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생산성 및 협업 · SKILL.md

prediction

prediction

Routes UltralyticsPro prediction workflows for YOLO image inference presets and their shared sample-image defaults.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: prediction description: "Routes UltralyticsPro prediction workflows for YOLO image inference presets and their shared sample-image defaults." disable-model-invocation: true metadata: disco-role: operating license: NO_LICENSE

Prediction

Use this sub-skill when the user wants to run or adapt one of the repository's single-image prediction wrappers.

Typical triggers

  • "predict on Zidane"
  • "run the YOLOv11 inference example"
  • "switch the model weight or confidence threshold"
  • "why did the prediction script try to download a weight file?"
  • "how do I save the output image?"

What belongs here

  • The prediction wrappers that mirror predict_v8.py, predict_yolo11.py, and predict_yolov10.py.
  • Model weight selection, input source selection, image size, confidence, saving, and output naming for those examples.
  • Dry-run planning before a real inference run.
  • Troubleshooting for first-run weight downloads, missing source images, output paths, and device selection.

What stays out

  • Training, finetuning, or resume workflows. Use sub-skills/training instead.
  • Upstream library source changes.
  • Export, tracking, benchmark, or video-streaming workflows that the repository does not wrap directly.

First reads

  1. references/workflows.md for the preset-to-script map and the canonical command forms.
  2. references/troubleshooting.md for weight, source, save-path, and device failures.
  3. ../../references/interface-reference.md when you need verified Ultralytics API or CLI details.
  4. ../../references/model-family-map.md when you need the broader source script inventory.

Bundled helper

  • scripts/run_predict.py — preferred wrapper for all prediction presets. It is safe by default and performs a dry run unless --execute is supplied.

How to use the helper

  • Start with --list-presets when you are mapping a source script to the bundled preset.
  • Use --preset predict-yolo11 or another preset when you want the same model and sample image pair as a source example.
  • Override --model, --source, --imgsz, --conf, --save, --device, --project, or --name when a user asks for a variation.
  • Pass --execute only after confirming that the model weights and source are available and that the user is willing to start a real inference run.

Common decisions

  • The default source is the packaged ultralytics/assets/zidane.jpg sample, which is shipped with the verified public Ultralytics install.
  • If the model weight name ends in .pt, the first execution may download the pretrained weights when they are not already cached.
  • If the user only needs to inspect the parameters, stay in dry-run mode and read the printed plan instead of launching inference.

When to escalate to the root skill

Go back to SKILL.md if the task turns into general package inspection, installation, or route selection across training and prediction.

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