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OpenCap Visualizer

OpenCap Visualizer is a Vue.js + Three.js web app for viewing biomechanics data in 3D. This repository contains the browser visualizer, sample data, and a repo-local WebSocket script for replaying an existing visualizer JSON in real time.

It supports OpenCap-style .json, markers .trc, ground-reaction-force .mot, OpenSim .osim + motion .mot, synced video, screenshots, browser recording, timelapse, sharing, and live WebSocket playback.

Links

What Is In This Repo

The packaged Python video renderer lives in a separate repository. To avoid drift, package CLI and API details should be taken from PyPI and the package repo rather than duplicated here.

Quick Start

npm install
npm run serve

Then open http://localhost:3001.

Supported Inputs

  • .json visualizer motion files
  • .trc marker trajectories
  • .mot force files
  • .osim + motion .mot
  • .mp4 and .webm reference videos
  • .pkl / .pickle SMPL or skeleton sequences via drag-and-drop

Example Workflows

The short version is:

  • Motion + markers + GRF + recorded browser video: yes
  • Real-time playback from an existing JSON: yes
  • Continuous labeled video across multiple trials: not yet as a repo-local script

See examples/README.md for concrete examples.

Live Streaming From An Existing JSON

Install the one repo-local dependency:

python -m pip install websockets

Replay one subject:

python live_stream_from_json.py public/samples/walk/sample_mono.json

Replay two subjects:

python live_stream_from_json.py \
  public/samples/walk/sample_mono.json \
  public/samples/walk/sample_wham.json

Then open the visualizer, expand Live IK Stream, and connect to ws://localhost:8765.

Browser Features Confirmed In This Repo

  • Multi-subject overlays with editable trial names
  • Marker visualization
  • Ground reaction force visualization
  • Synced reference video overlay
  • Screenshot export
  • Browser recording to WebM or MP4 when supported by the browser
  • Timelapse mode
  • Shared visualization files/URLs
  • Live WebSocket controls for camera, visibility, notifications, and trial scores

Notes On The Python Package

The paper discusses a separate pip package for automated rendering. That package is real, but it is not implemented in this repository.

Current package docs:

Development

npm install
npm run serve
npm run build