Gear Shift Lever Detection Dataset

The current industrial sector faces challenges in ensuring the accuracy and efficiency of manual transmission assembly, particularly in detecting lever misalignment. Existing solutions often lack precision and scalability, leading to increased error rates in assembly lines. This dataset aims to address the technical problem of accurately identifying and classifying gear shift lever positions to enhance assembly quality. The dataset is structured with images collected from various assembly environments under controlled lighting conditions using high-resolution cameras. Quality control measures include multi-round annotations, consistency checks, and expert reviews to ensure high labeling accuracy. The data is organized in JPG format, with each image linked to its respective metadata, ensuring easy access and usability for machine learning tasks.