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yolo-master-agent

Orchestrate YOLO-Master training, validation, and prediction workflows with Ultralytics.

615|138|Updated Dec 26, 2025
Search Tags:#machine learning#object detection#yolo#multimodal inference#open-world analysis
One-click install
npx skills add https://github.com/Tencent/YOLO-Master --skill yolo-master-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: yolo-master-agent
Source: https://github.com/Tencent/YOLO-Master/tree/main/agent
Command: npx skills add https://github.com/Tencent/YOLO-Master --skill yolo-master-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ultralytics, torch, torchvision, openai, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the process of training, validating, and predicting with YOLO-Master, offering advanced features like multimodal inference and open-world analysis.

Core Features & Use Cases

  • End-to-End Workflows: Execute all steps required for YOLO-Master experiments, including training, validation, and prediction.
  • Multimodal Inference: Combine YOLO detection with OpenAI VLM/LLM for advanced image understanding.
  • Open-World Analysis: Leverage LVIS/V3Det taxonomies for open-world object detection and classification.
  • Use Case: Imagine you have a dataset of images for object detection. Use this Skill to train your model, validate its performance on a test set, and then perform open-world inference to identify objects outside the standard COCO category set.

Quick Start

Use the yolo-master-agent to train a YOLO-Master model on the dataset 'coco128.yaml'.

Frequently Asked Questions about yolo-master-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I train and validate a YOLO object detection model end-to-end?▼

To train and validate a YOLO object detection model, orchestrate the experiment workflow to execute training and validation steps sequentially on datasets like 'coco128.yaml'.

What is open-world object detection and how does multimodal inference work?▼

Open-world object detection identifies objects outside standard COCO categories using LVIS/V3Det taxonomies, while multimodal inference combines YOLO detection with OpenAI VLM/LLM for advanced image understanding.

Do I need PyTorch and Ultralytics installed to run YOLO training workflows?▼

Yes, you need Ultralytics, PyTorch (torch), torchvision, and OpenAI installed in your environment to execute YOLO training, validation, and multimodal inference workflows.

Can I use OpenAI VLM and LLM to enhance YOLO image understanding?▼

Yes, multimodal inference combines YOLO detection outputs with OpenAI VLM and LLM capabilities, providing advanced image understanding beyond standard object detection.

How do I detect objects outside the standard COCO category set?▼

To detect objects outside the standard COCO category set, leverage open-world analysis using LVIS or V3Det taxonomies for broader object classification.

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