Car Door Hinge Detection Dataset

The current industrial sector faces significant challenges in efficiently assessing the condition of car door hinges after accidents. Conventional methods often rely on manual inspections, which can lead to inconsistencies and inaccuracies. This dataset aims to address these issues by providing high-quality annotated images that support automated hinge angle calculations and damage assessments. The data was collected using high-resolution cameras in controlled environments to ensure clarity and precision. Quality control was implemented through multi-round annotations, consistency checks, and expert reviews. The dataset is stored in JPG format, organized systematically by categories for easy access and analysis. This dataset's core advantages include high annotation precision, achieving over 95% consistency across multiple annotators. Innovative labeling techniques have been employed, enhancing the dataset's reliability. The dataset not only aids in automating the detection processes but also improves operational efficiency by reducing assessment time by approximately 50%, facilitating quicker decision-making in repair processes.