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name: evaluation-demos description: "Plan VOC evaluation, test-output inspection, notebook demos, and webcam prerequisites for ssd.pytorch." metadata: disco-role: operating disable-model-invocation: true license: MIT

evaluation-demos

Use this sub-skill when the task is to plan or diagnose ssd.pytorch evaluation, text test outputs, notebook-style image demos, or live webcam demos.

Choose this sub-skill for

• VOC2007 mAP evaluation command planning with eval.py.
• Prediction/ground-truth text dump planning with test.py.
• Understanding result file formats, AP summaries, confidence thresholds, top-k choices, and evaluation output locations.
• Checking static demo prerequisites for notebook and live webcam workflows.
• Explaining why full mAP reproduction requires both VOC2007 test data and a compatible trained SSD300 VOC weight file.

Do not handle here

• Dataset download, VOC directory repair, or dataset layout validation beyond naming the required VOC2007 files. Route that work to ../data-training/SKILL.md.
• Model construction, SSD weight/key compatibility, or modern PyTorch Detect(Function) patching. Route that work to ../model-inference/SKILL.md.
• Opening a webcam, displaying GUI windows, or running a full mAP benchmark from this skill's bundled scripts.

Fast workflow

1. Read references/evaluation-and-test.md before planning eval.py or test.py runs.
2. Use scripts/plan_evaluation_command.py to print a safe command template without executing the repository scripts.
3. Read references/demo-workflows.md before notebook or webcam demo work.
4. Use scripts/check_demo_requirements.py for import-only checks of torch, cv2, imutils, Jupyter components, and optional CUDA availability. It does not access a camera or open a GUI window.
5. If an attempted evaluation or demo fails, first classify the symptom with references/troubleshooting.md, then route model or dataset fixes to the sibling sub-skill named above.

Required planning inputs

• trained_model: path to a compatible SSD300 VOC .pth state_dict.
• voc_root: VOCdevkit root for VOC2007 test/val data when using evaluation or dataset-backed notebook examples.
• save_folder: output folder for test.py and parser-created evaluation folders; use a trailing separator for test.py legacy string concatenation.
• CUDA intent: CPU-only, CUDA if available, or CUDA required.
• Threshold intent: low confidence for mAP, higher visual thresholds for demos.

Safety defaults

• Do not promise the README mAP values unless VOC2007 test data, compatible weights, dependency versions, and legacy model-forward compatibility are all verified in the runtime environment.
• Prefer CPU command templates when hardware is unknown.
• Treat webcam and notebook demos as optional demonstrations, not benchmark evidence.