, dilating every mask at object boundaries; threshold at 0.5 to match Ultralytics
- add connector coverage: fake-result shims and round-trip tests (N>1, N=1, empty) for the nine previously untested `from_*` connectors and the `detection/tools/transformers.py` processors; one empty-`segments_info` panoptic case is xfail-marked pending a separate fix
* test(ci-fix): drop deprecated Pillow mode arg from panoptic helpers
* test(coverage): add from_qwen_3_vl end-to-end parametrized tests
* test(quality): harden test isolation, xfail strictness, and kwarg forwarding
* fix(detection): fix class_name empty dtype; annotate mask threshold asymmetry
* chore: ruff-format cleanup (blank lines)
---------
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
- Added compact COCO RLE mask ingestion with a `CompactMask` representation and optional compact mask parsing during inference for substantially lower memory usage on sparse segmentation results.
- Added `Detections.to_compact_masks()` to convert existing dense masks into compact masks while preserving detection and collection metadata.
- Improved compact mask decoding performance with cropped RLE processing, batched decoding on the fast path, vectorized decoding for small images, optimized RLE traversal, and faster delta decoding.
- Improved mask metrics to operate directly on `CompactMask` instances, preserving the compact representation while producing results equivalent to dense masks.
- Fixed mixed-modality inference handling by keeping detections and masks aligned, isolating malformed RLE failures to individual predictions where possible, and falling back safely when decoding cannot be completed.
- Fixed compact mask conversion and parsing to preserve dense-mask pixel content across public parsing and slicing paths, while correctly documenting and applying the intended bbox-cropping behavior for compact COCO RLE masks.
- Improved COCO RLE validation with checks for malformed payloads, invalid dimensions, count overflows, image size limits, count-sum mismatches, bounding-box mismatches, and safe fallback behavior for incompatible mask sizes.
- Added inference benchmarks and documentation demonstrating the memory and inference-time characteristics of compact masks, including guidance on their performance tradeoffs and behavior.
---------
Co-authored-by: Codex <codex@openai.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
process_roboflow_result appended a mask only for predictions carrying one
(RLE or polygon), while xyxy/confidence/class_id were appended for every
prediction. A result mixing masked and box-only predictions (e.g. a
segmentation batch where one polygon is empty) produced a mask array shorter
than the boxes, so Detections.from_inference raised a shape-mismatch error.
Append None for box-only predictions and build the mask array only when every
prediction has a mask, otherwise drop masks to preserve alignment, mirroring
the tracker_id handling. Fully-masked and mask-free results are unchanged.
- Update `masks` Returns clause to document partial-drop case and corrupt-RLE blast radius (D1+C1)
- Remove stale "known limitation" note from from_inference docstring; describe actual behavior (D2)
- Extract _all_present_or_none() helper; eliminate duplicated partial-drop-warn pattern (S1)
---------
Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
process_roboflow_result appended tracker_id only for predictions that carried
one, while xyxy/confidence/class_id were appended for every prediction. A
result where some predictions are tracked and others are not produced a
tracker_id array shorter than the boxes, so Detections.from_inference raised
"tracker_id must be a 1D np.ndarray with shape (N,)".
Collect tracker_id for every prediction (None when absent) and build the array
only when all detections carry one, otherwise leave it None. Fully-tracked and
untracked results are unchanged.
---------
Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
* Detections.from_inference works on RLE-encoded masks
* Apply suggestions from code review
* fix: harden RLE handling in from_inference and decoder
* lint: fix cv2.fillPoly color type in polygon_to_mask
* fix: resize RLE mask to image dims when size mismatches
* fix: pass RLE counts directly in coco_annotations_to_masks
* test: document mixed RLE + box-only batch misalignment
* test: add compressed RLE iscrowd case to coco_annotations_to_detections
* fix: cast polygon mask to bool in process_roboflow_result
* fix: log warning when RLE decode fails in process_roboflow_result
* fix: replace assert with ValueError in rle_to_mask
* test: add bytes invalid UTF-8 case to rle_to_mask tests
* docs: note rle_to_mask dtype change from uint8 to bool in changelog
* refactor: tighten rle_to_mask NDArray input type to np.integer[Any]
* refactor: drop mask_to_rle overloads; cast at call site
* docs: clarify COCO column-major RLE order in rle_to_mask/mask_to_rle
* refactor: update @deprecated annotations and docstrings for mask_to_rle/rle_to_mask; add pydeprecate dependency
* refactor: replace mask_to_rle body with `void` function to suppress unused argument warnings
---------
Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* refactor: reorganize project structure and update module imports
* configure setuptools to use 'src' layout and adjust package discovery
* refactor: move tests to `tests` directory and update imports accordingly
* update lint and mypy configurations to align with `src` and `tests` structure
* update test imports to use corrected `tests.helpers` module path
* fix(pre_commit): 🎨 auto format pre-commit hooks
Jirka Borovec
Abhijith Neil Abraham
Agis Kounelis
Mahbod
Lee Clement