Testing

The zmeventnotificationNg project has two tiers of tests: unit tests that need no special hardware, and end-to-end (e2e) tests that run real ML models through the full config-to-detection chain.

None of the tests require a running ZoneMinder instance.

Running all tests

cd zmeventnotificationNg

# Perl tests
prove -I t/lib -I . -r t/

# Python tests (unit + e2e)
cd hook && python3 -m pytest tests/ -v && cd ..

Unit / integration tests

These tests mock pyzmNg and use no real models. They run anywhere:

# Perl
prove -I t/lib -I . -r t/

# Python
pip install pytest pyyaml
cd hook && python3 -m pytest tests/ -m "not e2e" -v

End-to-end tests

The hook/tests/test_e2e/ directory contains tests that exercise the full objectconfig YAML → pyzmNg detection → output chain using real YOLO models and a real test image (bird.jpg, included in the repo).

These tests use real pyzmNg (installed as a system library, not mocked) and call the same functions that zm_detect.py uses: process_config() → secret substitution → Detector.from_dict() → detector.detect() → format_detection_output().

Prerequisites:

• pyzm installed (pip install pyzm or from source)

• ML models at /var/lib/zmeventnotification/models/ (at least one YOLO model, e.g. yolov4/ or ultralytics/)

• Python packages: opencv-python, numpy, shapely

Run all e2e tests:

cd hook
python3 -m pytest tests/test_e2e/ -v

Run a single test file:

python3 -m pytest tests/test_e2e/test_pattern_config.py -v

Test file reference

File	Tests	What it covers
test_config_to_detect.py	5	Full config→detect→output chain, output format, show_percent, image in matched_data, ${base_data_path} substitution
test_secret_chain.py	2	!TOKEN secret substitution in model paths and general config fields
test_pattern_config.py	3	Restrictive pattern (no matches), broad pattern (matches), specific label-only pattern
test_confidence_config.py	3	High threshold filters, low threshold keeps, low vs high comparison
test_disabled_config.py	2	enabled=no produces nothing, mixed enabled/disabled
test_monitor_config.py	3	Per-monitor ml_sequence override, zone parsing, per-monitor config key override (show_percent)
test_multi_model_config.py	2	UNION strategy (both models), FIRST strategy (first model only)
test_zone_config.py	3	Full-image zone keeps detections, tiny zone filters all, zone with restrictive pattern
test_format_chain.py	3	JSON roundtrip validity, label-confidence correlation, bounding box coordinates valid

Test dependencies

Tier	Dependencies
Perl	Test::More, YAML::XS, JSON, Time::Piece
Python (unit)	pytest, pyyaml
Python (e2e)	all of the above plus pyzmNg, opencv-python, numpy, shapely

Pytest markers

Marker	Description
e2e	End-to-end tests requiring real pyzmNg, models, and images on disk