Road Condition Image Annotation for Autonomous Driving
Contributed to a project focused on assessing road conditions for autonomous driving systems by annotating high-resolution road imagery. Performed data labeling tasks, including drawing bounding boxes around road issues such as potholes, cracks, and obstacles, to create high-quality datasets for training computer vision models. The project involved processing hundreds of images, ensuring precise annotations to support AI model accuracy. Implemented quality measures, such as cross-checking annotations with team members and adhering to predefined labeling guidelines, to maintain consistency and reliability. My proficiency in Python and attention to detail ensured efficient and accurate labeling, directly supporting the development of safer autonomous driving technology.