Three-way Catalytic Converter Detection Dataset

The current industrial sector faces significant challenges in verifying environmental compliance and detecting losses of catalytic converters, with many existing solutions lacking in accuracy and efficiency. Current methods often rely on manual inspections which are time-consuming and prone to human error. This dataset aims to address the need for automated, accurate detection and classification of catalytic converters using machine learning techniques. Data is collected through high-resolution cameras in controlled environments to ensure clarity and consistency. Quality control measures include multi-round annotations, consistency checks, and expert reviews to guarantee high standards. The dataset is organized in JPG format, with images stored in a structured directory for easy access and retrieval. Each image is accompanied by metadata that includes quality scores and classification labels.