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.