We demonstrate MaskSearch, a system designed to accelerate queries over
databases of image masks generated by machine learning models. MaskSearch
formalizes and accelerates a new category of queries for retrieving images and
their corresponding masks based on mask properties, which support various
applications, from identifying spurious correlations learned by models to
exploring discrepancies between model saliency and human attention. This
demonstration makes the following contributions:(1) the introduction of
MaskSearch's graphical user interface (GUI), which enables interactive
exploration of image databases through mask properties, (2) hands-on
opportunities for users to explore MaskSearch's capabilities and constraints
within machine learning workflows, and (3) an opportunity for conference
attendees to understand how MaskSearch accelerates queries over image masks.

我们展示了 MaskSearch，这是一个用于加速机器学习模型生成的图像掩码数据库的查询的系统。MaskSearch 通过掩码属性形式化和加速了一类新的查询，用于根据掩码属性检索图像及其对应的掩码，支持从识别模型学习到的虚假相关性到探索模型显著性和人类注意力之间的差异等各种应用。