Tableware Placement Structure Image Dataset

With the rapid development of the catering industry, the efficiency and standardization of tableware placement have become a focus of the industry, and existing solutions often rely on manual inspection, which is inefficient and prone to errors. This dataset aims to provide high-quality training data for automated tableware placement systems to address the limitations and inconsistencies of manual operations. Data collection is done by taking tens of thousands of table setting photos under different lighting and environmental conditions, using high-resolution cameras. Strict quality control is employed, including multiple rounds of annotation and consistency checks, reviewed by an expert team with dining industry experience. The annotation team consists of 10 people with extensive experience in image processing and annotation. Data has been cropped, enhanced, and normalized to improve model training effectiveness, ultimately stored in a structured JPG format, systematically organized for easy access.