This repository provides a template for training YOLO models on custom datasets (primarily from Kaggle) and performing inference. It includes command-line scripts for training and inference, a Streamlit app for interactive use, a Jupyter notebook for step-by-step execution, and utility scripts for data preprocessing, dataset exploration, and auto-labeling. The system allows users to download datasets, preprocess them (cleaning and augmentation), train YOLO models of various sizes, run inference on images/videos/webcam, export models to NCNN format, and automatically label images using GroundingDINO. The code is structured into modular components, with notable reusable parts in the data preprocessing and dataset exploration modules.