This repository contains a curated dataset of 5,431 high-resolution images of commercial beer bottles, designed specifically for computer vision and machine learning research. Each image represents a controlled configuration of bottle attributes, including: bottle type glass color fill level liquid color label presence cap state The dataset utilizes a deterministic file naming convention that directly encodes these attributes, making it highly structured and easy to parse. In addition to the raw images, the dataset is accompanied by machine-readable JSON annotations and a suite of Python utility scripts for data curation, validation, and statistical analysis. This ensures the integrity of the dataset and provides researchers with ready-to-use tools for their own image processing, object detection, or classification pipelines. Naming Convention File naming follows the pattern: {type}_{color}_{fill}_{liquid}_{label}_{cap}_{index}.{extension} For example: vichy_brown_filled_light_labeled_crowned_001.jpg Each component corresponds to one categorical attribute of the bottle.