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效率与协作 · SKILL.md

configuration-models

configuration-models

【效率与协作】Inspect, edit, validate, and reason about PySOT YACS configs, model builders, tracker mappings, model-zoo naming, and safe model construction.

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技能说明

GitHub

name: configuration-models description: "Inspect, edit, validate, and reason about PySOT YACS configs, model builders, tracker mappings, model-zoo naming, and safe model construction." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

PySOT configuration and model guidance

Use this sub-skill when the task is about PySOT experiment YAMLs, cfg keys, META_ARC, model-family selection, backbone/RPN/head/neck/tracker mappings, model-zoo names, or safe construction of ModelBuilder/build_tracker without running a benchmark or training job.

Read this sub-skill when

  • A user asks to edit, compare, or validate a PySOT config file.
  • A user asks which SiamRPN, SiamMask, long-term, AlexNet, ResNet, or MobileNetV2 variant fits a task.
  • A user asks what META_ARC, TRACK.TYPE, ANCHOR.*, RPN.KWARGS.anchor_num, TRAIN.OUTPUT_SIZE, or BACKBONE.KWARGS.used_layers means.
  • A user gets KeyError, missing-key, anchor-count, size not match!, ModelBuilder, or build_tracker failures while loading a config or building the model graph.
  • A user wants a safe preflight before using a snapshot, running a demo/test, or starting training.

Route elsewhere

  • Demo, video/webcam/image-folder tracking, snapshot loading, and benchmark test execution: read sibling tracking-inference.
  • Training datasets, crop/annotation formats, distributed launch, pretrained training backbones, and training data validation: read sibling training-data.
  • Benchmark dataset/result directory layouts, OPE/EAO/AR/F1 metrics, eval.py, and hyperparameter-search result interpretation: read sibling evaluation-toolkit.
  • Cross-cutting install/import/backend guidance belongs in the root PySOT troubleshooting reference; keep config/model-specific diagnosis here.

Operating workflow

  1. Identify the user-supplied PySOT config path and the intended workflow: model choice, config edit, construction smoke, tracking run, training, or evaluation.

  2. Read references/configuration.md for required YAML sections, common model families, safe edit rules, and anchor/output-size formulas.

  3. Read references/model-api.md before writing code that imports cfg, ModelBuilder, or build_tracker.

  4. Read references/model-zoo.md when selecting among model-zoo names or interpreting suffixes such as _otb, _lt, _8gpu, and _16gpu.

  5. Run the bundled validator before any heavy workflow:

    python scripts/validate_config.py --config path/to/config.yaml
    

    If the task specifically asks whether the model graph and tracker can be constructed, add:

    python scripts/validate_config.py --config path/to/config.yaml --instantiate-model
    

    This is a CPU-safe construction smoke: it does not load a snapshot, open video, run inference, launch training, download assets, or evaluate benchmarks.

  6. If validation fails, use references/troubleshooting.md. Fix config keys and rerun validation before routing to execution-oriented sub-skills.

Key safety rules

  • Pair a downloaded snapshot with the config family it was trained for; do not assume a checkpoint can be loaded under a different backbone, RPN, mask, or tracker setting.
  • Treat full benchmark/test/training runs as user-asset and often CUDA-dependent workflows. This sub-skill only validates config/model construction.
  • PySOT's package metadata installs the toolkit distribution; importing pysot normally depends on using the source checkout through PYTHONPATH or an editable-development setup.
  • Do not ask future users to reopen original repository docs or scripts for the information covered here; use the bundled references and helper script.

References and bundled helper

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