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Getting Started

Use this page as the fastest path from install to a working Annolid session.

20-Minute Path

  1. Install Annolid with your preferred method from Installation.
  2. Confirm commands resolve:
  3. annolid --help
  4. annolid-run --help
  5. Launch the GUI with annolid.
  6. Open a short sample video.
  7. Label one or more instances on a representative frame.
  8. Run tracking/propagation and review identity consistency.
  9. Export results for downstream analysis.

If this flow works, your environment is ready for full projects.

Quick Environment Check

Recommended development setup in this repository:

uv venv .venv --python 3.11
source .venv/bin/activate
uv pip install -e ".[gui]"

Validate:

annolid --help
annolid-run list-models

First GUI Session Checklist

  • Open video
  • Pick representative frame
  • Add labels/shapes/keypoints
  • Track forward/backward
  • Fix errors early (occlusion, swaps, overlap)
  • Save and export

See Workflows for detailed operating patterns.

First CLI Session Checklist

annolid-run --help
annolid-run list-models
annolid-run help train
annolid-run help predict
annolid-run help train <model>
annolid-run help predict <model>

Use run-config templates under annolid/configs/runs/ for reproducible jobs.

For built-in models, the model help view now shows a grouped quick reference before the full option list.

If you want Annolid Bot to drive those commands for you, use the typed annolid_run path described in Annolid Agent and annolid-run.

Optional Next Layers

Troubleshooting

  • qtpy.QtBindingsNotFoundError: install with .[gui] extra.
  • Missing codecs or video issues: install FFmpeg for your platform.
  • Plugin/model command errors: check active environment and run annolid-run --help.