Oleksandr Bezdieniezhnykh
cbf370c765
- Changed the directory structure for task specifications to include a dedicated `todo/` folder within `_docs/02_tasks/` for tasks ready for implementation. - Updated references in various skills and documentation to reflect the new task lifecycle, including changes in the `implementer` and `decompose` skills. - Enhanced the README and flow documentation to clarify the new task organization and its implications for the implementation process. These updates improve task management clarity and streamline the implementation workflow.
3.1 KiB
Video Processing Tests
Task: AZ-143_test_video Name: Video Processing Tests Description: Implement E2E tests verifying video frame sampling, annotation interval enforcement, and movement-based tracking Complexity: 3 points Dependencies: AZ-138_test_infrastructure, AZ-142_test_async_sse Component: Integration Tests Jira: AZ-143 Epic: AZ-137
Problem
Video detection processes frames at a configurable interval (frame_period_recognition), enforces minimum annotation intervals (frame_recognition_seconds), and tracks object movement to avoid redundant annotations. Tests must verify these three video-specific behaviors work correctly.
Outcome
- Frame sampling verified: only every Nth frame processed (±10% tolerance)
- Annotation interval enforced: no two annotations closer than configured seconds
- Movement tracking confirmed: annotations emitted on object movement, suppressed for static objects
Scope
Included
- FT-P-10: Video frame sampling processes every Nth frame
- FT-P-11: Video annotation interval enforcement
- FT-P-12: Video tracking accepts new annotations on movement
Excluded
- Async detection initiation (covered in async/SSE tests)
- SSE delivery mechanics (covered in async/SSE tests)
- Video processing performance (covered in performance tests)
Acceptance Criteria
AC-1: Frame sampling Given a 10s 30fps video (300 frames) and frame_period_recognition=4 When async detection is triggered Then approximately 75 frames are processed (±10% tolerance)
AC-2: Annotation interval Given a test video and frame_recognition_seconds=2 When async detection is triggered Then minimum gap between consecutive annotation events >= 2 seconds
AC-3: Movement tracking Given a test video with moving objects and tracking_distance_confidence > 0 When async detection is triggered Then annotations contain updated positions for moving objects And static objects do not generate redundant annotations
Non-Functional Requirements
Performance
- Video processing completes within 120s
Integration Tests
| AC Ref | Initial Data/Conditions | What to Test | Expected Behavior | NFR References |
|---|---|---|---|---|
| AC-1 | Engine warm, SSE connected, test-video, frame_period=4 | Count processed frames via SSE | ~75 frames (±10%) | Max 120s |
| AC-2 | Engine warm, SSE connected, test-video, frame_recognition_seconds=2 | Measure time between annotations | >= 2s gap between annotations | Max 120s |
| AC-3 | Engine warm, SSE connected, test-video, tracking config | Inspect annotation positions | Updated coords for moving objects | Max 120s |
Constraints
- Test video must contain moving objects for tracking verification
- Frame counting tolerance accounts for start/end frame edge cases
- Annotation interval measurement requires clock precision within 0.5s
Risks & Mitigation
Risk 1: Inconsistent frame counts
- Risk: Frame sampling may vary slightly depending on video codec and frame extraction
- Mitigation: Use ±10% tolerance as specified in test spec