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Oleksandr Bezdieniezhnykh
142c6c4de8
- Replaced module-level path variables in constants.py with a structured Pydantic Config class. - Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure. - Fixed bugs related to image processing and model saving. - Enhanced test infrastructure to accommodate the new configuration approach. This refactor improves code maintainability and clarity by centralizing configuration management.
51 lines
1.6 KiB
Markdown
51 lines
1.6 KiB
Markdown
# NMS Overlap Removal Tests
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**Task**: AZ-162_test_nms
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**Name**: NMS Overlap Removal Tests
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**Description**: Implement 3 tests for non-maximum suppression — overlapping kept by confidence, non-overlapping preserved, chain overlap resolution
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**Complexity**: 1 point
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**Dependencies**: AZ-152_test_infrastructure
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**Component**: Blackbox Tests
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**Jira**: AZ-162
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**Epic**: AZ-151
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## Problem
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The NMS module removes overlapping detections based on IoU threshold (0.3), keeping the higher-confidence detection. Tests verify all overlap scenarios.
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## Outcome
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- 3 passing pytest tests in `tests/test_nms.py`
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## Scope
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### Included
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- BT-NMS-01: Overlapping detections — keep higher confidence (IoU > 0.3 → 1 kept)
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- BT-NMS-02: Non-overlapping detections — keep both (IoU < 0.3 → 2 kept)
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- BT-NMS-03: Chain overlap resolution (A↔B, B↔C → ≤ 2 kept)
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### Excluded
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- Integration with inference pipeline (separate task)
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## Acceptance Criteria
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**AC-1: Overlap removal**
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Given 2 Detections at same position, confidence 0.9 and 0.5, IoU > 0.3
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When remove_overlapping_detections() runs
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Then 1 detection returned (confidence 0.9)
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**AC-2: Non-overlapping preserved**
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Given 2 Detections at distant positions, IoU < 0.3
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When remove_overlapping_detections() runs
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Then 2 detections returned
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**AC-3: Chain overlap**
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Given 3 Detections: A overlaps B, B overlaps C, A doesn't overlap C
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When remove_overlapping_detections() runs
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Then ≤ 2 detections; highest confidence per overlapping pair kept
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## Constraints
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- Detection objects constructed in-memory (no fixture files)
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- IoU threshold is 0.3 (from constants or hardcoded in NMS)
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