The glossary explains terms commonly used in Frigate's documentation.
A box returned from the object detection model that outlines an object in the frame. These have multiple colors depending on object type in the debug live view.
The time period starting when a tracked object entered the frame and ending when it left the frame, including any time that the object remained still. Events are saved when it is considered a true positive and meets the requirements for a snapshot or recording to be saved.
An incorrect detection of an object type. For example a dog being detected as a person, a chair being detected as a dog, etc. A person being detected in an area you want to ignore is not a false positive.
There are two types of masks in Frigate. See the mask docs for more info
Motion masks prevent detection of motion in masked areas from triggering Frigate to run object detection, but do not prevent objects from being detected if object detection runs due to motion in nearby areas. For example: camera timestamps, skies, the tops of trees, etc.
Object filter masks drop any bounding boxes where the bottom center (overlap doesn't matter) is in the masked area. It forces them to be considered a false positive so that they are ignored.
The lowest score that an object can be detected with during tracking, any detection with a lower score will be assumed to be a false positive
When pixels in the current camera frame are different than previous frames. When many nearby pixels are different in the current frame they grouped together and indicated with a red motion box in the live debug view. See the motion detection docs for more info
A portion of the camera frame that is sent to object detection, regions can be sent due to motion, active objects, or occasionally for stationary objects. These are represented by green boxes in the debug live view.
The score shown in a snapshot is the score of that object at that specific moment in time.
The threshold is the median score that an object must reach in order to be considered a true positive.
The top score for an object is the highest median score for an object.