baudneo
commented
2 years ago I like this but I would suggest it conform to how the current zones are configured in the per-monitor overrides. New config file syntax is in YAML format BTW (objectconfig.yml, zmeventnotfication.yml, zm_secrets.yml, mlapiconfig.yml). INI
[monitor-1]
parking_area_polygon_zone = polygon,points go,here
man_door_polygon_zone = polygon,points go,here
ignore_zones = [ { 'parking_area': { 'overlap': 0.85, 'labels': 'car,truck' } } ]New 'Neo' YAML
monitors:
1:
# can end in _polygon_zone or _polygonzone
parking_area_polygonzone: polygon,points go,here
man_door_polygon_zone: polygon,points go,here
ignore_zones:
- parking_area:
overlap: 0.85
labels: car,truckI will implement this tonight and test it as much as I can.
hqhoang
Scenario: car parks on driveway most of the time. With tree shadow, cloud, snow, rain, ...triggering the camera, it's easy to get the car detected and alerted over and over.
While
car_past_det_max_diff_areaparam works for cars that park short-term, it doesn't work well for long-term parked cars. Sometimes the detected box is far left or far right of the actual car, especially when it snows. If the detection box is far left then far right, the diff is over the threshold and triggers an alert.What I'm doing for the above scenario is to tap into the websocket notification. In my script that handles the events from websocket, I have a polygon defined as "parking zone" where the car can be anywhere in it. The detected box is then compared against this parking zone:
The above logic works well that the detected box can jump around the actual car without triggering an alert. Sometimes YOLOv4 can even detect a fake car in front of the real car, but it's small and still fit into the parking zone, so that works well to avoid false positive, too (no car that small). While it ignores cars detected in that zone, it doesn't ignore other objects so a person walking into that zone will still get detected and alerted.
Maybe add a new generic param to the config to ignore objects detected in the zone, matching the defined labels with certain overlapping percentage, e.g.: