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Pull Request Overview
This PR adds a new example notebook demonstrating an NVR (Network Video Recorder) system triggered by object detection. The system processes video streams using person detection models and generates notifications with video clips when persons are detected in specified zones.
- Adds a complete Jupyter notebook example showing smart NVR implementation with object detection, tracking, zone detection, and automated notifications
- Integrates the new notebook into the test suite to ensure it runs correctly
- Updates documentation to include the new example in the applications table
Reviewed Changes
Copilot reviewed 3 out of 4 changed files in this pull request and generated 1 comment.
| File | Description |
|---|---|
| examples/applications/smart_nvr.ipynb | New notebook implementing NVR with object detection, zone monitoring, and automated clip saving |
| tests/test_notebooks.py | Adds test configuration for the new smart_nvr notebook |
| README.md | Updates applications table to include the new smart NVR example |
| "hw_location = \"@cloud\"\n", | ||
| "model_zoo_url = \"degirum/public\"\n", | ||
| "model_name = \"yolo_v5s_person_det--512x512_quant_n2x_orca1_1\"\n", | ||
| "video_source = \"../../images/WalkingPerson.mp4\"\n", |
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The video file path '../../images/WalkingPerson.mp4' appears to be inconsistent with the test configuration in test_notebooks.py which uses 'Masked.mp4'. This could cause the test to fail or use a different video file than intended.
Suggested change
| "video_source = \"../../images/WalkingPerson.mp4\"\n", | |
| "video_source = \"../../images/Masked.mp4\"\n", |
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