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name: image-detection description: "Guide pytorch-yolo-v3 image and directory detection, preprocessing, postprocessing, NMS, output interpretation, and safe smoke checks." disable-model-invocation: true metadata: disco-role: operating license: NO_LICENSE

Image Detection

Use this sub-skill when a user asks to run or debug image/file-directory inference with the pytorch-yolo-v3 detector, interpret detector outputs, validate image preprocessing/postprocessing helpers, or perform a safe dry run that does not need weights.

Route first

• Model architecture, cfg details, class-name/weight compatibility, or weight-loading internals: route to ../model-and-config/SKILL.md.
• Video files, camera capture, GUI loops, or fp16 demo loops: route to ../video-camera-demos/SKILL.md.
• Training, fine-tuning, dataset preparation for training, and weight downloads are out of scope.

Safe operating policy

• Do not download weights, fetch data, open a GUI, use a camera, or write into a user's image directory as a default check.
• Actual image inference needs user-supplied local YOLO weights plus a matching cfg/classes setup; the bundled smoke helper deliberately does not load weights.
• Prefer CPU-safe checks first. CUDA can accelerate actual inference when PyTorch reports an available CUDA device, but do not require CUDA for preprocessing/postprocessing validation.
• When constructing an actual detection command, use only user-approved local image paths, output directories, cfg files, and weight files.

What to consult inside this sub-skill

• references/image-workflow.md for image/directory discovery, exact detector flags, command templates, output naming, and result interpretation.

• references/preprocessing-postprocessing.md for the distilled preprocessing and postprocessing API contracts.

• references/troubleshooting.md for missing weights, no detections, bad resolution, image I/O, class/cfg/weight mismatch, CPU/CUDA, pandas, and palette failures.

• scripts/check_image_pipeline.py for a deterministic smoke check that creates a tiny image and exercises preprocessing, IoU, and NMS-style postprocessing without weights:

  python scripts/check_image_pipeline.py --reso 64
  

  To inspect a user's checkout modules without reading source files, pass the checkout root explicitly:

  python scripts/check_image_pipeline.py --repo-root <repo-root> --reso 64
  

• scripts/run_image_detection.py for a bundled dry-run/launcher wrapper around the repository image detector. It validates local paths and prints the command by default; add --execute only after the user approves loading local weights and writing annotated outputs:

  python scripts/run_image_detection.py --repo-root <repo-root> --images <image-or-dir> --det <output-dir> --weights <weights-file>