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name: tracking description: "Guides SiamMask demo, benchmark tracking, VOT/DAVIS/YouTube-VOS evaluation, and tracking hyperparameter tuning workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

SiamMask Tracking and Evaluation

Use this sub-skill when the task is to run or reason about SiamMask inference-time workflows: an OpenCV demo, benchmark tracking outputs, VOT evaluation metrics, or hyperparameter tuning.

Prerequisites

• Read the root install/setup reference first.
• Verify the checkout and Python environment with the root scripts/check_environment.py helper.
• Prepare checkpoint files and datasets before launching native runs; this sub-skill does not download them.
• Use ../data-preparation/SKILL.md if a dataset, VOT JSON, or crop511/benchmark layout is missing.
• Use ../training/SKILL.md if the requested checkpoint must be trained or resumed.

Main Routes

User intent	What to do
"Run the demo" or "track the tennis sample"	Read references/workflows.md, then use scripts/run_tracking.py demo in dry-run mode before adding --run.
"Evaluate/check a checkpoint on VOT"	Read references/workflows.md and references/cli-reference.md. Use scripts/run_tracking.py test with the right experiment, config, checkpoint, dataset, and mask/refine flags.
"Compute VOT metrics from result folders"	Read references/workflows.md. Use scripts/run_tracking.py eval after result directories exist.
"Tune penalty/window/lr/search region"	Read references/workflows.md. Use tune-vot for VOT-style tuning; use tune-vos only with CUDA.
"Why did tracking fail?"	Read references/troubleshooting.md and root troubleshooting.

Bundled Helper

Use scripts/run_tracking.py for command composition and optional execution. It:

• Accepts --repo-root <siammask-checkout> so it is not tied to the checkout used to create this skill.
• Selects experiment working directories such as siammask_sharp, siammask_base, or siamrpn_resnet.
• Prepends the checkout root and experiment directory to PYTHONPATH.
• Prints commands by default and only runs native code when --run is supplied.
• Warns about GUI, checkpoint, dataset, and CUDA requirements before execution.

Example dry-run:

python scripts/run_tracking.py --repo-root <siammask-checkout> test \
  --experiment siammask_sharp \
  --config config_vot18.json \
  --resume <checkpoint.pth> \
  --dataset VOT2018 --mask --refine --cpu

Key Decisions

• Use siammask_sharp with --mask --refine for sharp segmentation masks.
• Use siammask_base with --mask when evaluating the base mask branch without refine.
• Use siamrpn_resnet without --mask/--refine for box-only tracking.
• For VOT reset-based evaluation, expect baseline/<video>/<video>_001.txt result files.
• For DAVIS/YouTube-VOS segmentation, enable mask mode and validate annotation/image layouts in the data-preparation sub-skill.
• Disable visualization on headless servers; use --cpu with test when CUDA is unavailable, but do not assume the interactive demo honors --cpu when CUDA is visible.