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Glossary

Terms used across these docs that mean something specific in TRAPPER, alphabetically.

  • AI Classification Job — One run of the AI pipeline submitted for a (Classification Project × Collection) pair. Tracked with a UUID, a job_config snapshot of exactly what was submitted, and a link to a UserRemoteTask following the remote job's lifecycle on the AI Manager. See Run & re-run the AI pipeline.
  • AI Provider — A configured AI model available to a Classification Project — either a TrapperAIProvider (backed by an AI Manager connection) or an ExternalAIProvider (manually configured, no connection). Has a provider_type (detection / classification / depth / pose) and a categories JSON describing what it can predict. See Data model.
  • AI Provider Connection — The credentials + URL pair pointing at one AI Manager instance. Multiple TrapperAIProviders can share one connection. See Configure an AI Manager connection.
  • Calibration sample — A DeploymentCalibrationSample: one reference Resource on a Deployment with marked (bbox, distance, frame_index) points at known real-world distances. Fitting the calibration action over a Deployment's samples produces its Deployment calibration result. There's no separate "calibration deployment" type — any Deployment can have calibration samples attached directly. See Distance estimation.
  • Camtrap DP — The TDWG camera-trap data exchange standard. TRAPPER exports to it and aligns AI provider categories JSON and Sequence/event grouping to its vocabulary. See explanation.
  • Classificator — The schema of attributes (species, sex, age, custom fields, …) that a Classification Project's annotation form is built from. One Classificator can be reused across multiple projects.
  • Classification — The unified model for AI predictions, human edits, and post-approval feedback — see Classification model for the four types (FINAL/AI/USER/FEEDBACK).
  • Classification Project — The unit that ties a Research Project, a Classificator, one or more Collections, AI Providers, and annotators together. See Create a classification project.
  • Collection — A grouped set of Resources, typically one ingestion session (e.g. one SD-card's worth of footage). Becomes the on-disk top-level directory name when ingested via trapper-tools.
  • Coordinator — The host-level process (trapperai-coordinator, package trapperai-core) that runs on the AI Worker machine, not in a container — so it can access GPU/Hailo hardware directly. Dispatches jobs to the installed Runtimes. See AI pipeline architecture.
  • Deployment — A camera placement with a start/end time at a Location — one camera-out-to-pickup session.
  • dynamic_attrs — Shorthand used throughout the code and these docs for ClassificationDynamicAttrs — the per-object (or per-group) observation row attached to an AI/USER/FEEDBACK Classification. See Data model.
  • FEEDBACK (classification type) — A correction logged against an already-approved Classification. Doesn't reopen approval — it's a permanent QC trail.
  • FINAL (classification type) — The container row representing a resource's approved-or-pending state within a project. Has no observation data of its own — reads it via source_classification.
  • frames_msgpack — The zstd-compressed MessagePack file holding per-frame object data for one Classification. See Msgpack contract.
  • Gold standard — A Classification (is_gold_standard=True) reviewed as fully correct — every object identified, classified, and tracked. Used for benchmarking and training data, not a routine annotation state.
  • Group (observation level) — A ClassificationDynamicAttrs row an expert adds by hand to record an aggregate group size, with no bounding box and no individual track. Opposite of the default object level.
  • hypertable / ObjectFrameObservation — A TimescaleDB-backed queryable index of per-frame data, built from frames_msgpack. The extension itself is mandatory; what's on-demand is each project's snapshot being populated into it. Never the source of truth — see Frame timeseries.
  • Predictor — A model-execution unit inside an AI Worker Runtime package (e.g. a depth predictor, a species classifier). Distinct from a Tracker, which links detections across frames rather than producing them.
  • Research Project — The top-level container for a body of camera-trap work — owns Locations, and the Collections/Classification Projects built on top of them.
  • Resource — A single uploaded media file (image or video) within a Collection.
  • Runtime — An installable AI Worker package providing model-execution code for specific hardware/frameworks (e.g. trapperai-trackers-ultralytics, trapperai-predictors-torch-depth, trapperai-predictors-hailo-depth). Installed alongside the Coordinator based on detected hardware.
  • Sequence — An automatically-built grouping of Resources within a Collection into one ecological "event", based on a configurable time interval between consecutive timestamps. Mirrors Camtrap DP's observations.eventID.
  • Tracker — Worker-side logic that links per-frame detections into a multi-frame track (a DetectedObject). See Configure trackers — and that page's caveat about which tracker types are actually user-selectable.
  • USER (classification type) — A human-authored or human-edited Classification, often forked from an AI Classification via source_classification.

See also