A Multi-Attribute Dataset of Commercial Bottles

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.

本仓库收录了一套经精心整理的商用啤酒瓶高分辨率图像数据集，共计5431张，专为计算机视觉与机器学习研究量身打造。

每张图像均对应一套受控的啤酒瓶属性配置，涵盖以下属性：
瓶型、玻璃颜色、灌装液位、液体颜色、标签存在状态、瓶盖状态。

该数据集采用确定性文件命名规范，可直接对上述属性进行编码，结构清晰且易于解析。

除原始图像外，本数据集还附带机器可读的JSON格式标注文件，以及一套用于数据整理、验证与统计分析的Python实用脚本。这既保障了数据集的完整性，也为研究人员提供了可直接用于图像处理、目标检测或分类流程的现成工具。

命名约定
文件命名遵循如下格式：
{type}_{color}_{fill}_{liquid}_{label}_{cap}_{index}.{extension}

示例：vichy_brown_filled_light_labeled_crowned_001.jpg

其中每个字段均对应啤酒瓶的一个分类属性。