Review camera-trap datasets locally.

Use AI for triage, not unquestioned ground truth

Camera-trap images vary by habitat, geography, season, camera model, illumination and animal distance. A species model that performs well on one project may behave differently on another. TrailEye therefore keeps predictions reviewable and supports correction rather than presenting automation as expert certainty.

Before operational use, evaluate detection recall and species precision on a representative, permissioned sample from your own deployment. Retain a human verification step for project-critical records and document the software version, model, settings and review protocol used.

Local-first processing for sensitive field data

Camera-trap datasets can reveal endangered-species locations, private land, personnel movements and bystanders. TrailEye’s standard detector runs locally on the Windows computer and does not require the archive to be placed in a hosted gallery. This can help teams working with limited connectivity or data-governance constraints.

Some functions may still use a network connection: maps can load online tiles, licence operations may contact the licensing service, and an optional cloud text-prompt search sends selected images to a provider chosen by the user. Projects requiring strict offline operation should assess and disable network-dependent features.

Timestamp recovery and audit context

Trail cameras frequently burn date and time into image pixels, and metadata may be absent or unreliable. TrailEye can apply OCR to the visible overlay, then use EXIF or file time as fallbacks. The recovered timestamp and confidence should be reviewed where timing affects analysis.

Activity exploration and camera sites

After review, TrailEye can summarize observations by species, hour and day and provide heatmaps, sun-period and moon context. Camera sites can be placed manually or derived from photo GPS where available. These views support exploration; researchers should conduct formal statistical analysis in an appropriate downstream environment.

Choosing an edition for a project

• Free: suitable for evaluating the complete recognition workflow on up to 20 files per analysis.
• Explorer: up to 1,000 files from one folder per run on one computer.
• Professional: unlimited files, folder-tree scanning and three computer activations for multi-camera projects.

Professional removes workflow limits but does not turn AI predictions into validated biological labels. Project-level validation remains essential.