yolo-research-guide

What problem does it solve?

It helps you complete an end-to-end YOLO object detection research workflow without getting stuck between environment setup, dataset formatting, baseline training, model improvements, experiments, and thesis-ready evidence.

Core Features & Use Cases

• Interactive Chinese stage-by-stage guidance: Diagnoses your current project state and advances through environment check → topic definition → dataset plan → baseline → improvement → ablation/comparison → visualization → demo system.
• Beginner-friendly decision discipline: Uses recommended options (typically 2–3) and limits question scope to short confirmations, including a conservative “default” path when the user is unsure.
• Research engineering outputs: Produces concrete artifacts such as data.yaml/check reports, training/validation commands, experiment tables, plots, error analysis, and a runnable demo plan.

Quick Start

Use yolo-research-guide to guide me through a YOLO research project step by step, starting with a read-only check of my current workspace and then asking me to confirm the next choice.