vame-app 0.4.0

An open-source machine learning tool for behavioral segmentation and analyses.

VAME App

A web application for the Variational Animal Motion Encoding (VAME) project — an open-source machine learning tool for behavioral segmentation and analyses.

VAME App runs locally: a Python (Flask) backend wraps the VAME library and serves a React frontend, which you use in your browser.

Requirements

• Python ≥ 3.12
• ffmpeg (needed for some video/image functions)
• A modern browser (Chrome, Edge, Firefox, or Safari)

Install

pip install vame-app

If PyTorch fails to install for your platform, install it first following the official instructions, then re-run pip install vame-app.

Run

vame-app

This starts the local server and opens the app in your browser.

CLI options

vame-app [--host HOST] [--port PORT] [--data-root DIR] [--no-browser] [--dev]

Flag	Default	Purpose
--host	127.0.0.1	Interface to bind. Use 0.0.0.0 to expose on the LAN.
--port	8641	Port to listen on. Use 0 to auto-pick a free port.
--data-root	home directory	Root the in-app file browser may traverse. Restrict this on shared servers.
--no-browser	off	Don't auto-open the browser.
--dev	off	Use the Flask dev server instead of waitress.

Projects are stored under ~/vame-app/projects. --data-root (env VAME_DATA_ROOT) only controls the file browser root, not project storage.

Development

Contributing or running from source? See README-DEV.md.