Export columns

What every column in the CSV and XLSX files means. The two formats hold the same columns; XLSX just puts each table on its own sheet.

There are four tables. Which one you want depends on the question you are asking.

Table	One row is	Use it for
Observations	one species in one event	ecological analysis. Start here
Detections	one box on one photo	model checking, bounding boxes
Files	one photo or video	file lists, finding blanks
Deployments	one camera period	effort, trap nights, locations

Which table should I use?

For "how many animals did I see", use observations. It counts each animal once per event instead of once per photo. See detections, events and observations.

Observations

One row per species per event, with the count. This is the analysis-ready table.

Column	Meaning
event_id	Identifier of the event
deployment_id	Which camera period it came from
event_start	Time of the first photo in the event, camera local time
event_end	Time of the last photo in the event
category	animal, person or vehicle
classification_label	The species label as used by the model
taxon_class	Class, for example mammalia
taxon_order	Order, for example carnivora
taxon_family	Family, for example canidae
taxon_genus	Genus, for example vulpes
taxon_species	Species
scientific_name	Scientific name for display
common_name	Common name for display
count	Number of individuals. Your confirmed number if you set one, otherwise the AI's highest number seen in a single photo
is_confirmed	TRUE if you signed off the count for this event

Detections

One row per box. Use it when you care about individual boxes rather than ecology. Blank files do not appear here.

Column	Meaning
detection_id	Identifier of the box
file_id	Which file it is on
deployment_id	Which camera period
event_id	Which event, empty if not grouped
detection_category	animal, person or vehicle
detection_confidence	How sure the detector was there is something there
classification_label	The current species label. May be your correction
classification_confidence	Score for the current label
ai_classification_label	What the AI originally said, kept even after you change it
ai_classification_confidence	Score for the AI's original label
classification_method	machine or human, who set the current label
is_verified	TRUE if you checked this detection
taxon_class to taxon_species	Taxonomy, broad to specific
scientific_name	Scientific name
common_name	Common name
frame_number	Frame index for videos, empty for photos
bbox_x, bbox_y	Top left corner of the box, 0 to 1
bbox_width, bbox_height	Size of the box, 0 to 1

Box positions are fractions of the image, not pixels. Multiply by the image width and height to get pixels.

To see where the AI was wrong, compare ai_classification_label with classification_label on rows where is_verified is TRUE.

Files

One row per photo or video, whether or not anything was found.

Column	Meaning
file_id	Identifier of the file
deployment_id	Which camera period
event_id	Which event, empty if not grouped
file_type	image or video
relative_path	Path inside the deployment folder
absolute_path	Full path on the machine that ran the analysis
datetime	Capture time, camera local time. Empty if the file had no readable date
observation_type	What the file holds overall: animal, human, vehicle or blank
is_verified	TRUE if every box on the file was checked
notes	Your own notes

observation_type is the only place "blank" appears. Use it to count empty photos.

Deployments

One row per camera period. This is your effort table.

Column	Meaning
deployment_id	Identifier of the camera period
site_name	Name of the location
latitude, longitude	Location in decimal degrees
site_elevation_m	Elevation in metres, if you entered it
site_habitat	Habitat type, if you entered it
site_notes	Your notes on the site
site_tags	Your tags on the site
deployment_start	First day of the period
deployment_end	Last day, empty if the camera is still out
trap_nights	Days the camera produced photos. See how trap nights are counted
deployment_notes	Your notes on this deployment
deployment_tags	Your tags on this deployment

Folder runs

A folder run writes the same tables, minus the columns that need a project. There is no deployment_id and no notes column, because a folder run has no sites or deployments.

It also writes a recognition file for Timelapse and a text file describing the models and settings used.

Camtrap DP

Projects can also export Camtrap DP, a standard format for camera trap data. It uses its own column names and a fixed structure, so other tools and archives can read your data without knowing anything about AddaxAI. Use it when you share data or deposit it in a repository.