Glasses-in-the Wild Dataset

The Glasses-in-the-Wild dataset is a collection of 1,000 RGB images of transparent and partially filled glasses, captured in diverse real-world environments. It was crowdsourced from 11 participants and includes 93 unique glass types across 60 different scenes with varying backgrounds, lighting conditions, reflections, occlusions, and distractors. Each image is annotated with bounding boxes and semantically meaningful keypoints, including the rim, base, and liquid level, to facilitate the training of models for transparent object detection and liquid level estimation. The dataset contains a broad distribution of liquid levels: 24.3% of glasses are empty, while 75.7% contain liquid, with an average fill of 48%. This dataset complements existing transparent object datasets by providing a wider variety of glass shapes, sizes, colors, and real-world conditions, supporting robust training for robotic perception systems and other computer vision applications involving transparent containers.野外玻璃杯（Glasses-in-the-Wild）数据集是一个包含1000张RGB图像的集合，素材为透明及半盛液体的玻璃杯，采集自多样化的真实世界场景。该数据集由11名参与者众包构建，涵盖60个不同场景下的93种独特玻璃杯款式，各场景的背景、光照条件、反射效果、遮挡情况及干扰物均存在差异。 每张图像均标注有边界框与语义关键特征点，包括杯沿、杯底及液面，以助力透明物体检测与液面预估相关模型的训练。该数据集的液面高度分布跨度较大：其中24.3%的玻璃杯为空杯，75.7%的杯内盛有液体，平均填充率为48%。 本数据集通过提供更丰富的玻璃杯形状、尺寸、色彩及真实场景条件，对现有透明物体数据集形成补充，可为机器人感知系统及其他涉及透明容器的计算机视觉应用提供鲁棒的模型训练支撑。