Add Baseline

Adding a baseline means creating a BaselineVSLAMLAB subclass, registering a pixi feature/environment for its dependencies, and wiring both into Baselines/get_baseline.py.

1. Implement the class: create Baselines/baseline_files/baseline_<name>.py, subclassing BaselineVSLAMLAB (Baselines/BaselineVSLAMLAB.py). There is no template file for baselines — copy the closest existing baseline of similar type (e.g. baseline_droidslam.py for a learned/CUDA method, baseline_orbslam2.py for a classical feature-based method) and adapt it. At minimum implement the abstract hooks:

   • __init__(self, baseline_name, baseline_folder, default_parameters='') — set baseline_path, settings_yaml, labels/colors.
   • build_execute_command(self, exp_it, exp, dataset, sequence_name) — construct the shell command that runs the baseline on a sequence.
   • is_installed(self) — check whether the baseline's environment/weights are already set up.

2. Add a pixi feature in pixi.toml for the baseline's dependencies (mirror [feature.<name>] blocks like [feature.droidslam]):

   • [feature.<name>] — channels/platforms (e.g. platforms = ["linux-64-cuda"] if it needs CUDA).
   • [feature.<name>.tasks] — at minimum a git-clone task pointing at the baseline's source repo, plus execute-mono/execute-rgbd/execute-stereo tasks (whichever modes the baseline supports) that invoke its executable/entrypoint.
   • [feature.<name>.dependencies] — conda/pip packages the baseline needs.
   • Register the environment in the top-level [environments] table: <name> = { features = ["<name>", ...], solve-group = "<name>" } (pin shared cuda*/py* features and a solve-group the way droidslam does, to reuse dependency solves across baselines).

3. Register it in Baselines/get_baseline.py: import the class and add it to the baseline switcher/lookup, following the existing pattern (mirrors Datasets/get_dataset.py's switcher dict).

4. Verify: run pixi run install-baseline to clone/build the new baseline, then pixi run demo <name> <dataset> <sequence> <mode> or a configs/test_exp_<name>.yaml via pixi run vslamlab configs/test_exp_<name>.yaml to confirm it executes end-to-end and produces a trajectory output.

Full reference docs live on the project's GitHub Wiki if more detail is needed.