Etho presentation mode

Score animal behavior from plain-English definitions

Upload lab video, describe each behavior in words, and get a scored ethogram, metrics and an auditable methods report. Every model call is logged and costed.

Precomputed showcase runs (open instantly, zero spend)

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Try it yourself: a 60 s sample clip

Download this clip to see the definitions it is scored with. The whole pipeline takes about 90 s on this clip. The clip is from the dataset's development split.

Clip from CalMS21 (Sun et al. 2021, Caltech), licensed CC BY 4.0

Links: CalMS21 dataset, CC BY 4.0 licence. This clip was trimmed to 60 s and re-encoded from a longer CalMS21 recording.

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Behavior definitions to paste

The dataset authors' definitions (Segalin et al., MARS, eLife 2021). They are already filled in on the upload form; paste them as they are if you edit the form. Subject: . Partner: .

Privacy notice. Uploads are processed by Meta's Model API in Standard mode. Meta states that it "does not use your Content from Standard Services to train Meta Models" and keeps API content as described in its Terms and Privacy Policy (Meta Model API Data Commitments). Frame strips from your video are sent to Fireworks (Muse Spark Open) for the tier-1 checks; Fireworks and Meta keep request logs under their own policies. Within about 24 hours after upload, the video, its results and every intermediate file made from it are deleted from this server. The clips uploaded to Meta's Files API for tracking are deleted there through its API right after tracking, again when the job ends, and again at that deadline if an attempt failed. Kept longer: detector code written from your behavior definitions (no video or user data; it is reused when someone writes the same definition), the spend ledger (job id, times, token counts, cost, and the phrase used to find the animals), and server logs that include job links. Revising a showcase also uses the Standard models. Only upload video you have the right to share. Detector code runs in a local sandbox. The app estimates the cost before starting and refuses a job that would pass its spend cap.